| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000025 (GRS) |
PGP000015 | Chouraki V et al. J Alzheimers Dis (2016) |
Alzheimer's disease | Alzheimer disease | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000025/ScoringFiles/PGS000025.txt.gz |
| PGS000026 (PHS) |
PGP000016 | Desikan RS et al. PLoS Med (2017) |
Alzheimer's disease | Alzheimer disease | 33 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000026/ScoringFiles/PGS000026.txt.gz | |
| PGS000038 (PRS90) |
PGP000026 | Rutten-Jacobs LC et al. BMJ (2018) |
Stroke | stroke disorder | 90 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000038/ScoringFiles/PGS000038.txt.gz |
| PGS000039 (metaGRS_ischaemicstroke) |
PGP000027 | Abraham G et al. Nat Commun (2019) |
Ischemic stroke | Ischemic stroke, stroke disorder |
3,225,583 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000039/ScoringFiles/PGS000039.txt.gz | |
| PGS000053 (ALZ21_NIA-LOAD) |
PGP000039 | Tosto G et al. Neurology (2017) |
Alzheimer's disease (late onset) | late-onset Alzheimer's disease | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000053/ScoringFiles/PGS000053.txt.gz |
| PGS000054 (ALZ21_EFIGA) |
PGP000039 | Tosto G et al. Neurology (2017) |
Alzheimer's disease (late onset) | late-onset Alzheimer's disease | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000054/ScoringFiles/PGS000054.txt.gz |
| PGS000056 (PD_PRS) |
PGP000041 | Paul KC et al. JAMA Neurol (2018) |
Parkinson's disease | Parkinson disease | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000056/ScoringFiles/PGS000056.txt.gz |
| PGS000123 (2017_PD16) |
PGP000059 | Ibanez L et al. BMC Neurol (2017) |
Parkinson's disease | Parkinson disease | 16 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000123/ScoringFiles/PGS000123.txt.gz |
| PGS000133 (SCZ_BVU) |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Schizophrenia | schizophrenia | 604,645 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000133/ScoringFiles/PGS000133.txt.gz |
| PGS000134 (SCZ_GHS) |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Schizophrenia | schizophrenia | 830,589 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000134/ScoringFiles/PGS000134.txt.gz |
| PGS000135 (SCZ_MTS) |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Schizophrenia | schizophrenia | 972,439 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000135/ScoringFiles/PGS000135.txt.gz |
| PGS000136 (SCZ_PBK) |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Schizophrenia | schizophrenia | 833,502 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000136/ScoringFiles/PGS000136.txt.gz |
| PGS000138 (LifetimeMDD) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Lifetime Major Depressive Disorder | major depressive disorder | 22,274 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000138/ScoringFiles/PGS000138.txt.gz |
| PGS000139 (MDDRecur) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Lifetime Major Depressive Disorder (with recurrence) | recurrent, major depressive disorder |
21,980 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000139/ScoringFiles/PGS000139.txt.gz |
| PGS000140 (GPpsy) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Broad Depression (seen a General Practitioner for nerves, anxiety, tension or depression) | seeing a general practitioner for nerves, anxiety, tension or depression, self-reported, depressive disorder |
24,665 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000140/ScoringFiles/PGS000140.txt.gz |
| PGS000141 (Psypsy) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Seen a psychiatrist for nerves, anxiety, tension or depression | seeing a psychiatrist for nerves, anxiety, tension or depression, self-reported, depressive disorder |
22,728 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000141/ScoringFiles/PGS000141.txt.gz |
| PGS000142 (DepAll) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Probable Depression (low mood or anhedonia, and seen a GP or psychiatrist for nerves, anxiety, tension or depression) | seeing a general practitioner for nerves, anxiety, tension or depression, self-reported, seeing a psychiatrist for nerves, anxiety, tension or depression, self-reported, depressive disorder |
21,908 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000142/ScoringFiles/PGS000142.txt.gz |
| PGS000145 (ICD10Dep) |
PGP000068 | Cai N et al. Nat Genet (2020) |
Depression (ICD-10 defined) | major depressive disorder | 21,510 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000145/ScoringFiles/PGS000145.txt.gz |
| PGS000155 (cGRS_Glioma) |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Glioma | glioma | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000155/ScoringFiles/PGS000155.txt.gz |
| PGS000193 (MDD_0.001_Coleman_2020) |
PGP000080 | Coleman JRI et al. Mol Psychiatry (2020) |
Major depression | major depressive disorder | 1,138 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000193/ScoringFiles/PGS000193.txt.gz |
| PGS000211 (PD19) |
PGP000087 | Pihlstrøm L et al. Mov Disord (2016) |
Parkinson's disease | Parkinson disease | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000211/ScoringFiles/PGS000211.txt.gz |
| PGS000327 (ASD2019) |
PGP000098 | Grove J et al. Nat Genet (2019) |
Autism spectrum disorder | autism spectrum disorder | 35,087 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000327/ScoringFiles/PGS000327.txt.gz | |
| PGS000334 (GRSfull_22) |
PGP000101 | Zhang Q et al. Nat Commun (2020) |
Late-onset Alzheimer’s disease | late-onset Alzheimer's disease | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000334/ScoringFiles/PGS000334.txt.gz |
| PGS000617 (PRSWEB_PHECODE190_20001-1030_PRS-CS_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Ocular cancer | ocular cancer | 834,009 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000617/ScoringFiles/PGS000617.txt.gz | |
| PGS000618 (PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain and nervous system cancer | central nervous system cancer | 23 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000618/ScoringFiles/PGS000618.txt.gz | |
| PGS000619 (PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain and nervous system cancer | central nervous system cancer | 19 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000619/ScoringFiles/PGS000619.txt.gz | |
| PGS000620 (PRSWEB_PHECODE191.11_C71_LASSOSUM_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 522 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000620/ScoringFiles/PGS000620.txt.gz | |
| PGS000621 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000621/ScoringFiles/PGS000621.txt.gz | |
| PGS000622 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000622/ScoringFiles/PGS000622.txt.gz | |
| PGS000623 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000623/ScoringFiles/PGS000623.txt.gz | |
| PGS000624 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 5 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000624/ScoringFiles/PGS000624.txt.gz | |
| PGS000625 (PRSWEB_PHECODE191.11_UKBB-SAIGE-HRC-X191.11_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Brain cancer | brain cancer | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000625/ScoringFiles/PGS000625.txt.gz | |
| PGS000665 (GRS_32) |
PGP000125 | Marston NA et al. Circulation (2020) |
Ischemic stroke | Ischemic stroke, stroke disorder |
32 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000665/ScoringFiles/PGS000665.txt.gz |
| PGS000750 (PRS_43) |
PGP000155 | Bobbili DR et al. J Med Genet (2020) |
Parkinson's disease | Parkinson disease | 43 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000750/ScoringFiles/PGS000750.txt.gz |
| PGS000756 (GRS3_Nar) |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Narcolepsy | narcolepsy-cataplexy syndrome | 32 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000756/ScoringFiles/PGS000756.txt.gz |
| PGS000757 (GRS4_Nar) |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Narcolepsy | narcolepsy-cataplexy syndrome | 5 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000757/ScoringFiles/PGS000757.txt.gz |
| PGS000762 (PRS_HD) |
PGP000165 | Cherny SS et al. Eur J Hum Genet (2020) |
Hearing difficulty | presbycusis | 100,325 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000762/ScoringFiles/PGS000762.txt.gz |
| PGS000763 (PRS_HAID) |
PGP000165 | Cherny SS et al. Eur J Hum Genet (2020) |
Hearing aid use | presbycusis | 4,270 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000763/ScoringFiles/PGS000763.txt.gz |
| PGS000767 (GRS14) |
PGP000174 | Guffanti G et al. Transl Psychiatry (2019) |
Depression | depressive symptom measurement, major depressive disorder |
14 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000767/ScoringFiles/PGS000767.txt.gz |
| PGS000777 (PHS3_PDD) |
PGP000181 | Liu G et al. Nat Genet (2021) |
Parkinson's disease dementia | cognitive decline measurement, Parkinson disease |
3 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000777/ScoringFiles/PGS000777.txt.gz | |
| PGS000779 (PGS7_AD) |
PGP000183 | Zhou X et al. Alzheimers Dement (Amst) (2020) |
Alzheimer's disease | Alzheimer disease | 7 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000779/ScoringFiles/PGS000779.txt.gz | |
| PGS000781 (GRS7_Glio) |
PGP000185 | Adel Fahmideh M et al. Sci Rep (2019) |
Glioma | glioma, brain neoplasm |
5 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000781/ScoringFiles/PGS000781.txt.gz |
| PGS000809 (PRS127_MS) |
PGP000194 | Barnes CLK et al. Eur J Hum Genet (2021) |
Multiple sclerosis | multiple sclerosis | 127 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000809/ScoringFiles/PGS000809.txt.gz |
| PGS000811 (AD-PRS_39) |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Alzheimer's disease | Alzheimer disease | 39 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000811/ScoringFiles/PGS000811.txt.gz |
| PGS000812 (AD-PRS_57) |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Alzheimer's disease | Alzheimer disease | 57 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000812/ScoringFiles/PGS000812.txt.gz |
| PGS000819 (PRS_DR) |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Diabetic retinopathy | diabetic retinopathy | 3,537,914 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000819/ScoringFiles/PGS000819.txt.gz |
| PGS000823 (GRS23_AD) |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Alzheimer's disease | Alzheimer disease | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000823/ScoringFiles/PGS000823.txt.gz |
| PGS000862 (DR) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Diabetic Retinopathy | diabetic retinopathy | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000862/ScoringFiles/PGS000862.txt.gz |
| PGS000876 (PRS31_AD) |
PGP000222 | Leonenko G et al. Ann Clin Transl Neurol (2019) |
Alzheimer's disease | Alzheimer disease | 31 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000876/ScoringFiles/PGS000876.txt.gz |
| PGS000898 (PRS39_AD) |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Alzheimer's disease | Alzheimer disease | 40 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000898/ScoringFiles/PGS000898.txt.gz | |
| PGS000902 (PRS90_PD) |
PGP000235 | Nalls MA et al. Lancet Neurol (2019) |
Parkinson's disease | Parkinson disease | 90 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000902/ScoringFiles/PGS000902.txt.gz | |
| PGS000903 (PRS1805_PD) |
PGP000235 | Nalls MA et al. Lancet Neurol (2019) |
Parkinson's disease | Parkinson disease | 1,805 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000903/ScoringFiles/PGS000903.txt.gz | |
| PGS000907 (PRS_MDD) |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Major depressive disorder | major depressive disorder | 1,773,528 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000907/ScoringFiles/PGS000907.txt.gz |
| PGS000908 (PRS_Insomnia) |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Insomnia | insomnia | 2,746,982 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000908/ScoringFiles/PGS000908.txt.gz |
| PGS000911 (PRS_IS) |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Ischemic stroke | Ischemic stroke, stroke disorder |
530,933 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000911/ScoringFiles/PGS000911.txt.gz | |
| PGS000929 (GBE_HC1583) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
All-cause dementia (algorithmically-defined) | dementia | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000929/ScoringFiles/PGS000929.txt.gz |
| PGS000945 (GBE_HC710) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Dementia in Alzheimer's disease (time-to-event) | dementia, Alzheimer disease |
26 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000945/ScoringFiles/PGS000945.txt.gz |
| PGS000946 (GBE_HC713) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Unspecified dementia (time-to-event) | dementia | 9 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000946/ScoringFiles/PGS000946.txt.gz |
| PGS000990 (GBE_HC878) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Retinal detachments and breaks (time-to-event) | retinal break, retinal detachment |
237 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000990/ScoringFiles/PGS000990.txt.gz |
| PGS001013 (GBE_BIN_FC5006148) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Macular degeneration | macular degeneration | 53 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001013/ScoringFiles/PGS001013.txt.gz |
| PGS001137 (GBE_HC302) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Retinal detachment | retinal detachment | 321 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001137/ScoringFiles/PGS001137.txt.gz |
| PGS001179 (GBE_HC711) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Vascular dementia (time-to-event) | vascular dementia | 7 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001179/ScoringFiles/PGS001179.txt.gz |
| PGS001252 (GBE_BIN_FC3002247) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hearing difficulty and deafness | deafness, hearing loss disorder |
3,731 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001252/ScoringFiles/PGS001252.txt.gz |
| PGS001253 (GBE_BIN_FC1002247) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hearing difficulty | hearing loss disorder | 3,098 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001253/ScoringFiles/PGS001253.txt.gz |
| PGS001270 (GBE_HC151) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Multiple sclerosis | multiple sclerosis | 41 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001270/ScoringFiles/PGS001270.txt.gz |
| PGS001271 (GBE_HC810) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Multiple sclerosis (time-to-event) | multiple sclerosis | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001271/ScoringFiles/PGS001271.txt.gz |
| PGS001275 (GBE_HC880) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other retinal disorders (time-to-event) | retinal disorder | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001275/ScoringFiles/PGS001275.txt.gz |
| PGS001276 (GBE_HC881) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Retinal disorders in diseases classified elsewhere (time-to-event) | retinal disorder | 185 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001276/ScoringFiles/PGS001276.txt.gz |
| PGS001281 (GBE_HC86) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Migraine | migraine disorder | 25 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001281/ScoringFiles/PGS001281.txt.gz |
| PGS001282 (GBE_HC815) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Migraine (time-to-event) | migraine disorder | 329 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001282/ScoringFiles/PGS001282.txt.gz |
| PGS001348 (GBE_HC1584) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Alzheimer's disease (algorithmically-defined) | Alzheimer disease | 15 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001348/ScoringFiles/PGS001348.txt.gz |
| PGS001349 (GBE_HC807) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Alzheimer's disease (time-to-event) | Alzheimer disease | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001349/ScoringFiles/PGS001349.txt.gz |
| PGS001353 (PRS6_PD) |
PGP000250 | Sia MW et al. Mov Disord (2021) |
Parkinson's disease | Parkinson disease | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001353/ScoringFiles/PGS001353.txt.gz |
| PGS001774 (PRS12_PD) |
PGP000254 | Chairta PP et al. Genes (Basel) (2021) |
Parkinson's disease | Parkinson disease | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001774/ScoringFiles/PGS001774.txt.gz |
| PGS001775 (PRS39_AD) |
PGP000255 | Ebenau JL et al. Alzheimers Dement (Amst) (2021) |
Alzheimer's disease | Alzheimer disease | 39 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001775/ScoringFiles/PGS001775.txt.gz |
| PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Stroke | stroke disorder | 910,099 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001793/ScoringFiles/PGS001793.txt.gz |
| PGS001798 (1kgeur_gbmi_Stroke_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Stroke | stroke disorder | 884,168 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001798/ScoringFiles/PGS001798.txt.gz |
| PGS001808 (portability-PLR_191.11) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Brain cancer | brain cancer | 117 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001808/ScoringFiles/PGS001808.txt.gz |
| PGS001819 (portability-PLR_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 249 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001819/ScoringFiles/PGS001819.txt.gz |
| PGS001827 (portability-PLR_290.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Dementia | dementia | 33 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001827/ScoringFiles/PGS001827.txt.gz |
| PGS001828 (portability-PLR_290.11) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Alzheimer's disease | Alzheimer disease | 38 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001828/ScoringFiles/PGS001828.txt.gz |
| PGS001829 (portability-PLR_296.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Depression | depressive disorder | 7,534 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001829/ScoringFiles/PGS001829.txt.gz |
| PGS001831 (portability-PLR_335) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Multiple sclerosis | multiple sclerosis | 491 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001831/ScoringFiles/PGS001831.txt.gz |
| PGS001832 (portability-PLR_351) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Other peripheral nerve disorders | peripheral nervous system disorder | 8,393 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001832/ScoringFiles/PGS001832.txt.gz |
| PGS001833 (portability-PLR_361) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Retinal detachments and defects | retinal detachment | 3,737 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001833/ScoringFiles/PGS001833.txt.gz |
| PGS001834 (portability-PLR_362.29) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Macular degeneration (senile) of retina NOS | age-related macular degeneration | 157 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001834/ScoringFiles/PGS001834.txt.gz |
| PGS001891 (portability-PLR_bad_hearing) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hearing difficulty/problems | hearing disorder | 19,960 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001891/ScoringFiles/PGS001891.txt.gz |
| PGS001928 (portability-PLR_headaches_for_3m) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Headaches for 3+ months | headache disorder | 5,709 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001928/ScoringFiles/PGS001928.txt.gz |
| PGS001932 (portability-PLR_insomnia) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Sleeplessness / insomnia | insomnia | 37,712 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001932/ScoringFiles/PGS001932.txt.gz |
| PGS002027 (portability-ldpred2_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 389,029 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002027/ScoringFiles/PGS002027.txt.gz |
| PGS002035 (portability-ldpred2_290.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Dementia | dementia | 39,752 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002035/ScoringFiles/PGS002035.txt.gz |
| PGS002036 (portability-ldpred2_296.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Depression | depressive disorder | 807,338 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002036/ScoringFiles/PGS002036.txt.gz |
| PGS002038 (portability-ldpred2_335) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Multiple sclerosis | multiple sclerosis | 129,077 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002038/ScoringFiles/PGS002038.txt.gz |
| PGS002039 (portability-ldpred2_351) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Other peripheral nerve disorders | peripheral nervous system disorder | 799,326 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002039/ScoringFiles/PGS002039.txt.gz |
| PGS002040 (portability-ldpred2_361) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Retinal detachments and defects | retinal detachment | 706,872 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002040/ScoringFiles/PGS002040.txt.gz |
| PGS002041 (portability-ldpred2_362.29) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Macular degeneration (senile) of retina NOS | age-related macular degeneration | 116,538 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002041/ScoringFiles/PGS002041.txt.gz |
| PGS002052 (portability-ldpred2_433.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Occlusion and stenosis of precerebral arteries | occlusion precerebral artery | 490,459 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002052/ScoringFiles/PGS002052.txt.gz |
| PGS002053 (portability-ldpred2_433) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Cerebrovascular disease | cerebrovascular disorder | 599,726 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002053/ScoringFiles/PGS002053.txt.gz |
| PGS002104 (portability-ldpred2_bad_hearing) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hearing difficulty/problems | hearing disorder | 869,179 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002104/ScoringFiles/PGS002104.txt.gz |
| PGS002145 (portability-ldpred2_headaches_for_3m) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Headaches for 3+ months | headache disorder | 720,580 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002145/ScoringFiles/PGS002145.txt.gz |
| PGS002149 (portability-ldpred2_insomnia) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Sleeplessness / insomnia | insomnia | 926,585 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002149/ScoringFiles/PGS002149.txt.gz |
| PGS002249 (AD_PRS_0.5) |
PGP000276 | Lourida I et al. JAMA (2019) |
Alzheimer's disease | Alzheimer disease | 249,273 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002249/ScoringFiles/PGS002249.txt.gz |
| PGS002259 (metaPRS_Stroke) |
PGP000285 | Lu X et al. Neurology (2021) |
Stroke | stroke disorder | 534 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002259/ScoringFiles/PGS002259.txt.gz | |
| PGS002261 (PRS22_NB) |
PGP000287 | Testori A et al. Cancer Epidemiol Biomarkers Prev (2022) |
Neuroblastoma | neuroblastoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002261/ScoringFiles/PGS002261.txt.gz |
| PGS002269 (PRS47_AMD) |
PGP000299 | Zekavat SM et al. Ophthalmology (2022) |
Age-related macular degeneration | age-related macular degeneration | 47 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002269/ScoringFiles/PGS002269.txt.gz |
| PGS002280 (GRS83_AD) |
PGP000309 | Bellenguez C et al. Nat Genet (2022) |
Alzheimer's disease | Alzheimer disease | 83 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002280/ScoringFiles/PGS002280.txt.gz |
| PGS002289 (GRS23_AD) |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Late-onset Alzheimer's disease | late-onset Alzheimer's disease | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002289/ScoringFiles/PGS002289.txt.gz |
| PGS002302 (PRS28_glioma) |
PGP000328 | Choi J et al. Int J Cancer (2020) |
Glioma | glioma | 28 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002302/ScoringFiles/PGS002302.txt.gz |
| PGS002724 (GIGASTROKE_iPGS_EUR) |
PGP000333 | Mishra A et al. Nature (2022) |
Ischemic stroke | Ischemic stroke, stroke disorder |
1,213,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002724/ScoringFiles/PGS002724.txt.gz | |
| PGS002725 (GIGASTROKE_iPGS_EAS) |
PGP000333 | Mishra A et al. Nature (2022) |
Ischemic stroke | Ischemic stroke, stroke disorder |
6,010,730 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002725/ScoringFiles/PGS002725.txt.gz | |
| PGS002726 (PGS_MS_Brain) |
PGP000334 | Shams H et al. Brain (2022) |
Multiple sclerosis | multiple sclerosis | 476,399 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002726/ScoringFiles/PGS002726.txt.gz |
| PGS002731 (oA-PRS) |
PGP000339 | Xicota L et al. Neurology (2022) |
Alzheimer's disease | Alzheimer disease | 17 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002731/ScoringFiles/PGS002731.txt.gz | |
| PGS002746 (PRS_ADHD) |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Attention-deficit hyperactivity disorder | attention deficit-hyperactivity disorder | 513,659 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002746/ScoringFiles/PGS002746.txt.gz |
| PGS002753 (Alzheimer_s_disease_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Alzheimer's disease | Alzheimer disease | 1,092,011 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002753/ScoringFiles/PGS002753.txt.gz |
| PGS002759 (Depression_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Depression | major depressive disorder | 1,091,613 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002759/ScoringFiles/PGS002759.txt.gz |
| PGS002760 (Generalised_epilepsy_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Epilepsy | epilepsy | 835,537 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002760/ScoringFiles/PGS002760.txt.gz |
| PGS002770 (Stroke_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Stroke | stroke disorder | 1,088,719 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002770/ScoringFiles/PGS002770.txt.gz |
| PGS002785 (SCZ_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Schizophrenia | schizophrenia | 964,422 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002785/ScoringFiles/PGS002785.txt.gz |
| PGS002786 (BD_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Bipolar disorder | bipolar disorder | 948,996 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002786/ScoringFiles/PGS002786.txt.gz |
| PGS002787 (BD1_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Type 1 bipolar disorder | bipolar I disorder | 937,511 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002787/ScoringFiles/PGS002787.txt.gz |
| PGS002788 (BD2_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Type 2 bipolar disorder | bipolar II disorder | 935,292 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002788/ScoringFiles/PGS002788.txt.gz |
| PGS002789 (MDD_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Major depressive disorder | major depressive disorder | 943,784 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002789/ScoringFiles/PGS002789.txt.gz |
| PGS002790 (ASD_SDPR) |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Autism spectrum disorder | autism spectrum disorder | 916,713 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002790/ScoringFiles/PGS002790.txt.gz |
| PGS003319 (ExPRSweb_Insomnia_1160_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 578,551 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003319/ScoringFiles/PGS003319.txt.gz | |
| PGS003320 (ExPRSweb_Insomnia_1160_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 147 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003320/ScoringFiles/PGS003320.txt.gz | |
| PGS003321 (ExPRSweb_Insomnia_1160_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 148 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003321/ScoringFiles/PGS003321.txt.gz | |
| PGS003322 (ExPRSweb_Insomnia_1160_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 8,590,163 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003322/ScoringFiles/PGS003322.txt.gz | |
| PGS003323 (ExPRSweb_Insomnia_1160_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003323/ScoringFiles/PGS003323.txt.gz | |
| PGS003324 (ExPRSweb_Insomnia_1200_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 464,576 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003324/ScoringFiles/PGS003324.txt.gz | |
| PGS003325 (ExPRSweb_Insomnia_1200_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 28,289 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003325/ScoringFiles/PGS003325.txt.gz | |
| PGS003326 (ExPRSweb_Insomnia_1200_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 27,462 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003326/ScoringFiles/PGS003326.txt.gz | |
| PGS003327 (ExPRSweb_Insomnia_1200_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 6,214,923 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003327/ScoringFiles/PGS003327.txt.gz | |
| PGS003328 (ExPRSweb_Insomnia_1200_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Insomnia | insomnia | 1,065,129 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003328/ScoringFiles/PGS003328.txt.gz | |
| PGS003333 (MDD-PRS) |
PGP000399 | Fang Y et al. Biol Psychiatry (2022) |
Major Depressive Disorder | major depressive disorder | 1,088,415 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003333/ScoringFiles/PGS003333.txt.gz |
| PGS003334 (PRS_dementia) |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Dementia | dementia | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003334/ScoringFiles/PGS003334.txt.gz |
| PGS003384 (best_GBM) |
PGP000413 | Namba S et al. Cancer Res (2022) |
Glioblastoma | glioblastoma | 910 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003384/ScoringFiles/PGS003384.txt.gz |
| PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm | 6,852,195 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003406/ScoringFiles/PGS003406.txt.gz | |
| PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, male |
6,618,190 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003407/ScoringFiles/PGS003407.txt.gz | |
| PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, female |
6,671,269 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003408/ScoringFiles/PGS003408.txt.gz | |
| PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm | 6,852,195 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003409/ScoringFiles/PGS003409.txt.gz | |
| PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, male |
6,618,190 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003410/ScoringFiles/PGS003410.txt.gz | |
| PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, female |
6,671,269 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003411/ScoringFiles/PGS003411.txt.gz | |
| PGS003440 (GRS11_nonapoeAD) |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Alzheimer's disease in non APOE | APOE carrier status, Alzheimer disease |
11 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003440/ScoringFiles/PGS003440.txt.gz |
| PGS003441 (GRS28_AD) |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Alzheimer's disease | Alzheimer disease | 28 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003441/ScoringFiles/PGS003441.txt.gz |
| PGS003442 (GRS8_MD) |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Major depressive disorder | major depressive disorder | 8 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003442/ScoringFiles/PGS003442.txt.gz |
| PGS003457 (GRS_ICH) |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Intracerebral hemorrhage | intracerebral hemorrhage | 682,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003457/ScoringFiles/PGS003457.txt.gz | |
| PGS003574 (GRS_Dementia21) |
PGP000459 | Mukadam N et al. PLoS One (2022) |
Alzheimer's disease (late onset) | Alzheimer disease | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003574/ScoringFiles/PGS003574.txt.gz |
| PGS003576 (AutoImpAll.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 5,776,312 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003576/ScoringFiles/PGS003576.txt.gz | |
| PGS003577 (AutoImpOnly.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 5,776,312 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003577/ScoringFiles/PGS003577.txt.gz | |
| PGS003578 (MTAG.All.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,786,322 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003578/ScoringFiles/PGS003578.txt.gz | |
| PGS003579 (MTAG.AllDep.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,786,322 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003579/ScoringFiles/PGS003579.txt.gz | |
| PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,786,322 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003580/ScoringFiles/PGS003580.txt.gz | |
| PGS003581 (MTAG.Envs.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,861,398 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003581/ScoringFiles/PGS003581.txt.gz | |
| PGS003582 (MTAG.FamHist.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,861,398 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003582/ScoringFiles/PGS003582.txt.gz | |
| PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 4,861,398 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003583/ScoringFiles/PGS003583.txt.gz | |
| PGS003584 (SoftImpAll.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 5,776,312 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003584/ScoringFiles/PGS003584.txt.gz | |
| PGS003585 (SoftImpOnly.LifetimeMDD) |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Major Depressive Disorder (Lifetime) | major depressive disorder | 5,776,312 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003585/ScoringFiles/PGS003585.txt.gz | |
| PGS003737 (PRS26_BrC) |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Brain cancer | brain neoplasm | 26 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003737/ScoringFiles/PGS003737.txt.gz | |
| PGS003753 (PRS35445_ADHD) |
PGP000473 | Sato JR et al. Genes Brain Behav (2023) |
Attention deficit hyperactivity disorder | attention deficit-hyperactivity disorder | 35,445 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003753/ScoringFiles/PGS003753.txt.gz |
| PGS003763 (PRS44_PD) |
PGP000486 | Zheng Z et al. JAMA Neurol (2023) |
Parkinson's disease | Parkinson disease | 44 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003763/ScoringFiles/PGS003763.txt.gz |
| PGS003953 (AD_Bellenguez) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 1,937 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003953/ScoringFiles/PGS003953.txt.gz |
| PGS003954 (AD_FINNGEN) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 81 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003954/ScoringFiles/PGS003954.txt.gz |
| PGS003955 (AD_Jun) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 85 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003955/ScoringFiles/PGS003955.txt.gz |
| PGS003956 (AD_Kunkle_AFR) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 157 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003956/ScoringFiles/PGS003956.txt.gz |
| PGS003957 (AD_Kunkle) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 12,002 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003957/ScoringFiles/PGS003957.txt.gz |
| PGS003958 (AD_Unweighted_PRSsum) |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 14,109 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003958/ScoringFiles/PGS003958.txt.gz |
| PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,121,845 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003984/ScoringFiles/PGS003984.txt.gz | |
| PGS003992 (dbslmm.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 1,136,212 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003992/ScoringFiles/PGS003992.txt.gz |
| PGS004000 (lassosum.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 2,371 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004000/ScoringFiles/PGS004000.txt.gz | |
| PGS004008 (lassosum.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 5,663 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004008/ScoringFiles/PGS004008.txt.gz |
| PGS004015 (lassosum.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 65,138 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004015/ScoringFiles/PGS004015.txt.gz | |
| PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004026/ScoringFiles/PGS004026.txt.gz | |
| PGS004034 (ldpred2.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 1,046,908 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004034/ScoringFiles/PGS004034.txt.gz |
| PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004041/ScoringFiles/PGS004041.txt.gz | |
| PGS004054 (megaprs.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004054/ScoringFiles/PGS004054.txt.gz | |
| PGS004062 (megaprs.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 691,136 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004062/ScoringFiles/PGS004062.txt.gz |
| PGS004070 (megaprs.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004070/ScoringFiles/PGS004070.txt.gz | |
| PGS004084 (prscs.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004084/ScoringFiles/PGS004084.txt.gz | |
| PGS004092 (prscs.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 1,109,233 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004092/ScoringFiles/PGS004092.txt.gz |
| PGS004098 (prscs.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004098/ScoringFiles/PGS004098.txt.gz | |
| PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 13 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004108/ScoringFiles/PGS004108.txt.gz | |
| PGS004116 (pt_clump.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 58 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004116/ScoringFiles/PGS004116.txt.gz |
| PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 5,808 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004124/ScoringFiles/PGS004124.txt.gz | |
| PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 888,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004138/ScoringFiles/PGS004138.txt.gz | |
| PGS004146 (sbayesr.auto.GCST90012877.AD) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Alzheimer's disease | Alzheimer disease | 915,771 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004146/ScoringFiles/PGS004146.txt.gz |
| PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,116,976 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004154/ScoringFiles/PGS004154.txt.gz | |
| PGS004227 (ad_apoe_gw_pgs) |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 15 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004227/ScoringFiles/PGS004227.txt.gz |
| PGS004228 (ad_apoe_0.1_pgs) |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 8,863 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004228/ScoringFiles/PGS004228.txt.gz |
| PGS004229 (ad_noapoe_0.1_pgs) |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Alzheimer's disease | Alzheimer disease | 8,858 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004229/ScoringFiles/PGS004229.txt.gz |
| PGS004280 (GenoBoost_all-cause_dementia_0) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
All-cause dementia | dementia | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004280/ScoringFiles/PGS004280.txt.gz |
| PGS004281 (GenoBoost_all-cause_dementia_1) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
All-cause dementia | dementia | 110 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004281/ScoringFiles/PGS004281.txt.gz |
| PGS004282 (GenoBoost_all-cause_dementia_2) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
All-cause dementia | dementia | 40 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004282/ScoringFiles/PGS004282.txt.gz |
| PGS004283 (GenoBoost_all-cause_dementia_3) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
All-cause dementia | dementia | 90 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004283/ScoringFiles/PGS004283.txt.gz |
| PGS004284 (GenoBoost_all-cause_dementia_4) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
All-cause dementia | dementia | 50 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004284/ScoringFiles/PGS004284.txt.gz |
| PGS004285 (GenoBoost_alzheimer_s_disease_0) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Alzheimer's disease | Alzheimer disease | 20 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004285/ScoringFiles/PGS004285.txt.gz |
| PGS004286 (GenoBoost_alzheimer_s_disease_1) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Alzheimer's disease | Alzheimer disease | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004286/ScoringFiles/PGS004286.txt.gz |
| PGS004287 (GenoBoost_alzheimer_s_disease_2) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Alzheimer's disease | Alzheimer disease | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004287/ScoringFiles/PGS004287.txt.gz |
| PGS004288 (GenoBoost_alzheimer_s_disease_3) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Alzheimer's disease | Alzheimer disease | 200 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004288/ScoringFiles/PGS004288.txt.gz |
| PGS004289 (GenoBoost_alzheimer_s_disease_4) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Alzheimer's disease | Alzheimer disease | 40 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004289/ScoringFiles/PGS004289.txt.gz |
| PGS004318 (PRS29_dementia) |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Dementia | dementia | 29 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004318/ScoringFiles/PGS004318.txt.gz |
| PGS004322 (GRS30_IS) |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Ischemic stroke | Ischemic stroke, stroke disorder |
30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004322/ScoringFiles/PGS004322.txt.gz |
| PGS004449 (disease.F10.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F10 (Mental and behavioural disorders due to use of alcohol) | alcohol-induced mental disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004449/ScoringFiles/PGS004449.txt.gz |
| PGS004450 (disease.F17.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F17 (Mental and behavioural disorders due to use of tobacco) | mental disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004450/ScoringFiles/PGS004450.txt.gz |
| PGS004451 (disease.F41.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F41 (Other anxiety disorders) | anxiety disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004451/ScoringFiles/PGS004451.txt.gz |
| PGS004453 (disease.G56.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
G56 (Mononeuropathies of upper limb) | mononeuropathy | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004453/ScoringFiles/PGS004453.txt.gz |
| PGS004519 (meta.F10.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F10 (Mental and behavioural disorders due to use of alcohol) | alcohol-induced mental disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004519/ScoringFiles/PGS004519.txt.gz |
| PGS004520 (meta.F17.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F17 (Mental and behavioural disorders due to use of tobacco) | mental disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004520/ScoringFiles/PGS004520.txt.gz |
| PGS004521 (meta.F41.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
F41 (Other anxiety disorders) | anxiety disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004521/ScoringFiles/PGS004521.txt.gz |
| PGS004523 (meta.G56.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
G56 (Mononeuropathies of upper limb) | mononeuropathy | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004523/ScoringFiles/PGS004523.txt.gz |
| PGS004588 (PRS39_Eur) |
PGP000567 | Jung SH et al. JAMA Netw Open (2022) |
Alzheimer's disease | Alzheimer disease | 39 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004588/ScoringFiles/PGS004588.txt.gz | |
| PGS004589 (PRS80_trans) |
PGP000567 | Jung SH et al. JAMA Netw Open (2022) |
Alzheimer's disease | Alzheimer disease | 80 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004589/ScoringFiles/PGS004589.txt.gz | |
| PGS004590 (PRS363_rand_eff) |
PGP000569 | Lake J et al. Mol Psychiatry (2023) |
Alzheimer's disease | Alzheimer disease | 363 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004590/ScoringFiles/PGS004590.txt.gz |
| PGS004591 (PRS17_MDD) |
PGP000570 | Li D et al. BMC Med (2023) |
Major depressive disorder | major depressive disorder | 17 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004591/ScoringFiles/PGS004591.txt.gz |
| PGS004597 (PRS32_IS) |
PGP000576 | Peng H et al. Nutrients (2023) |
Ischemic stroke | Ischemic stroke, stroke disorder |
32 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004597/ScoringFiles/PGS004597.txt.gz |
| PGS004600 (PRS_AD83) |
PGP000578 | Tomassen J et al. BMC Neurol (2022) |
Alzheimer's disease | Alzheimer disease | 83 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004600/ScoringFiles/PGS004600.txt.gz |
| PGS004606 (AMD-IAMDGC-EUR) |
PGP000582 | Gorman BR et al. Nat Genet (2024) |
Age-related macular degeneration | age-related macular degeneration | 1,000,946 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004606/ScoringFiles/PGS004606.txt.gz |
| PGS004607 (AMD-MVP-AFR) |
PGP000582 | Gorman BR et al. Nat Genet (2024) |
Age-related macular degeneration | age-related macular degeneration | 1,067,520 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004607/ScoringFiles/PGS004607.txt.gz |
| PGS004699 (Non-HLA-GRS) |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Multiple sclerosis | multiple sclerosis | 307 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004699/ScoringFiles/PGS004699.txt.gz |
| PGS004700 (HLA-GRS) |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Multiple sclerosis | multiple sclerosis | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004700/ScoringFiles/PGS004700.txt.gz |
| PGS004759 (depression_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Depression | major depressive disorder | 1,538,576 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004759/ScoringFiles/PGS004759.txt.gz |
| PGS004760 (depression_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Depression | major depressive disorder | 2,141,267 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004760/ScoringFiles/PGS004760.txt.gz |
| PGS004797 (migraine_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004797/ScoringFiles/PGS004797.txt.gz |
| PGS004798 (migraine_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 3,984,158 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004798/ScoringFiles/PGS004798.txt.gz |
| PGS004799 (migraine_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 4,319,950 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004799/ScoringFiles/PGS004799.txt.gz |
| PGS004800 (migraine_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 2,968,987 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004800/ScoringFiles/PGS004800.txt.gz |
| PGS004835 (stroke_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Stroke | stroke disorder | 2,263,784 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004835/ScoringFiles/PGS004835.txt.gz |
| PGS004836 (stroke_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Stroke | stroke disorder | 5,644,266 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004836/ScoringFiles/PGS004836.txt.gz |
| PGS004863 (PRS74_AD) |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Alzheimer's disease | Alzheimer disease | 74 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004863/ScoringFiles/PGS004863.txt.gz |
| PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Epilepsy | epilepsy | 605,432 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004881/ScoringFiles/PGS004881.txt.gz | |
| PGS004885 (INTERVENE_MegaPRS_MDD) |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Major depressive disorder | major depressive disorder | 801,544 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004885/ScoringFiles/PGS004885.txt.gz | |
| PGS004898 (PRS_AD) |
PGP000624 | Vasiljevic E et al. Alzheimers Dement (2023) |
Alzheimer's disease | Alzheimer disease | 44 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004898/ScoringFiles/PGS004898.txt.gz |
| PGS004918 (PRS8_Synapse) |
PGP000649 | Lawingco T et al. Neurobiol Aging (2020) |
Late-onset Alzheimers disease (based on SNPs in genes involved in synaptic function) | late-onset Alzheimer's disease | 8 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004918/ScoringFiles/PGS004918.txt.gz | |
| PGS004924 (PRS90_PD) |
PGP000657 | Cao Z et al. Parkinsonism Relat Disord (2023) |
Parkinson's disease | Parkinson disease | 90 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004924/ScoringFiles/PGS004924.txt.gz |
| PGS004943 (ICH_MetaPRS) |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Intracerebral hemorrhage | intracerebral hemorrhage | 2,124,631 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004943/ScoringFiles/PGS004943.txt.gz |
| PGS004952 (PRS52_AMD) |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Age-related macular degeneration | age-related macular degeneration | 52 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004952/ScoringFiles/PGS004952.txt.gz |
| PGS005156 (Stroke (PRS-CSx; EAS+EUR)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Stroke | stroke disorder | 908,465 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005156/ScoringFiles/PGS005156.txt.gz |
| PGS005170 (iPRS_DEM) |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
All-cause dementia | dementia | 1,320,229 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005170/ScoringFiles/PGS005170.txt.gz | |
| PGS005230 (PRS71_STROKE) |
PGP000736 | Ma Y et al. Stroke (2023) |
Stroke | stroke disorder | 71 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005230/ScoringFiles/PGS005230.txt.gz |
| PGS005389 (ADRD_consensus_main_score) |
PGP000776 | EADB et al. Nat Genet (2026) |
Alzheimer's disease | Alzheimer disease | 115 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005389/ScoringFiles/PGS005389.txt.gz | |
| PGS005390 (ADRD_consensus_no_proxy_score) |
PGP000776 | EADB et al. Nat Genet (2026) |
Alzheimer's disease | Alzheimer disease | 91 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005390/ScoringFiles/PGS005390.txt.gz | |
| PGS005391 (ADRD_consensus_no_biobank_score) |
PGP000776 | EADB et al. Nat Genet (2026) |
Alzheimer's disease | Alzheimer disease | 65 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005391/ScoringFiles/PGS005391.txt.gz | |
| PGS005393 (PGS_SEXUAL_ASSAULT_PTSD) |
PGP000778 | Bugiga AVG et al. Braz J Psychiatry (2024) |
Post-traumatic stress disorder | post-traumatic stress disorder | 53,705 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005393/ScoringFiles/PGS005393.txt.gz |
| PGS012548 (PRS94_AD) |
PGP000791 | Li Y et al. J Gerontol A Biol Sci Med Sci (2024) |
Alzheimer's disease | Alzheimer disease | 94 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012548/ScoringFiles/PGS012548.txt.gz |
| PGS012551 (PRS_stroke) |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Stroke | stroke disorder | 1,997,066 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012551/ScoringFiles/PGS012551.txt.gz |
| PGS012579 (PRS11_stroke) |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Stroke | stroke disorder | 11 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012579/ScoringFiles/PGS012579.txt.gz |
| PGS012584 (PRS44_PD) |
PGP000818 | Geng T et al. NPJ Parkinsons Dis (2024) |
Parkinson's disease | Parkinson disease | 44 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012584/ScoringFiles/PGS012584.txt.gz |
| PGS012589 (PRS29_dementia) |
PGP000823 | Zhang S et al. Int J Public Health (2024) |
Dementia | dementia | 29 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012589/ScoringFiles/PGS012589.txt.gz |
| PGS018414 (pgshl) |
PGP000832 | Miao DNR et al. Hum Genomics (2024) |
Hearing loss (HL) | hearing loss disorder | 2,370,365 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018414/ScoringFiles/PGS018414.txt.gz |
| PGS018460 (TPMI_145.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Tongue cancer | tongue cancer | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018460/ScoringFiles/PGS018460.txt.gz | |
| PGS018461 (TPMI_145.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Tongue cancer | tongue cancer | 34,059 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018461/ScoringFiles/PGS018461.txt.gz | |
| PGS018462 (TPMI_145.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Tongue cancer | tongue cancer | 570,182 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018462/ScoringFiles/PGS018462.txt.gz | |
| PGS018463 (TPMI_145.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Tongue cancer | tongue cancer | 983,776 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018463/ScoringFiles/PGS018463.txt.gz | |
| PGS018464 (TPMI_145.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Tongue cancer | tongue cancer | 1,003,968 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018464/ScoringFiles/PGS018464.txt.gz | |
| PGS018575 (TPMI_191_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Manlignant and unknown neoplasms of brain and nervous system | central nervous system cancer | 43 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018575/ScoringFiles/PGS018575.txt.gz | |
| PGS018576 (TPMI_191_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Manlignant and unknown neoplasms of brain and nervous system | central nervous system cancer | 90,905 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018576/ScoringFiles/PGS018576.txt.gz | |
| PGS018577 (TPMI_191_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Manlignant and unknown neoplasms of brain and nervous system | central nervous system cancer | 487,886 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018577/ScoringFiles/PGS018577.txt.gz | |
| PGS018578 (TPMI_191_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Manlignant and unknown neoplasms of brain and nervous system | central nervous system cancer | 983,826 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018578/ScoringFiles/PGS018578.txt.gz | |
| PGS018579 (TPMI_191_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Manlignant and unknown neoplasms of brain and nervous system | central nervous system cancer | 996,644 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018579/ScoringFiles/PGS018579.txt.gz | |
| PGS018630 (TPMI_225_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Benign neoplasm of brain and other parts of nervous system | benign neoplasm of peripheral nervous system | 105,501 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018630/ScoringFiles/PGS018630.txt.gz | |
| PGS018631 (TPMI_225_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Benign neoplasm of brain and other parts of nervous system | benign neoplasm of peripheral nervous system | 939,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018631/ScoringFiles/PGS018631.txt.gz | |
| PGS018632 (TPMI_225_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Benign neoplasm of brain and other parts of nervous system | benign neoplasm of peripheral nervous system | 18,584 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018632/ScoringFiles/PGS018632.txt.gz | |
| PGS018633 (TPMI_225_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Benign neoplasm of brain and other parts of nervous system | benign neoplasm of peripheral nervous system | 983,826 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018633/ScoringFiles/PGS018633.txt.gz | |
| PGS018634 (TPMI_225_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Benign neoplasm of brain and other parts of nervous system | benign neoplasm of peripheral nervous system | 994,892 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018634/ScoringFiles/PGS018634.txt.gz | |
| PGS018734 (TPMI_250.6_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 669 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018734/ScoringFiles/PGS018734.txt.gz | |
| PGS018735 (TPMI_250.6_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 939,815 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018735/ScoringFiles/PGS018735.txt.gz | |
| PGS018736 (TPMI_250.6_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 54,980 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018736/ScoringFiles/PGS018736.txt.gz | |
| PGS018737 (TPMI_250.6_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 983,767 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018737/ScoringFiles/PGS018737.txt.gz | |
| PGS018738 (TPMI_250.6_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 1,071,477 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018738/ScoringFiles/PGS018738.txt.gz | |
| PGS018739 (TPMI_250.6_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Polyneuropathy in diabetes | diabetic neuropathy | 996,392 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018739/ScoringFiles/PGS018739.txt.gz | |
| PGS018740 (TPMI_250.7_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 96 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018740/ScoringFiles/PGS018740.txt.gz | |
| PGS018741 (TPMI_250.7_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 939,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018741/ScoringFiles/PGS018741.txt.gz | |
| PGS018742 (TPMI_250.7_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 80,280 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018742/ScoringFiles/PGS018742.txt.gz | |
| PGS018743 (TPMI_250.7_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 983,771 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018743/ScoringFiles/PGS018743.txt.gz | |
| PGS018744 (TPMI_250.7_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 1,071,355 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018744/ScoringFiles/PGS018744.txt.gz | |
| PGS018745 (TPMI_250.7_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 1,014,773 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018745/ScoringFiles/PGS018745.txt.gz | |
| PGS018891 (TPMI_290_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Delirium dementia and amnestic and other cognitive disorders | cognitive disorder | 21,198 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018891/ScoringFiles/PGS018891.txt.gz | |
| PGS018892 (TPMI_290_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Delirium dementia and amnestic and other cognitive disorders | cognitive disorder | 939,891 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018892/ScoringFiles/PGS018892.txt.gz | |
| PGS018893 (TPMI_290_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Delirium dementia and amnestic and other cognitive disorders | cognitive disorder | 16,411 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018893/ScoringFiles/PGS018893.txt.gz | |
| PGS018894 (TPMI_290_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Delirium dementia and amnestic and other cognitive disorders | cognitive disorder | 983,825 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018894/ScoringFiles/PGS018894.txt.gz | |
| PGS018895 (TPMI_290_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Delirium dementia and amnestic and other cognitive disorders | cognitive disorder | 170,479 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018895/ScoringFiles/PGS018895.txt.gz | |
| PGS018896 (TPMI_290.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Dementia | dementia | 56,203 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018896/ScoringFiles/PGS018896.txt.gz | |
| PGS018897 (TPMI_290.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Dementia | dementia | 354,947 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018897/ScoringFiles/PGS018897.txt.gz | |
| PGS018898 (TPMI_290.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Dementia | dementia | 14,376 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018898/ScoringFiles/PGS018898.txt.gz | |
| PGS018899 (TPMI_290.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Dementia | dementia | 983,826 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018899/ScoringFiles/PGS018899.txt.gz | |
| PGS018900 (TPMI_290.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Dementia | dementia | 84,318 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018900/ScoringFiles/PGS018900.txt.gz | |
| PGS018901 (TPMI_290.3_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other persistent mental disorders due to conditions classified elsewhere | mental disorder | 34,357 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018901/ScoringFiles/PGS018901.txt.gz | |
| PGS018902 (TPMI_290.3_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other persistent mental disorders due to conditions classified elsewhere | mental disorder | 939,840 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018902/ScoringFiles/PGS018902.txt.gz | |
| PGS018903 (TPMI_290.3_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other persistent mental disorders due to conditions classified elsewhere | mental disorder | 69,993 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018903/ScoringFiles/PGS018903.txt.gz | |
| PGS018904 (TPMI_290.3_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other persistent mental disorders due to conditions classified elsewhere | mental disorder | 983,791 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018904/ScoringFiles/PGS018904.txt.gz | |
| PGS018905 (TPMI_290.3_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other persistent mental disorders due to conditions classified elsewhere | mental disorder | 322,143 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018905/ScoringFiles/PGS018905.txt.gz | |
| PGS018906 (TPMI_290.11_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Alzheimers disease | Alzheimer disease | 87 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018906/ScoringFiles/PGS018906.txt.gz | |
| PGS018907 (TPMI_290.11_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Alzheimers disease | Alzheimer disease | 383,714 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018907/ScoringFiles/PGS018907.txt.gz | |
| PGS018908 (TPMI_290.11_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Alzheimers disease | Alzheimer disease | 456,140 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018908/ScoringFiles/PGS018908.txt.gz | |
| PGS018909 (TPMI_290.11_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Alzheimers disease | Alzheimer disease | 983,819 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018909/ScoringFiles/PGS018909.txt.gz | |
| PGS018910 (TPMI_290.11_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Alzheimers disease | Alzheimer disease | 102,677 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018910/ScoringFiles/PGS018910.txt.gz | |
| PGS018911 (TPMI_290.13_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Senile dementia | dementia | 6,126 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018911/ScoringFiles/PGS018911.txt.gz | |
| PGS018912 (TPMI_290.13_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Senile dementia | dementia | 939,839 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018912/ScoringFiles/PGS018912.txt.gz | |
| PGS018913 (TPMI_290.13_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Senile dementia | dementia | 652,894 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018913/ScoringFiles/PGS018913.txt.gz | |
| PGS018914 (TPMI_290.13_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Senile dementia | dementia | 983,791 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018914/ScoringFiles/PGS018914.txt.gz | |
| PGS018915 (TPMI_290.13_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Senile dementia | dementia | 942,185 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018915/ScoringFiles/PGS018915.txt.gz | |
| PGS018916 (TPMI_291_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other specified nonpsychotic and or transient mental disorders | mental disorder | 317 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018916/ScoringFiles/PGS018916.txt.gz | |
| PGS018917 (TPMI_291_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other specified nonpsychotic and or transient mental disorders | mental disorder | 373,255 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018917/ScoringFiles/PGS018917.txt.gz | |
| PGS018918 (TPMI_291_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other specified nonpsychotic and or transient mental disorders | mental disorder | 616,739 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018918/ScoringFiles/PGS018918.txt.gz | |
| PGS018919 (TPMI_291_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other specified nonpsychotic and or transient mental disorders | mental disorder | 983,789 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018919/ScoringFiles/PGS018919.txt.gz | |
| PGS018920 (TPMI_291_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other specified nonpsychotic and or transient mental disorders | mental disorder | 333,423 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018920/ScoringFiles/PGS018920.txt.gz | |
| PGS018921 (TPMI_291.4_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Specific nonpsychotic mental disorders due to brain damage | mental disorder | 127 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018921/ScoringFiles/PGS018921.txt.gz | |
| PGS018922 (TPMI_291.4_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Specific nonpsychotic mental disorders due to brain damage | mental disorder | 939,895 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018922/ScoringFiles/PGS018922.txt.gz | |
| PGS018923 (TPMI_291.4_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Specific nonpsychotic mental disorders due to brain damage | mental disorder | 19,578 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018923/ScoringFiles/PGS018923.txt.gz | |
| PGS018924 (TPMI_291.4_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Specific nonpsychotic mental disorders due to brain damage | mental disorder | 983,829 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018924/ScoringFiles/PGS018924.txt.gz | |
| PGS018925 (TPMI_291.4_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Specific nonpsychotic mental disorders due to brain damage | mental disorder | 131,160 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018925/ScoringFiles/PGS018925.txt.gz | |
| PGS018926 (TPMI_292_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Neurological disorders | nervous system disorder | 4 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018926/ScoringFiles/PGS018926.txt.gz | |
| PGS018927 (TPMI_292_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Neurological disorders | nervous system disorder | 330,541 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018927/ScoringFiles/PGS018927.txt.gz | |
| PGS018928 (TPMI_292_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Neurological disorders | nervous system disorder | 566,907 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018928/ScoringFiles/PGS018928.txt.gz | |
| PGS018929 (TPMI_292_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Neurological disorders | nervous system disorder | 983,821 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018929/ScoringFiles/PGS018929.txt.gz | |
| PGS018930 (TPMI_292_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Neurological disorders | nervous system disorder | 980,061 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018930/ScoringFiles/PGS018930.txt.gz | |
| PGS018936 (TPMI_296.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Depression | depressive disorder | 230,322 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018936/ScoringFiles/PGS018936.txt.gz | |
| PGS018937 (TPMI_296.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Depression | depressive disorder | 939,862 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018937/ScoringFiles/PGS018937.txt.gz | |
| PGS018938 (TPMI_296.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Depression | depressive disorder | 18,793 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018938/ScoringFiles/PGS018938.txt.gz | |
| PGS018939 (TPMI_296.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Depression | depressive disorder | 983,806 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018939/ScoringFiles/PGS018939.txt.gz | |
| PGS018940 (TPMI_296.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Depression | depressive disorder | 961,120 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018940/ScoringFiles/PGS018940.txt.gz | |
| PGS018941 (TPMI_300.11_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Generalized anxiety disorder | generalized anxiety disorder | 729,735 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018941/ScoringFiles/PGS018941.txt.gz | |
| PGS018942 (TPMI_300.11_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Generalized anxiety disorder | generalized anxiety disorder | 939,863 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018942/ScoringFiles/PGS018942.txt.gz | |
| PGS018943 (TPMI_300.11_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Generalized anxiety disorder | generalized anxiety disorder | 21,630 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018943/ScoringFiles/PGS018943.txt.gz | |
| PGS018944 (TPMI_300.11_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Generalized anxiety disorder | generalized anxiety disorder | 983,808 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018944/ScoringFiles/PGS018944.txt.gz | |
| PGS018945 (TPMI_300.11_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Generalized anxiety disorder | generalized anxiety disorder | 975,855 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018945/ScoringFiles/PGS018945.txt.gz | |
| PGS018946 (TPMI_306_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other mental disorder | mental disorder | 393,402 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018946/ScoringFiles/PGS018946.txt.gz | |
| PGS018947 (TPMI_306_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other mental disorder | mental disorder | 402,973 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018947/ScoringFiles/PGS018947.txt.gz | |
| PGS018948 (TPMI_306_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other mental disorder | mental disorder | 22,265 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018948/ScoringFiles/PGS018948.txt.gz | |
| PGS018949 (TPMI_306_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other mental disorder | mental disorder | 983,807 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018949/ScoringFiles/PGS018949.txt.gz | |
| PGS018950 (TPMI_306_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other mental disorder | mental disorder | 922,093 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018950/ScoringFiles/PGS018950.txt.gz | |
| PGS018951 (TPMI_315_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Develomental delays and disorders | specific developmental disorder | 21 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018951/ScoringFiles/PGS018951.txt.gz | |
| PGS018952 (TPMI_315_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Develomental delays and disorders | specific developmental disorder | 178,694 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018952/ScoringFiles/PGS018952.txt.gz | |
| PGS018953 (TPMI_315_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Develomental delays and disorders | specific developmental disorder | 28,656 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018953/ScoringFiles/PGS018953.txt.gz | |
| PGS018954 (TPMI_315_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Develomental delays and disorders | specific developmental disorder | 983,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018954/ScoringFiles/PGS018954.txt.gz | |
| PGS018955 (TPMI_315_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Develomental delays and disorders | specific developmental disorder | 1,013,967 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018955/ScoringFiles/PGS018955.txt.gz | |
| PGS018971 (TPMI_327.7_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Sleep related movement disorders | movement disorder | 147,703 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018971/ScoringFiles/PGS018971.txt.gz | |
| PGS018972 (TPMI_327.7_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Sleep related movement disorders | movement disorder | 939,812 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018972/ScoringFiles/PGS018972.txt.gz | |
| PGS018973 (TPMI_327.7_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Sleep related movement disorders | movement disorder | 10,770 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018973/ScoringFiles/PGS018973.txt.gz | |
| PGS018974 (TPMI_327.7_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Sleep related movement disorders | movement disorder | 983,773 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018974/ScoringFiles/PGS018974.txt.gz | |
| PGS018975 (TPMI_327.7_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Sleep related movement disorders | movement disorder | 1,002,797 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018975/ScoringFiles/PGS018975.txt.gz | |
| PGS018976 (TPMI_327.41_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Organic or persistent insomnia | insomnia | 246,776 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018976/ScoringFiles/PGS018976.txt.gz | |
| PGS018977 (TPMI_327.41_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Organic or persistent insomnia | insomnia | 939,879 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018977/ScoringFiles/PGS018977.txt.gz | |
| PGS018978 (TPMI_327.41_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Organic or persistent insomnia | insomnia | 23,384 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018978/ScoringFiles/PGS018978.txt.gz | |
| PGS018979 (TPMI_327.41_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Organic or persistent insomnia | insomnia | 983,818 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018979/ScoringFiles/PGS018979.txt.gz | |
| PGS018980 (TPMI_327.41_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Organic or persistent insomnia | insomnia | 967,358 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018980/ScoringFiles/PGS018980.txt.gz | |
| PGS018986 (TPMI_340_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 154,713 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018986/ScoringFiles/PGS018986.txt.gz | |
| PGS018987 (TPMI_340_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 356,947 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018987/ScoringFiles/PGS018987.txt.gz | |
| PGS018988 (TPMI_340_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 19,422 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018988/ScoringFiles/PGS018988.txt.gz | |
| PGS018989 (TPMI_340_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 983,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018989/ScoringFiles/PGS018989.txt.gz | |
| PGS018990 (TPMI_340_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 959,731 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018990/ScoringFiles/PGS018990.txt.gz | |
| PGS018991 (TPMI_345.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Epilepsy | epilepsy | 65 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018991/ScoringFiles/PGS018991.txt.gz | |
| PGS018992 (TPMI_345.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Epilepsy | epilepsy | 300,225 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018992/ScoringFiles/PGS018992.txt.gz | |
| PGS018993 (TPMI_345.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Epilepsy | epilepsy | 16,624 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018993/ScoringFiles/PGS018993.txt.gz | |
| PGS018994 (TPMI_345.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Epilepsy | epilepsy | 983,823 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018994/ScoringFiles/PGS018994.txt.gz | |
| PGS018995 (TPMI_345.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Epilepsy | epilepsy | 997,881 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018995/ScoringFiles/PGS018995.txt.gz | |
| PGS018996 (TPMI_352.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Facial nerve disorders CN7 | facial nerve disorder | 241,782 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018996/ScoringFiles/PGS018996.txt.gz | |
| PGS018997 (TPMI_352.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Facial nerve disorders CN7 | facial nerve disorder | 939,882 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018997/ScoringFiles/PGS018997.txt.gz | |
| PGS018998 (TPMI_352.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Facial nerve disorders CN7 | facial nerve disorder | 18,580 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018998/ScoringFiles/PGS018998.txt.gz | |
| PGS018999 (TPMI_352.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Facial nerve disorders CN7 | facial nerve disorder | 983,821 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018999/ScoringFiles/PGS018999.txt.gz | |
| PGS019000 (TPMI_352.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Facial nerve disorders CN7 | facial nerve disorder | 1,002,253 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019000/ScoringFiles/PGS019000.txt.gz | |
| PGS019001 (TPMI_357_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Inflammatory and toxic neuropathy | neuropathy | 155,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019001/ScoringFiles/PGS019001.txt.gz | |
| PGS019002 (TPMI_357_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Inflammatory and toxic neuropathy | neuropathy | 939,882 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019002/ScoringFiles/PGS019002.txt.gz | |
| PGS019003 (TPMI_357_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Inflammatory and toxic neuropathy | neuropathy | 26,916 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019003/ScoringFiles/PGS019003.txt.gz | |
| PGS019004 (TPMI_357_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Inflammatory and toxic neuropathy | neuropathy | 983,823 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019004/ScoringFiles/PGS019004.txt.gz | |
| PGS019005 (TPMI_357_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Inflammatory and toxic neuropathy | neuropathy | 974,368 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019005/ScoringFiles/PGS019005.txt.gz | |
| PGS019006 (TPMI_361_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Retinal detachments and defects | retinal detachment | 37,750 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019006/ScoringFiles/PGS019006.txt.gz | |
| PGS019007 (TPMI_361_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Retinal detachments and defects | retinal detachment | 336,398 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019007/ScoringFiles/PGS019007.txt.gz | |
| PGS019008 (TPMI_361_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Retinal detachments and defects | retinal detachment | 20,644 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019008/ScoringFiles/PGS019008.txt.gz | |
| PGS019009 (TPMI_361_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Retinal detachments and defects | retinal detachment | 983,814 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019009/ScoringFiles/PGS019009.txt.gz | |
| PGS019010 (TPMI_361_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Retinal detachments and defects | retinal detachment | 994,334 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019010/ScoringFiles/PGS019010.txt.gz | |
| PGS019011 (TPMI_362_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other retinal disorders | retinal disorder | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019011/ScoringFiles/PGS019011.txt.gz | |
| PGS019012 (TPMI_362_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other retinal disorders | retinal disorder | 939,882 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019012/ScoringFiles/PGS019012.txt.gz | |
| PGS019013 (TPMI_362_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other retinal disorders | retinal disorder | 27,392 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019013/ScoringFiles/PGS019013.txt.gz | |
| PGS019014 (TPMI_362_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other retinal disorders | retinal disorder | 983,815 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019014/ScoringFiles/PGS019014.txt.gz | |
| PGS019015 (TPMI_362_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other retinal disorders | retinal disorder | 936,613 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019015/ScoringFiles/PGS019015.txt.gz | |
| PGS019016 (TPMI_362.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Degeneration of macula and posterior pole of retina | degeneration of macula and posterior pole | 4 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019016/ScoringFiles/PGS019016.txt.gz | |
| PGS019017 (TPMI_362.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Degeneration of macula and posterior pole of retina | degeneration of macula and posterior pole | 314,377 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019017/ScoringFiles/PGS019017.txt.gz | |
| PGS019018 (TPMI_362.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Degeneration of macula and posterior pole of retina | degeneration of macula and posterior pole | 34,660 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019018/ScoringFiles/PGS019018.txt.gz | |
| PGS019019 (TPMI_362.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Degeneration of macula and posterior pole of retina | degeneration of macula and posterior pole | 983,766 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019019/ScoringFiles/PGS019019.txt.gz | |
| PGS019020 (TPMI_362.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Degeneration of macula and posterior pole of retina | degeneration of macula and posterior pole | 1,008,320 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019020/ScoringFiles/PGS019020.txt.gz | |
| PGS019021 (TPMI_362.6_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Peripheral retinal degenerations | retinal degeneration | 107 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019021/ScoringFiles/PGS019021.txt.gz | |
| PGS019022 (TPMI_362.6_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Peripheral retinal degenerations | retinal degeneration | 939,860 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019022/ScoringFiles/PGS019022.txt.gz | |
| PGS019023 (TPMI_362.6_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Peripheral retinal degenerations | retinal degeneration | 24,607 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019023/ScoringFiles/PGS019023.txt.gz | |
| PGS019024 (TPMI_362.6_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Peripheral retinal degenerations | retinal degeneration | 983,802 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019024/ScoringFiles/PGS019024.txt.gz | |
| PGS019025 (TPMI_362.6_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Peripheral retinal degenerations | retinal degeneration | 1,011,772 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019025/ScoringFiles/PGS019025.txt.gz | |
| PGS019026 (TPMI_362.26_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular puckering of retina | degeneration of macula and posterior pole | 5,750 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019026/ScoringFiles/PGS019026.txt.gz | |
| PGS019027 (TPMI_362.26_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular puckering of retina | degeneration of macula and posterior pole | 337,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019027/ScoringFiles/PGS019027.txt.gz | |
| PGS019028 (TPMI_362.26_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular puckering of retina | degeneration of macula and posterior pole | 15,945 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019028/ScoringFiles/PGS019028.txt.gz | |
| PGS019029 (TPMI_362.26_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular puckering of retina | degeneration of macula and posterior pole | 983,768 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019029/ScoringFiles/PGS019029.txt.gz | |
| PGS019030 (TPMI_362.26_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular puckering of retina | degeneration of macula and posterior pole | 1,009,853 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019030/ScoringFiles/PGS019030.txt.gz | |
| PGS019031 (TPMI_362.29_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular degeneration senile of retina NOS | macular degeneration | 222 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019031/ScoringFiles/PGS019031.txt.gz | |
| PGS019032 (TPMI_362.29_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular degeneration senile of retina NOS | macular degeneration | 939,874 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019032/ScoringFiles/PGS019032.txt.gz | |
| PGS019033 (TPMI_362.29_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular degeneration senile of retina NOS | macular degeneration | 21,742 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019033/ScoringFiles/PGS019033.txt.gz | |
| PGS019034 (TPMI_362.29_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular degeneration senile of retina NOS | macular degeneration | 983,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019034/ScoringFiles/PGS019034.txt.gz | |
| PGS019035 (TPMI_362.29_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Macular degeneration senile of retina NOS | macular degeneration | 1,000,676 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019035/ScoringFiles/PGS019035.txt.gz | |
| PGS019081 (TPMI_386_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Vertiginous syndromes and other disorders of vestibular system | vestibular disorder | 125,242 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019081/ScoringFiles/PGS019081.txt.gz | |
| PGS019082 (TPMI_386_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Vertiginous syndromes and other disorders of vestibular system | vestibular disorder | 939,898 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019082/ScoringFiles/PGS019082.txt.gz | |
| PGS019083 (TPMI_386_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Vertiginous syndromes and other disorders of vestibular system | vestibular disorder | 22,265 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019083/ScoringFiles/PGS019083.txt.gz | |
| PGS019084 (TPMI_386_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Vertiginous syndromes and other disorders of vestibular system | vestibular disorder | 983,829 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019084/ScoringFiles/PGS019084.txt.gz | |
| PGS019085 (TPMI_386_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Vertiginous syndromes and other disorders of vestibular system | vestibular disorder | 914,097 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019085/ScoringFiles/PGS019085.txt.gz | |
| PGS019086 (TPMI_386.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Menieres disease | Meniere disease | 802,789 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019086/ScoringFiles/PGS019086.txt.gz | |
| PGS019087 (TPMI_386.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Menieres disease | Meniere disease | 939,888 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019087/ScoringFiles/PGS019087.txt.gz | |
| PGS019088 (TPMI_386.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Menieres disease | Meniere disease | 23,220 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019088/ScoringFiles/PGS019088.txt.gz | |
| PGS019089 (TPMI_386.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Menieres disease | Meniere disease | 983,823 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019089/ScoringFiles/PGS019089.txt.gz | |
| PGS019090 (TPMI_386.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Menieres disease | Meniere disease | 987,552 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019090/ScoringFiles/PGS019090.txt.gz | |
| PGS019111 (TPMI_389_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hearing loss | hearing loss disorder | 409,744 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019111/ScoringFiles/PGS019111.txt.gz | |
| PGS019112 (TPMI_389_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hearing loss | hearing loss disorder | 939,885 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019112/ScoringFiles/PGS019112.txt.gz | |
| PGS019113 (TPMI_389_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hearing loss | hearing loss disorder | 531,934 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019113/ScoringFiles/PGS019113.txt.gz | |
| PGS019114 (TPMI_389_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hearing loss | hearing loss disorder | 983,822 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019114/ScoringFiles/PGS019114.txt.gz | |
| PGS019115 (TPMI_389_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Hearing loss | hearing loss disorder | 928,045 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019115/ScoringFiles/PGS019115.txt.gz | |
| PGS019116 (TPMI_389.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Sensorineural hearing loss | sensorineural hearing loss disorder | 697,131 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019116/ScoringFiles/PGS019116.txt.gz | |
| PGS019117 (TPMI_389.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Sensorineural hearing loss | sensorineural hearing loss disorder | 939,879 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019117/ScoringFiles/PGS019117.txt.gz | |
| PGS019118 (TPMI_389.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Sensorineural hearing loss | sensorineural hearing loss disorder | 23,594 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019118/ScoringFiles/PGS019118.txt.gz | |
| PGS019119 (TPMI_389.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Sensorineural hearing loss | sensorineural hearing loss disorder | 983,819 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019119/ScoringFiles/PGS019119.txt.gz | |
| PGS019120 (TPMI_389.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Sensorineural hearing loss | sensorineural hearing loss disorder | 976,192 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019120/ScoringFiles/PGS019120.txt.gz | |
| PGS019215 (TPMI_430_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 709,249 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019215/ScoringFiles/PGS019215.txt.gz | |
| PGS019216 (TPMI_430_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 939,872 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019216/ScoringFiles/PGS019216.txt.gz | |
| PGS019217 (TPMI_430_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 23,091 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019217/ScoringFiles/PGS019217.txt.gz | |
| PGS019218 (TPMI_430_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 983,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019218/ScoringFiles/PGS019218.txt.gz | |
| PGS019219 (TPMI_430_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 1,006,461 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019219/ScoringFiles/PGS019219.txt.gz | |
| PGS019220 (TPMI_430.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 239,850 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019220/ScoringFiles/PGS019220.txt.gz | |
| PGS019221 (TPMI_430.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 939,827 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019221/ScoringFiles/PGS019221.txt.gz | |
| PGS019222 (TPMI_430.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 26,024 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019222/ScoringFiles/PGS019222.txt.gz | |
| PGS019223 (TPMI_430.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 983,782 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019223/ScoringFiles/PGS019223.txt.gz | |
| PGS019224 (TPMI_430.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 1,012,521 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019224/ScoringFiles/PGS019224.txt.gz | |
| PGS019225 (TPMI_433_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 157,854 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019225/ScoringFiles/PGS019225.txt.gz | |
| PGS019226 (TPMI_433_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 939,895 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019226/ScoringFiles/PGS019226.txt.gz | |
| PGS019227 (TPMI_433_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 35,297 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019227/ScoringFiles/PGS019227.txt.gz | |
| PGS019228 (TPMI_433_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 983,828 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019228/ScoringFiles/PGS019228.txt.gz | |
| PGS019229 (TPMI_433_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 950,004 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019229/ScoringFiles/PGS019229.txt.gz | |
| PGS019230 (TPMI_433.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 562,676 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019230/ScoringFiles/PGS019230.txt.gz | |
| PGS019231 (TPMI_433.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 939,882 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019231/ScoringFiles/PGS019231.txt.gz | |
| PGS019232 (TPMI_433.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 33,950 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019232/ScoringFiles/PGS019232.txt.gz | |
| PGS019233 (TPMI_433.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 983,818 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019233/ScoringFiles/PGS019233.txt.gz | |
| PGS019234 (TPMI_433.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 969,384 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019234/ScoringFiles/PGS019234.txt.gz | |
| PGS019240 (TPMI_433.6_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 356,084 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019240/ScoringFiles/PGS019240.txt.gz | |
| PGS019241 (TPMI_433.6_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 939,874 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019241/ScoringFiles/PGS019241.txt.gz | |
| PGS019242 (TPMI_433.6_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 436,050 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019242/ScoringFiles/PGS019242.txt.gz | |
| PGS019243 (TPMI_433.6_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 983,814 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019243/ScoringFiles/PGS019243.txt.gz | |
| PGS019244 (TPMI_433.6_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 999,333 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019244/ScoringFiles/PGS019244.txt.gz | |
| PGS019245 (TPMI_433.8_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 703,260 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019245/ScoringFiles/PGS019245.txt.gz | |
| PGS019246 (TPMI_433.8_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 332,716 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019246/ScoringFiles/PGS019246.txt.gz | |
| PGS019247 (TPMI_433.8_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 11,065 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019247/ScoringFiles/PGS019247.txt.gz | |
| PGS019248 (TPMI_433.8_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 983,823 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019248/ScoringFiles/PGS019248.txt.gz | |
| PGS019249 (TPMI_433.8_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 1,001,105 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019249/ScoringFiles/PGS019249.txt.gz | |
| PGS019250 (TPMI_433.21_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 48,064 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019250/ScoringFiles/PGS019250.txt.gz | |
| PGS019251 (TPMI_433.21_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 939,870 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019251/ScoringFiles/PGS019251.txt.gz | |
| PGS019252 (TPMI_433.21_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 23,452 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019252/ScoringFiles/PGS019252.txt.gz | |
| PGS019253 (TPMI_433.21_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 983,812 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019253/ScoringFiles/PGS019253.txt.gz | |
| PGS019254 (TPMI_433.21_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 976,798 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019254/ScoringFiles/PGS019254.txt.gz | |
| PGS019928 (Insomnia UKB) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,069,748 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019928/ScoringFiles/PGS019928.txt.gz |
| PGS019929 (Insomnia MVP EUR) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,085,967 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019929/ScoringFiles/PGS019929.txt.gz |
| PGS019930 (Insomnia MVP AFR) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,211,512 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019930/ScoringFiles/PGS019930.txt.gz |
| PGS019931 (Insomnia MVP AMR) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,166,626 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019931/ScoringFiles/PGS019931.txt.gz |
| PGS019932 (Insomnia MVP EAS) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,021,391 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019932/ScoringFiles/PGS019932.txt.gz |
| PGS019933 (Insomnia UKB+MVP EUR (meta-analyzed)) |
PGP000836 | Wyss AB et al. Sleep (2026) |
Insomnia | insomnia | 1,116,570 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019933/ScoringFiles/PGS019933.txt.gz |
|
PGS Performance Metric ID (PPM) |
Evaluated Score |
PGS Sample Set ID (PSS) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
Classification Metrics | Other Metrics | Covariates Included in the Model |
PGS Performance: Other Relevant Information |
|---|---|---|---|---|---|---|---|---|---|
| PPM000051 | PGS000025 (GRS) |
PSS000034| European Ancestry| 4,353 individuals |
PGP000015 | Chouraki V et al. J Alzheimers Dis (2016) |
Reported Trait: Incident Alzheimer's disease in APOE Ɛ4 carriers | HR: 1.24 [1.15, 1.34] | — | ΔC-index between models with and without GRS: 0.0112 [0.0015, 0.0208] | age at baseline, sex, education level | HRs are derived from a meta-analysis of studies (adjusted for study center, and participant relatedness) |
| PPM000052 | PGS000025 (GRS) |
PSS000035| European Ancestry| 15,334 individuals |
PGP000015 | Chouraki V et al. J Alzheimers Dis (2016) |
Reported Trait: Incident Alzheimer's disease in APOE Ɛ4 non-carriers | HR: 1.13 [1.08, 1.18] | — | ΔC-index between models with and without GRS: 0.0018 [-0.0003, 0.0039] | age at baseline, sex, education level | HRs are derived from a meta-analysis of studies (adjusted for study center, and participant relatedness) |
| PPM000090 | PGS000038 (PRS90) |
PSS000057| European Ancestry| 306,473 individuals |
PGP000026 | Rutten-Jacobs LC et al. BMJ (2018) |
Reported Trait: Incident stroke | — | — | HR (High [top 33%] vs. Low [bottom 33%] of genetic risk): 1.35 [1.21, 1.5] | age, sex, 10 PCs of genetic ancestry, genotyping batch | The best performing PRS (e.g. C+T thresholds) were selected based on this sample set, as well as being used for the evaluation. |
| PPM000053 | PGS000026 (PHS) |
PSS000036| European Ancestry| 17,956 individuals |
PGP000016 | Desikan RS et al. PLoS Med (2017) |
Reported Trait: Alzheimer disease | — | — | r (correlation between between binned quantiles of PHS-predicted and empirical age of AD onset): 0.9 | APOE risk alleles (e2 and e4), age, sex, genetic PCs 1-5 | — |
| PPM000091 | PGS000039 (metaGRS_ischaemicstroke) |
PSS000058| European Ancestry| 395,393 individuals |
PGP000027 | Abraham G et al. Nat Commun (2019) |
Reported Trait: Ischaemic stroke before age 75 | HR: 1.26 [1.22, 1.31] | C-index: 0.585 [0.574, 0.595] | — | Sex, genotyping chip, 10 PCs | — |
| PPM000092 | PGS000038 (PRS90) |
PSS000058| European Ancestry| 395,393 individuals |
PGP000027 | Abraham G et al. Nat Commun (2019) |Ext. |
Reported Trait: Ischaemic stroke before age 75 | HR: 1.13 [1.1, 1.17] | — | — | Sex, genotyping chip, 10 PCs | — |
| PPM000142 | PGS000056 (PD_PRS) |
PSS000088| European Ancestry| 285 individuals |
PGP000041 | Paul KC et al. JAMA Neurol (2018) |
Reported Trait: Motor decline (time to UPDRS III 20-point increase | HR: 1.42 [1.0, 2.01] | — | — | sex, age at diagnosis | — |
| PPM000475 | PGS000155 (cGRS_Glioma) |
PSS000275| European Ancestry| 14,419 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Glioma | — | — | Mean realative risk: 1.22 [1.18, 1.26] Wilcoxon test (case vs. control) p-value: 1.39e-37 |
— | — |
| PPM000143 | PGS000056 (PD_PRS) |
PSS000088| European Ancestry| 285 individuals |
PGP000041 | Paul KC et al. JAMA Neurol (2018) |
Reported Trait: Motor decline (time to H&Y Scale stage ≥ 3) | HR: 1.34 [1.0, 1.79] | — | — | sex, age at diagnosis | — |
| PPM000420 | PGS000136 (SCZ_PBK) |
PSS000244| European Ancestry| 18,461 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Psychosis | OR: 1.4768 | — | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000418 | PGS000134 (SCZ_GHS) |
PSS000240| European Ancestry| 44,436 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Psychosis | OR: 1.2224 | — | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000417 | PGS000133 (SCZ_BVU) |
PSS000238| European Ancestry| 33,694 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Psychosis | OR: 1.3755 | — | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000416 | PGS000136 (SCZ_PBK) |
PSS000243| European Ancestry| 18,461 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Schizophrenia | OR: 1.7 | AUROC: 0.64 [0.6, 0.69] | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000415 | PGS000135 (SCZ_MTS) |
PSS000241| European Ancestry| 9,569 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Schizophrenia | — | AUROC: 0.74 [0.67, 0.81] | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000414 | PGS000134 (SCZ_GHS) |
PSS000239| European Ancestry| 44,436 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Schizophrenia | OR: 1.483 | AUROC: 0.6 [0.56, 0.64] | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000413 | PGS000133 (SCZ_BVU) |
PSS000237| European Ancestry| 33,694 individuals |
PGP000065 | Zheutlin AB et al. Am J Psychiatry (2019) |
Reported Trait: Schizophrenia | OR: 1.691 | AUROC: 0.6 [0.55, 0.66] | — | age, sex, 10 PCs of ancestry, genotyping platform, genotyping batch | *SNP weights were adjusted for use in this cohort |
| PPM000879 | PGS000327 (ASD2019) |
PSS000435| European Ancestry| 7,148 individuals |
PGP000098 | Grove J et al. Nat Genet (2019) |
Reported Trait: Autism spectrum disorder | OR: 1.33 [1.3, 1.36] | — | R²: 0.0245 | Genetic PCs, genotyping wave | *Pooled cross-validation performance on 1/5th of iPSYCH sample. PRS is based on full iPSYCH+PGC GWAS |
| PPM000141 | PGS000056 (PD_PRS) |
PSS000088| European Ancestry| 285 individuals |
PGP000041 | Paul KC et al. JAMA Neurol (2018) |
Reported Trait: Cognitive decline (time to MMSE 4-point decrease) | HR: 1.44 [1.0, 2.07] | — | — | sex, age at diagnosis | — |
| PPM000398 | PGS000123 (2017_PD16) |
PSS000226| European Ancestry| 786 individuals |
PGP000059 | Ibanez L et al. BMC Neurol (2017) |
Reported Trait: Age at Onset (Survival) | β: 9.3 [3.59, 15.0] | — | Association (p-value): 0.00141 | age at last assessment, sex, 2 PCs of ancestry | Cox regression |
| PPM000396 | PGS000123 (2017_PD16) |
PSS000225| European Ancestry| 469 individuals |
PGP000059 | Ibanez L et al. BMC Neurol (2017) |
Reported Trait: Age at Onset (Survival) | β: 16.62 [9.63, 23.61] | — | Association (p-value): 3.19e-06 | age at last assessment, sex, 2 PCs of ancestry | Cox regression |
| PPM000137 | PGS000053 (ALZ21_NIA-LOAD) |
PSS000085| European Ancestry| 4,792 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Alzheimer's disease (age-at-onset) | β: -0.7 (0.15) years | — | — | — | — |
| PPM000138 | PGS000054 (ALZ21_EFIGA) |
PSS000084| Hispanic or Latin American Ancestry| 3,324 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Alzheimer's disease (age-at-onset) | β: -0.86 (0.15) years | — | — | — | — |
| PPM000901 | PGS000334 (GRSfull_22) |
PSS000449| European Ancestry| 3,810 individuals |
PGP000101 | Zhang Q et al. Nat Commun (2020) |
Reported Trait: Late-onset Alzheimer’s disease | — | — | R²: 0.191 [0.131, 0.269] | — | R2 = variance explained on the liability scale |
| PPM000133 | PGS000053 (ALZ21_NIA-LOAD) |
PSS000085| European Ancestry| 4,792 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Familial late-onset Alzheimer's disease (LOAD) | OR: 1.29 [1.21, 1.37] | — | — | Age, sex | — |
| PPM000134 | PGS000053 (ALZ21_NIA-LOAD) |
PSS000085| European Ancestry| 4,792 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Familial late-onset Alzheimer's disease (LOAD) | OR: 1.29 [1.21, 1.38] | — | — | Age, sex, APOE e4 | — |
| PPM000135 | PGS000054 (ALZ21_EFIGA) |
PSS000084| Hispanic or Latin American Ancestry| 3,324 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Familial late-onset Alzheimer's disease (LOAD) | OR: 1.73 [1.57, 1.93] | — | — | Age, sex | — |
| PPM000136 | PGS000054 (ALZ21_EFIGA) |
PSS000084| Hispanic or Latin American Ancestry| 3,324 individuals |
PGP000039 | Tosto G et al. Neurology (2017) |
Reported Trait: Familial late-onset Alzheimer's disease (LOAD) | OR: 1.71 [1.55, 1.9] | — | — | Age, sex, APOE e4 | — |
| PPM000433 | PGS000141 (Psypsy) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.52988 | R²: 0.00438 | Cohort | — |
| PPM000397 | PGS000123 (2017_PD16) |
PSS000226| European Ancestry| 786 individuals |
PGP000059 | Ibanez L et al. BMC Neurol (2017) |
Reported Trait: Parkinson disease | β: 4.85 [2.32, 7.39] | — | Association (p-value): 0.00018 | age at last assessment, sex, 2 PCs of ancestry | — |
| PPM000395 | PGS000123 (2017_PD16) |
PSS000225| European Ancestry| 469 individuals |
PGP000059 | Ibanez L et al. BMC Neurol (2017) |
Reported Trait: Parkinson disease | β: 5.84 [3.1, 8.59] | — | Association (p-value): 3e-05 | age at last assessment, sex, 2 PCs of ancestry | — |
| PPM000437 | PGS000145 (ICD10Dep) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.5251 | R²: 0.0032 | Cohort | — |
| PPM000434 | PGS000142 (DepAll) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.5333 | R²: 0.00492 | Cohort | — |
| PPM000432 | PGS000140 (GPpsy) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.53193 | R²: 0.00481 | Cohort | — |
| PPM000431 | PGS000139 (MDDRecur) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.54874 | R²: 0.01097 | Cohort | — |
| PPM000430 | PGS000138 (LifetimeMDD) |
PSS000250| European Ancestry| 36,709 individuals |
PGP000068 | Cai N et al. Nat Genet (2020) |
Reported Trait: Major Depressive Disorder status | — | AUROC: 0.5611 | R²: 0.01817 | Cohort | — |
| PPM000486 | PGS000155 (cGRS_Glioma) |
PSS000275| European Ancestry| 14,419 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Glioma | — | — | Odds Ratio (OR; high vs. average risk groups): 1.8 [1.55, 2.1] | — | — |
| PPM001304 | PGS000619 (PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_PT_UKB_20200608) |
PSS000578| European Ancestry| 3,110 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain and nervous system | OR: 1.564 [1.396, 1.753] β: 0.448 (0.0581) |
AUROC: 0.622 [0.59, 0.653] | Nagelkerke's Pseudo-R²: 0.0401 Brier score: 0.0812 Odds Ratio (OR, top 1% vs. Rest): 2.93 [1.34, 6.41] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_PT_UKB_20200608 |
| PPM001307 | PGS000622 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_UKB_20200608) |
PSS000577| European Ancestry| 3,020 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.486 [1.315, 1.679] β: 0.396 (0.0624) |
AUROC: 0.605 [0.569, 0.639] | Nagelkerke's Pseudo-R²: 0.0289 Brier score: 0.0815 Odds Ratio (OR, top 1% vs. Rest): 3.38 [1.59, 7.2] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_UKB_20200608 |
| PPM001310 | PGS000625 (PRSWEB_PHECODE191.11_UKBB-SAIGE-HRC-X191.11_PT_MGI_20200608) |
PSS000557| European Ancestry| 2,563 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.142 [1.004, 1.299] β: 0.133 (0.0657) |
AUROC: 0.53 [0.492, 0.57] | Nagelkerke's Pseudo-R²: 0.00328 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 2.28 [0.88, 5.88] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_UKBB-SAIGE-HRC-X191.11_PT_MGI_20200608 |
| PPM001302 | PGS000617 (PRSWEB_PHECODE190_20001-1030_PRS-CS_MGI_20200608) |
PSS000556| European Ancestry| 672 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of eye | OR: 1.339 [1.033, 1.736] β: 0.292 (0.132) |
AUROC: 0.586 [0.508, 0.658] | Nagelkerke's Pseudo-R²: 0.0152 Brier score: 0.0831 Odds Ratio (OR, top 1% vs. Rest): 4.74 [1.2, 18.7] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE190_20001-1030_PRS-CS_MGI_20200608 |
| PPM001303 | PGS000618 (PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_P_5e-08_UKB_20200608) |
PSS000578| European Ancestry| 3,110 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain and nervous system | OR: 1.569 [1.399, 1.759] β: 0.45 (0.0585) |
AUROC: 0.623 [0.592, 0.656] | Nagelkerke's Pseudo-R²: 0.0401 Brier score: 0.0812 Odds Ratio (OR, top 1% vs. Rest): 3.64 [1.76, 7.53] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.1_GWAS-Catalog-r2019-05-03-X191.1_P_5e-08_UKB_20200608 |
| PPM001305 | PGS000620 (PRSWEB_PHECODE191.11_C71_LASSOSUM_MGI_20200608) |
PSS000557| European Ancestry| 2,563 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.195 [1.045, 1.367] β: 0.179 (0.0686) |
AUROC: 0.546 [0.504, 0.587] | Nagelkerke's Pseudo-R²: 0.00561 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 1.42 [0.453, 4.47] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_C71_LASSOSUM_MGI_20200608 |
| PPM001306 | PGS000621 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_MGI_20200608) |
PSS000557| European Ancestry| 2,563 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.159 [1.015, 1.324] β: 0.148 (0.068) |
AUROC: 0.54 [0.503, 0.579] | Nagelkerke's Pseudo-R²: 0.00394 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 1.02 [0.271, 3.86] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_P_5e-08_MGI_20200608 |
| PPM001308 | PGS000623 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_MGI_20200608) |
PSS000557| European Ancestry| 2,563 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.153 [1.01, 1.316] β: 0.142 (0.0676) |
AUROC: 0.538 [0.501, 0.577] | Nagelkerke's Pseudo-R²: 0.00369 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 0.602 [0.113, 3.22] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_MGI_20200608 |
| PPM001309 | PGS000624 (PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_UKB_20200608) |
PSS000577| European Ancestry| 3,020 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Cancer of brain | OR: 1.515 [1.344, 1.708] β: 0.415 (0.0611) |
AUROC: 0.606 [0.568, 0.642] | Nagelkerke's Pseudo-R²: 0.0326 Brier score: 0.0813 Odds Ratio (OR, top 1% vs. Rest): 4.15 [2.04, 8.41] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE191.11_GWAS-Catalog-r2019-05-03-X191.11_PT_UKB_20200608 |
| PPM002216 | PGS000823 (GRS23_AD) |
PSS001080| European Ancestry| 12,255 individuals |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Reported Trait: Incident dementia at age 85 in individuals homozygous for APOE ε4 | — | — | Cumulative risk p-value (top 33.3% vs bottom 33.3%): 0.00022 | Mortality | — |
| PPM001373 | PGS000665 (GRS_32) |
PSS000602| European Ancestry| 51,288 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke | — | — | Hazard Ratio (HR, top vs. bottom tertile): 1.24 [1.05, 1.45] Hazard Ratio (HR, intermediate vs. bottom tertile): 1.15 [0.98, 1.36] |
age, sex, PCs(1-5), hypertension, hyperlipidemia, diabetes mellitus, smoking, bascular disease, congestive heart failure, atrial fibrillation | — |
| PPM001374 | PGS000665 (GRS_32) |
PSS000602| European Ancestry| 51,288 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke | — | C-index: 0.65 [0.63, 0.66] | — | Clinical variables from the Revised Framingham Stroke Risk score, geographic region | — |
| PPM001375 | PGS000665 (GRS_32) |
PSS000601| European Ancestry| 11,187 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke in individuals with atrial fibrillation | — | — | Hazard Ratio (HR, top vs. bottom tertile): 1.29 [1.01, 1.64] | age, sex, PCs(1-5), hypertension, hyperlipidemia, diabetes mellitus, smoking, bascular disease, congestive heart failure, atrial fibrillation, components of CHA2DS2-VASc score | — |
| PPM000564 | PGS000193 (MDD_0.001_Coleman_2020) |
PSS000294| European Ancestry| 92,957 individuals |
PGP000080 | Coleman JRI et al. Mol Psychiatry (2020) |
Reported Trait: Major depressive disorder | OR: 1.179 | — | R²: 0.01485 Nagelkerke pseudo-R2 (increase when adding PRS to null model of covariates): 0.00785 |
batch, centre, genomic prinicipal components (x6) | — |
| PPM000648 | PGS000211 (PD19) |
PSS000358| European Ancestry| 336 individuals |
PGP000087 | Pihlstrøm L et al. Mov Disord (2016) |
Reported Trait: Motor decline (time to Hoehn & Yahr ≥ 3) | HR: 1.29 [1.06, 1.56] | — | — | sex, age at diagnosis | — |
| PPM002190 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Retinal hemorrhage in inidividuals with type 2 diabetes | OR: 1.44 [1.03, 2.02] | — | — | — | — |
| PPM001904 | PGS000750 (PRS_43) |
PSS000952| Multi-ancestry (including European)| 486 individuals |
PGP000155 | Bobbili DR et al. J Med Genet (2020) |
Reported Trait: Parkinson's disease | — | AUROC: 0.703 [0.698, 0.708] | — | Sex, singleton loss of function variant count, Parkinson's disease family history. | Mean AUROC over 1000 repetitions on test sets randomly drawn with a 0.9 training-test pslit |
| PPM001905 | PGS000750 (PRS_43) |
PSS000952| Multi-ancestry (including European)| 486 individuals |
PGP000155 | Bobbili DR et al. J Med Genet (2020) |
Reported Trait: Parkinson's disease | — | AUROC: 0.653 [0.647, 0.659] | — | Sex, singleton loss of function variant count. | Mean AUROC over 1000 repetitions on test sets randomly drawn with a 0.9 training-test pslit |
| PPM001906 | PGS000750 (PRS_43) |
PSS000952| Multi-ancestry (including European)| 486 individuals |
PGP000155 | Bobbili DR et al. J Med Genet (2020) |
Reported Trait: Parkinson's disease | — | AUROC: 0.616 [0.611, 0.621] | — | Sex | Mean AUROC over 1000 repetitions on test sets randomly drawn with a 0.9 training-test pslit |
| PPM001925 | PGS000756 (GRS3_Nar) |
PSS000966| East Asian Ancestry| 2,884 individuals |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Reported Trait: Incident narcolepsy | OR: 1.149 [1.119, 1.181] | — | Odds Ratio (OR, high vs low risk): 2.586 [2.109, 3.173] | — | Individuals with a high polygenic risk had a score ≥28. Individuals with a low polygenic risk had a score <25. |
| PPM001926 | PGS000756 (GRS3_Nar) |
PSS000966| East Asian Ancestry| 2,884 individuals |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Reported Trait: Incident narcolepsy | OR: 1.152 [1.12, 1.185] | AUROC: 0.723 | Odds Ratio (OR, high vs low risk): 2.602 [2.097, 3.232] | Gender | Individuals with a high polygenic risk had a score ≥28. Individuals with a low polygenic risk had a score <25. |
| PPM001927 | PGS000757 (GRS4_Nar) |
PSS000966| East Asian Ancestry| 2,884 individuals |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Reported Trait: Incident narcolepsy | OR: 1.449 [1.367, 1.536] | — | Odds Ratio (OR, high vs low risk): 4.298 [3.378, 5.481] | — | Individuals with a high polygenic risk had a score ≥8. Individuals with a low polygenic risk had a score <6. |
| PPM001928 | PGS000757 (GRS4_Nar) |
PSS000966| East Asian Ancestry| 2,884 individuals |
PGP000162 | Ouyang H et al. Ann Transl Med (2020) |
Reported Trait: Incident narcolepsy | OR: 1.442 [1.357, 1.534] | AUROC: 0.736 | Odds Ratio (OR, high vs low risk): 4.157 [3.224, 5.371] | Gender | Individuals with a high polygenic risk had a score ≥8. Individuals with a low polygenic risk had a score <6. |
| PPM001937 | PGS000763 (PRS_HAID) |
PSS000971| European Ancestry| 2,912 individuals |
PGP000165 | Cherny SS et al. Eur J Hum Genet (2020) |
Reported Trait: Hearing aid use | — | — | R²: 0.1923 | Age, sex | — |
| PPM001938 | PGS000762 (PRS_HD) |
PSS000972| European Ancestry| 3,636 individuals |
PGP000165 | Cherny SS et al. Eur J Hum Genet (2020) |
Reported Trait: Hearing difficulties | — | — | R²: 0.0911 | Age, sex | — |
| PPM001972 | PGS000767 (GRS14) |
PSS000984| Multi-ancestry (including European)| 62 individuals |
PGP000174 | Guffanti G et al. Transl Psychiatry (2019) |
Reported Trait: Bilateral Nucleus acumbens stress induced reward prediciton error change | — | — | R²: 0.065 | PCs(1-2) | — |
| PPM001973 | PGS000767 (GRS14) |
PSS000985| Multi-ancestry (including European)| 63 individuals |
PGP000174 | Guffanti G et al. Transl Psychiatry (2019) |
Reported Trait: Bilateral putamen stress induced reward prediciton error change | — | — | R²: 0.074 | PCs(1-2) | — |
| PPM001974 | PGS000767 (GRS14) |
PSS000986| Multi-ancestry (including European)| 73 individuals |
PGP000174 | Guffanti G et al. Transl Psychiatry (2019) |
Reported Trait: Bilateral nucleus acumbens volume | — | — | R²: 0.064 | PCs(1-2) | — |
| PPM001975 | PGS000767 (GRS14) |
PSS000986| Multi-ancestry (including European)| 73 individuals |
PGP000174 | Guffanti G et al. Transl Psychiatry (2019) |
Reported Trait: Bilateral putamen volume | — | — | R²: 0.095 | PCs(1-2) | — |
| PPM002022 | PGS000779 (PGS7_AD) |
PSS001005| East Asian Ancestry| 112 individuals |
PGP000183 | Zhou X et al. Alzheimers Dement (Amst) (2020) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.612 | Beta (β, top 33.3% vs bottom 33.3%): 1.485 (0.602) | Age, sex | — |
| PPM002023 | PGS000779 (PGS7_AD) |
PSS001006| European Ancestry| 2,696 individuals |
PGP000183 | Zhou X et al. Alzheimers Dement (Amst) (2020) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.717 | Beta (β, top 33.3% vs bottom 33.3%): 2.283 (1.021) | Age, sex, PCs(1-5) | — |
| PPM002036 | PGS000781 (GRS7_Glio) |
PSS001009| Multi-ancestry (including European)| 734 individuals |
PGP000185 | Adel Fahmideh M et al. Sci Rep (2019) |
Reported Trait: Pediatric brain tumors | OR: 1.25 [1.06, 1.49] | — | R²: 0.012 | Age, sex, country | — |
| PPM002137 | PGS000809 (PRS127_MS) |
PSS001050| European Ancestry| 725 individuals |
PGP000194 | Barnes CLK et al. Eur J Hum Genet (2021) |
Reported Trait: Multiple sclerosis | β: 0.6 | AUROC: 0.705 (0.029) | R²: 0.07 | Age, sex, PCs(1-2) | — |
| PPM002138 | PGS000809 (PRS127_MS) |
PSS001051| European Ancestry| 656 individuals |
PGP000194 | Barnes CLK et al. Eur J Hum Genet (2021) |
Reported Trait: Multiple sclerosis | β: 0.59 | AUROC: 0.762 (0.055) | R²: 0.075 | Age, sex, PCs(1-2) | — |
| PPM002139 | PGS000809 (PRS127_MS) |
PSS001049| European Ancestry| 8,370 individuals |
PGP000194 | Barnes CLK et al. Eur J Hum Genet (2021) |
Reported Trait: Multiple Sclerosis | β: 0.63 | AUROC: 0.765 (0.042) | R²: 0.069 | Age, sex, PCs(1-2) | — |
| PPM002014 | PGS000777 (PHS3_PDD) |
PSS000997| Multi-ancestry (including European)| 404 individuals |
PGP000181 | Liu G et al. Nat Genet (2021) |
Reported Trait: Parkinson's disease dementia | HR: 2.05 [1.16, 3.61] | AUROC: 0.688 [0.519, 0.817] | Hazard's Ratio (HR, top 25% vs PHS of 0): 3.2 [1.26, 8.11] | Age at Parkinson's disease onset, sex, years of education, PCs(1-10), study cohort, genetic factors (genes: GBA, APOE ε4) | — |
| PPM002140 | PGS000811 (AD-PRS_39) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in APOE ɛ4 non-carriers | HR: 1.22 [1.1, 1.35] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002141 | PGS000812 (AD-PRS_57) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia | HR: 1.09 [1.01, 1.19] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002142 | PGS000812 (AD-PRS_57) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in APOE ɛ4 non-carriers | HR: 1.15 [1.05, 1.27] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002143 | PGS000811 (AD-PRS_39) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in APOE ɛ4 non-carriers aged between 70 and 94 | HR: 1.16 [1.01, 1.34] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002144 | PGS000811 (AD-PRS_39) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in APOE ɛ4 non-carriers aged 95 years or above | HR: 1.28 [1.1, 1.5] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002145 | PGS000811 (AD-PRS_39) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in APOE ɛ4 carriers aged 95 years or above | HR: 0.62 [0.41, 0.95] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002146 | PGS000812 (AD-PRS_57) |
PSS001052| European Ancestry| 2,052 individuals |
PGP000196 | Najar J et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Incident dementia in individuals aged 95 or above | HR: 1.15 [1.01, 1.32] | — | — | Age at blood sampling, birth year, sex, PCs(1-10) | — |
| PPM002221 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.41 [1.2, 1.65] | AUROC: 0.685 [0.64, 0.73] | Hazard Ratio (HR, top 33.3% vs bottom 33.3%): 1.74 [1.19, 2.56] | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. For AUROC values this was 11,385 individuals (158 cases). |
| PPM002222 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | — | — | Net reclassification index (NRI): 0.252 [0.175, 0.434] | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 11,385 individuals (158 cases) were used. |
| PPM002223 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.43 [1.22, 1.68] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, PCs(1-10) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002224 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.43 [1.22, 1.68] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, intake of antihypertensive drugs, intake of statin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002225 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.41 [1.2, 1.66] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, index of relative socio-economic advantage and disadvantage(1-10) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002226 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.4 [1.2, 1.64] | — | — | Age, sex, systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, alcohol consumption (current versus former or never consumption) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002227 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | — | AUROC: 0.582 [0.537, 0.628] | — | — | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. For AUROC values only 11,385 individuals (158 cases) were used. |
| PPM002228 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident large vessel ischemic stroke | HR: 1.43 [1.05, 1.94] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. |
| PPM002229 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident cardiometabolic ischemic stroke | HR: 1.74 [1.24, 2.43] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. |
| PPM002218 | PGS000823 (GRS23_AD) |
PSS001080| European Ancestry| 12,255 individuals |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Reported Trait: Incident dementia at age 90 | — | — | Cumulative risk p-value (top 33.3% vs bottom 33.3%): 5.20e-13 | Mortality | — |
| PPM002219 | PGS000823 (GRS23_AD) |
PSS001081| European Ancestry| 12,978 individuals |
PGP000208 | Riaz M et al. Aging Cell (2021) |Ext. |
Reported Trait: Incident all-cause dementia | — | — | Hazard Ratio (HR, top 33.3% vs bottom 33.3%): 1.36 [1.04, 1.76] | Age at enrolment, sex | — |
| PPM002220 | PGS000823 (GRS23_AD) |
PSS001081| European Ancestry| 12,978 individuals |
PGP000208 | Riaz M et al. Aging Cell (2021) |Ext. |
Reported Trait: Incident all-cause dementia | — | — | Hazard Ratio (HR, top 33.3% vs bottom 33.3%): 1.36 [1.04, 1.77] | Age at enrolment, sex, competing risk of death | — |
| PPM002185 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.12 [1.04, 1.2] | — | — | — | — |
| PPM002186 | PGS000819 (PRS_DR) |
PSS001066| European Ancestry| 978 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.22 [1.02, 1.41] | — | — | — | — |
| PPM002187 | PGS000819 (PRS_DR) |
PSS001065| African Ancestry| 1,925 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.15 [1.03, 1.28] | — | — | — | — |
| PPM002188 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | — | — | Odds Ratio (OR, top 10% vs bottom 10%): 1.8 [1.28, 2.55] | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002189 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.14 [1.05, 1.23] | — | — | PCs(1-20), type 2 diabetes duration, type 2 diabetes medication, hyperglycemia, elevated HbA1c, hypertension, hypercholesterolemia, hyperlipidemia, insomina, sleep apnea, age, sex, body mass index | — |
| PPM002191 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diplopia in individuals with type 2 diabetes | OR: 1.31 [1.02, 1.7] | — | — | — | — |
| PPM002192 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Time to diabetic retinopathy diagnosis in individuals with type 2 diabetes | HR: 1.13 [1.05, 1.21] | — | — | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002393 | PGS000862 (DR) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.98 [0.89, 1.08] | — | — | PC1-10 | — |
| PPM002395 | PGS000862 (DR) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM005177 | PGS001353 (PRS6_PD) |
PSS003601| Additional Asian Ancestries| 25,646 individuals |
PGP000250 | Sia MW et al. Mov Disord (2021) |
Reported Trait: Parkinson's disease | — | C-index: 0.63 [0.6, 0.66] | Hazard Ratio (HR, top 33.3% vs bottom 33.3%): 1.81 [1.37, 2.39] Hazard Ratio (HR, top 33.3% vs middle 33.3%): 1.35 [1.0, 1.83] |
Age of recruitment, year of interview (1993-1995, 1996-1998), dialect group (Cantonese, Hokkien), level of education (no formal education, primary school, secondary school or higher), body mass index (<20, 20-<24, 24-<28, 28+ kg/m2) | — |
| PPM002504 | PGS000026 (PHS) |
PSS001127| European Ancestry| 8,415 individuals |
PGP000222 | Leonenko G et al. Ann Clin Transl Neurol (2019) |Ext. |
Reported Trait: Age at Alzheimer's disease onset | β: 0.11 (0.02) | — | — | Gender, PCs (1-3), APOE(ε2 + ε4) | Due to SNP availability issues in the dataset, only 25 out of the 31 variants in Desikan et al's polygenic hazard score (PGS000026) were used. No APOE alleles were included |
| PPM002505 | PGS000876 (PRS31_AD) |
PSS001127| European Ancestry| 8,415 individuals |
PGP000222 | Leonenko G et al. Ann Clin Transl Neurol (2019) |
Reported Trait: Age at Alzheimer's disease onset | β: 0.13 (0.02) | — | — | Gender, PCs (1-3), APOE(ε2 + ε4) | Due to SNP availability issues in the dataset, only 25 out of the 31 variants used to construct the polygenic risk score were used. |
| PPM002506 | PGS000876 (PRS31_AD) |
PSS001125| European Ancestry| 9,903 individuals |
PGP000222 | Leonenko G et al. Ann Clin Transl Neurol (2019) |
Reported Trait: Age at Alzheimer's disease onset | β: 0.28 (0.04) | — | — | Gender, PCs (1-3), APOE ε2, APOE ε4 | — |
| PPM002507 | PGS000876 (PRS31_AD) |
PSS001126| European Ancestry| 4,100 individuals |
PGP000222 | Leonenko G et al. Ann Clin Transl Neurol (2019) |
Reported Trait: Age at Alzheimer's disease onset in individuals above the age of 55 | β: 0.29 (0.03) | — | — | Gender, PCs (1-3), APOE ε2, APOE ε4 | — |
| PPM002634 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Alzheimer's disease (clinically confirmed) | OR: 1.3 [1.18, 1.44] | — | — | PCs(1-4) | — |
| PPM002635 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Alzheimer's disease (pathologically confirmed) | OR: 1.38 [1.21, 1.58] | — | — | PCs(1-4) | — |
| PPM002636 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Alzheimer's disease (pathologically confirmed, males) | OR: 1.33 [1.13, 1.56] | — | — | PCs(1-4) | — |
| PPM002637 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Alzheimer's disease (pathologically confirmed, females) | OR: 1.32 [1.19, 1.47] | — | — | PCs(1-4) | — |
| PPM002638 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Early-onset Alzheimer's disease (< 65 years) | OR: 1.58 [1.22, 2.05] | — | — | PCs(1-4) | — |
| PPM002639 | PGS000898 (PRS39_AD) |
PSS001167| European Ancestry| 2,394 individuals |
PGP000231 | de Rojas I et al. Nat Commun (2021) |
Reported Trait: Late-onset Alzheimer's disease (> 85 years) | OR: 1.29 [1.1, 1.51] | — | — | PCs(1-4) | — |
| PPM002664 | PGS000903 (PRS1805_PD) |
PSS001174| Multi-ancestry (including European)| 999 individuals |
PGP000235 | Nalls MA et al. Lancet Neurol (2019) |
Reported Trait: Parkinson's disease | β: 0.709 (0.072) | AUROC: 0.692 | R²: 0.054 Odds Ratio (OR, top 25% vs bottom 25%): 6.25 [4.26, 9.28] |
PCs(1-5), age, sex | — |
| PPM002665 | PGS000902 (PRS90_PD) |
PSS001174| Multi-ancestry (including European)| 999 individuals |
PGP000235 | Nalls MA et al. Lancet Neurol (2019) |
Reported Trait: Parkinson's disease | — | AUROC: 0.651 [0.617, 0.684] | — | PCs(1-5), age, sex | Only 88 SNPs from the 90 SNP PRS were utilised. 2 SNPs were not included as they failed to pass quality control in the HBS cohort. |
| PPM002681 | PGS000907 (PRS_MDD) |
PSS001279| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Escitalopram takers | OR: 1.0 [0.92, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002682 | PGS000907 (PRS_MDD) |
PSS001284| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Venlafaxine takers | OR: 1.05 [0.96, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002684 | PGS000907 (PRS_MDD) |
PSS001281| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Mirtazapine takers | OR: 1.05 [0.91, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002685 | PGS000907 (PRS_MDD) |
PSS001277| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Desvenlafaxine takers | OR: 1.01 [0.91, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002686 | PGS000907 (PRS_MDD) |
PSS001276| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Citalopram takers | OR: 1.02 [0.9, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002687 | PGS000907 (PRS_MDD) |
PSS001280| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Fluoxetine takers | OR: 1.06 [0.96, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002688 | PGS000907 (PRS_MDD) |
PSS001278| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Duloxetine takers | OR: 1.06 [0.95, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002689 | PGS000907 (PRS_MDD) |
PSS001282| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Paroxetine takers | OR: 1.08 [0.92, 1.26] | — | Variance explained (Nagelkerke's R2*100): 0.11 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002690 | PGS000907 (PRS_MDD) |
PSS001243| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Sertraline takers | OR: 1.06 [0.98, 1.14] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002691 | PGS000907 (PRS_MDD) |
PSS001239| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Escitalopram takers | OR: 1.06 [0.98, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002692 | PGS000907 (PRS_MDD) |
PSS001244| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Venlafaxine takers | OR: 1.01 [0.93, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002693 | PGS000907 (PRS_MDD) |
PSS001235| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Amitriptyline takers | OR: 0.96 [0.83, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002694 | PGS000907 (PRS_MDD) |
PSS001241| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Mirtazapine takers | OR: 1.07 [0.93, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002695 | PGS000907 (PRS_MDD) |
PSS001237| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Desvenlafaxine takers | OR: 0.97 [0.87, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002696 | PGS000907 (PRS_MDD) |
PSS001236| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Citalopram takers | OR: 0.99 [0.87, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002697 | PGS000907 (PRS_MDD) |
PSS001240| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Fluoxetine takers | OR: 1.16 [1.04, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.41 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002698 | PGS000907 (PRS_MDD) |
PSS001238| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Duloxetine takers | OR: 0.98 [0.88, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002699 | PGS000907 (PRS_MDD) |
PSS001242| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dizziness in Paroxetine takers | OR: 1.08 [0.93, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.12 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002700 | PGS000907 (PRS_MDD) |
PSS001373| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Sertraline takers | OR: 1.03 [0.94, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002701 | PGS000907 (PRS_MDD) |
PSS001369| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Escitalopram takers | OR: 1.01 [0.9, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002702 | PGS000907 (PRS_MDD) |
PSS001374| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Venlafaxine takers | OR: 1.1 [1.0, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.18 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002703 | PGS000907 (PRS_MDD) |
PSS001365| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Amitriptyline takers | OR: 0.99 [0.81, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002704 | PGS000907 (PRS_MDD) |
PSS001371| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Mirtazapine takers | OR: 1.03 [0.86, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002705 | PGS000907 (PRS_MDD) |
PSS001367| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Desvenlafaxine takers | OR: 1.04 [0.92, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002707 | PGS000907 (PRS_MDD) |
PSS001370| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Fluoxetine takers | OR: 1.06 [0.95, 1.19] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002708 | PGS000907 (PRS_MDD) |
PSS001368| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Duloxetine takers | OR: 0.9 [0.79, 1.04] | — | Variance explained (Nagelkerke's R2*100): 0.21 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002709 | PGS000907 (PRS_MDD) |
PSS001372| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Paroxetine takers | OR: 1.19 [1.0, 1.41] | — | Variance explained (Nagelkerke's R2*100): 0.53 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002710 | PGS000907 (PRS_MDD) |
PSS001303| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Sertraline takers | OR: 1.13 [0.97, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.18 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002711 | PGS000907 (PRS_MDD) |
PSS001299| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Escitalopram takers | OR: 0.96 [0.8, 1.14] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002712 | PGS000907 (PRS_MDD) |
PSS001304| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Venlafaxine takers | OR: 1.22 [1.03, 1.45] | — | Variance explained (Nagelkerke's R2*100): 0.51 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002713 | PGS000907 (PRS_MDD) |
PSS001295| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Amitriptyline takers | OR: 1.06 [0.8, 1.4] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002715 | PGS000907 (PRS_MDD) |
PSS001297| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Desvenlafaxine takers | OR: 1.0 [0.8, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002716 | PGS000907 (PRS_MDD) |
PSS001296| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Citalopram takers | OR: 0.95 [0.72, 1.27] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002717 | PGS000907 (PRS_MDD) |
PSS001300| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Fluoxetine takers | OR: 1.3 [1.05, 1.6] | — | Variance explained (Nagelkerke's R2*100): 0.77 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002718 | PGS000907 (PRS_MDD) |
PSS001298| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Duloxetine takers | OR: 0.99 [0.82, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002720 | PGS000907 (PRS_MDD) |
PSS001263| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Sertraline takers | OR: 1.04 [0.98, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002721 | PGS000907 (PRS_MDD) |
PSS001259| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Escitalopram takers | OR: 1.01 [0.94, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002722 | PGS000907 (PRS_MDD) |
PSS001264| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Venlafaxine takers | OR: 0.98 [0.91, 1.05] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002723 | PGS000907 (PRS_MDD) |
PSS001255| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Amitriptyline takers | OR: 1.06 [0.95, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002724 | PGS000907 (PRS_MDD) |
PSS001261| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Mirtazapine takers | OR: 1.05 [0.94, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002725 | PGS000907 (PRS_MDD) |
PSS001257| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Desvenlafaxine takers | OR: 1.09 [0.99, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.2 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002726 | PGS000907 (PRS_MDD) |
PSS001256| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Citalopram takers | OR: 1.11 [1.0, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.23 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002727 | PGS000907 (PRS_MDD) |
PSS001260| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Fluoxetine takers | OR: 1.0 [0.92, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002728 | PGS000907 (PRS_MDD) |
PSS001258| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Duloxetine takers | OR: 1.03 [0.93, 1.13] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002729 | PGS000907 (PRS_MDD) |
PSS001262| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Dry mouth in Paroxetine takers | OR: 0.98 [0.86, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002730 | PGS000907 (PRS_MDD) |
PSS001403| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Sertraline takers | OR: 0.99 [0.92, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002731 | PGS000907 (PRS_MDD) |
PSS001399| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Escitalopram takers | OR: 0.97 [0.89, 1.06] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002732 | PGS000907 (PRS_MDD) |
PSS001404| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Venlafaxine takers | OR: 1.04 [0.96, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002733 | PGS000907 (PRS_MDD) |
PSS001395| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Amitriptyline takers | OR: 1.14 [0.96, 1.37] | — | Variance explained (Nagelkerke's R2*100): 0.3 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002734 | PGS000907 (PRS_MDD) |
PSS001401| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Mirtazapine takers | OR: 1.05 [0.9, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002735 | PGS000907 (PRS_MDD) |
PSS001397| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Desvenlafaxine takers | OR: 0.99 [0.9, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002736 | PGS000907 (PRS_MDD) |
PSS001396| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Citalopram takers | OR: 1.14 [0.99, 1.3] | — | Variance explained (Nagelkerke's R2*100): 0.29 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002737 | PGS000907 (PRS_MDD) |
PSS001400| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Fluoxetine takers | OR: 1.04 [0.94, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002738 | PGS000907 (PRS_MDD) |
PSS001398| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Duloxetine takers | OR: 0.96 [0.86, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002739 | PGS000907 (PRS_MDD) |
PSS001402| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Sweating in Paroxetine takers | OR: 1.1 [0.94, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.17 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002741 | PGS000907 (PRS_MDD) |
PSS001309| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Escitalopram takers | OR: 1.06 [0.98, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002742 | PGS000907 (PRS_MDD) |
PSS001314| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Venlafaxine takers | OR: 1.08 [1.0, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002743 | PGS000907 (PRS_MDD) |
PSS001305| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Amitriptyline takers | OR: 1.12 [0.95, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.22 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002744 | PGS000907 (PRS_MDD) |
PSS001311| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Mirtazapine takers | OR: 1.08 [0.93, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002745 | PGS000907 (PRS_MDD) |
PSS001307| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Desvenlafaxine takers | OR: 1.06 [0.96, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002746 | PGS000907 (PRS_MDD) |
PSS001306| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Citalopram takers | OR: 1.11 [0.99, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.24 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002747 | PGS000907 (PRS_MDD) |
PSS001310| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Fluoxetine takers | OR: 1.06 [0.97, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002748 | PGS000907 (PRS_MDD) |
PSS001308| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Duloxetine takers | OR: 1.16 [1.04, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.55 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002749 | PGS000907 (PRS_MDD) |
PSS001312| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Paroxetine takers | OR: 1.1 [0.96, 1.27] | — | Variance explained (Nagelkerke's R2*100): 0.21 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002750 | PGS000907 (PRS_MDD) |
PSS001423| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Sertraline takers | OR: 1.21 [1.03, 1.43] | — | Variance explained (Nagelkerke's R2*100): 0.44 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002751 | PGS000907 (PRS_MDD) |
PSS001419| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Escitalopram takers | OR: 0.96 [0.78, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002752 | PGS000907 (PRS_MDD) |
PSS001424| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Venlafaxine takers | OR: 1.14 [0.96, 1.36] | — | Variance explained (Nagelkerke's R2*100): 0.22 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002754 | PGS000907 (PRS_MDD) |
PSS001421| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Mirtazapine takers | OR: 1.23 [0.88, 1.72] | — | Variance explained (Nagelkerke's R2*100): 0.45 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002755 | PGS000907 (PRS_MDD) |
PSS001417| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Desvenlafaxine takers | OR: 1.08 [0.86, 1.36] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002756 | PGS000907 (PRS_MDD) |
PSS001416| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Citalopram takers | OR: 1.19 [0.87, 1.64] | — | Variance explained (Nagelkerke's R2*100): 0.32 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002757 | PGS000907 (PRS_MDD) |
PSS001420| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Fluoxetine takers | OR: 1.01 [0.8, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002758 | PGS000907 (PRS_MDD) |
PSS001418| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Duloxetine takers | OR: 1.09 [0.87, 1.35] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002759 | PGS000907 (PRS_MDD) |
PSS001422| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Paroxetine takers | OR: 1.17 [0.86, 1.61] | — | Variance explained (Nagelkerke's R2*100): 0.3 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002760 | PGS000907 (PRS_MDD) |
PSS001223| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Sertraline takers | OR: 1.15 [1.03, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.29 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002761 | PGS000907 (PRS_MDD) |
PSS001219| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Escitalopram takers | OR: 1.16 [1.01, 1.33] | — | Variance explained (Nagelkerke's R2*100): 0.32 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002762 | PGS000907 (PRS_MDD) |
PSS001224| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Venlafaxine takers | OR: 1.19 [1.07, 1.34] | — | Variance explained (Nagelkerke's R2*100): 0.54 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002763 | PGS000907 (PRS_MDD) |
PSS001215| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Amitriptyline takers | OR: 1.16 [0.98, 1.37] | — | Variance explained (Nagelkerke's R2*100): 0.38 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002764 | PGS000907 (PRS_MDD) |
PSS001221| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Mirtazapine takers | OR: 1.08 [0.89, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002765 | PGS000907 (PRS_MDD) |
PSS001217| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Desvenlafaxine takers | OR: 1.03 [0.89, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002767 | PGS000907 (PRS_MDD) |
PSS001220| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Fluoxetine takers | OR: 1.09 [0.94, 1.27] | — | Variance explained (Nagelkerke's R2*100): 0.11 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002768 | PGS000907 (PRS_MDD) |
PSS001218| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Duloxetine takers | OR: 1.02 [0.89, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002769 | PGS000907 (PRS_MDD) |
PSS001222| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Paroxetine takers | OR: 1.09 [0.9, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.12 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002771 | PGS000907 (PRS_MDD) |
PSS001229| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Escitalopram takers | OR: 1.01 [0.89, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002772 | PGS000907 (PRS_MDD) |
PSS001234| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Venlafaxine takers | OR: 1.13 [0.97, 1.32] | — | Variance explained (Nagelkerke's R2*100): 0.2 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002773 | PGS000907 (PRS_MDD) |
PSS001225| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Amitriptyline takers | OR: 1.02 [0.73, 1.42] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002774 | PGS000907 (PRS_MDD) |
PSS001231| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Mirtazapine takers | OR: 1.13 [0.89, 1.42] | — | Variance explained (Nagelkerke's R2*100): 0.18 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002775 | PGS000907 (PRS_MDD) |
PSS001227| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Desvenlafaxine takers | OR: 1.01 [0.84, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002776 | PGS000907 (PRS_MDD) |
PSS001226| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Citalopram takers | OR: 0.95 [0.76, 1.19] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002777 | PGS000907 (PRS_MDD) |
PSS001230| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Fluoxetine takers | OR: 0.99 [0.84, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002778 | PGS000907 (PRS_MDD) |
PSS001228| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Duloxetine takers | OR: 1.08 [0.9, 1.3] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002779 | PGS000907 (PRS_MDD) |
PSS001232| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Paroxetine takers | OR: 1.47 [1.13, 1.91] | — | Variance explained (Nagelkerke's R2*100): 1.92 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002780 | PGS000907 (PRS_MDD) |
PSS001253| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Sertraline takers | OR: 1.01 [0.94, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002782 | PGS000907 (PRS_MDD) |
PSS001254| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Venlafaxine takers | OR: 1.0 [0.91, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002783 | PGS000907 (PRS_MDD) |
PSS001245| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Amitriptyline takers | OR: 0.99 [0.89, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002784 | PGS000907 (PRS_MDD) |
PSS001251| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Mirtazapine takers | OR: 1.06 [0.96, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002785 | PGS000907 (PRS_MDD) |
PSS001247| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Desvenlafaxine takers | OR: 0.99 [0.88, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002786 | PGS000907 (PRS_MDD) |
PSS001246| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Citalopram takers | OR: 1.05 [0.93, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002787 | PGS000907 (PRS_MDD) |
PSS001250| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Fluoxetine takers | OR: 1.04 [0.94, 1.14] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002788 | PGS000907 (PRS_MDD) |
PSS001248| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Duloxetine takers | OR: 0.96 [0.86, 1.08] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002789 | PGS000907 (PRS_MDD) |
PSS001252| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Paroxetine takers | OR: 0.97 [0.83, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002790 | PGS000907 (PRS_MDD) |
PSS001413| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Sertraline takers | OR: 1.04 [0.97, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002791 | PGS000907 (PRS_MDD) |
PSS001409| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Escitalopram takers | OR: 1.02 [0.94, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002792 | PGS000907 (PRS_MDD) |
PSS001414| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Venlafaxine takers | OR: 1.02 [0.94, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002793 | PGS000907 (PRS_MDD) |
PSS001405| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Amitriptyline takers | OR: 1.05 [0.88, 1.26] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002794 | PGS000907 (PRS_MDD) |
PSS001411| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Mirtazapine takers | OR: 1.13 [0.97, 1.32] | — | Variance explained (Nagelkerke's R2*100): 0.27 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002795 | PGS000907 (PRS_MDD) |
PSS001407| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Desvenlafaxine takers | OR: 1.05 [0.95, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002796 | PGS000907 (PRS_MDD) |
PSS001406| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Citalopram takers | OR: 1.0 [0.89, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002797 | PGS000907 (PRS_MDD) |
PSS001410| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Fluoxetine takers | OR: 1.05 [0.96, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002798 | PGS000907 (PRS_MDD) |
PSS001408| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Duloxetine takers | OR: 0.97 [0.87, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002800 | PGS000907 (PRS_MDD) |
PSS001203| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Sertraline takers | OR: 1.13 [1.04, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.29 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002801 | PGS000907 (PRS_MDD) |
PSS001199| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Escitalopram takers | OR: 1.01 [0.91, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002802 | PGS000907 (PRS_MDD) |
PSS001204| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Venlafaxine takers | OR: 1.14 [1.04, 1.26] | — | Variance explained (Nagelkerke's R2*100): 0.36 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002803 | PGS000907 (PRS_MDD) |
PSS001195| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Amitriptyline takers | OR: 1.05 [0.87, 1.27] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002804 | PGS000907 (PRS_MDD) |
PSS001201| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Mirtazapine takers | OR: 1.2 [1.03, 1.39] | — | Variance explained (Nagelkerke's R2*100): 0.59 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002805 | PGS000907 (PRS_MDD) |
PSS001197| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Desvenlafaxine takers | OR: 1.04 [0.92, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002806 | PGS000907 (PRS_MDD) |
PSS001196| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Citalopram takers | OR: 0.97 [0.85, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002807 | PGS000907 (PRS_MDD) |
PSS001200| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Fluoxetine takers | OR: 1.05 [0.96, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002808 | PGS000907 (PRS_MDD) |
PSS001198| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Duloxetine takers | OR: 1.0 [0.87, 1.14] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002809 | PGS000907 (PRS_MDD) |
PSS001202| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Anxiety in Paroxetine takers | OR: 1.1 [0.94, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.19 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002810 | PGS000907 (PRS_MDD) |
PSS001193| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Sertraline takers | OR: 1.04 [0.96, 1.13] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002811 | PGS000907 (PRS_MDD) |
PSS001189| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Escitalopram takers | OR: 1.06 [0.96, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002812 | PGS000907 (PRS_MDD) |
PSS001194| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Venlafaxine takers | OR: 1.06 [0.97, 1.17] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002813 | PGS000907 (PRS_MDD) |
PSS001185| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Amitriptyline takers | OR: 1.02 [0.85, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002814 | PGS000907 (PRS_MDD) |
PSS001191| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Mirtazapine takers | OR: 1.25 [1.08, 1.46] | — | Variance explained (Nagelkerke's R2*100): 0.93 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002816 | PGS000907 (PRS_MDD) |
PSS001186| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Citalopram takers | OR: 1.05 [0.91, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002817 | PGS000907 (PRS_MDD) |
PSS001190| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Fluoxetine takers | OR: 1.06 [0.96, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002818 | PGS000907 (PRS_MDD) |
PSS001188| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Duloxetine takers | OR: 1.05 [0.91, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002819 | PGS000907 (PRS_MDD) |
PSS001192| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Paroxetine takers | OR: 1.19 [1.02, 1.38] | — | Variance explained (Nagelkerke's R2*100): 0.6 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002820 | PGS000907 (PRS_MDD) |
PSS001273| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Sertraline takers | OR: 1.01 [0.94, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002821 | PGS000907 (PRS_MDD) |
PSS001269| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Escitalopram takers | OR: 0.96 [0.88, 1.05] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002822 | PGS000907 (PRS_MDD) |
PSS001274| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Venlafaxine takers | OR: 1.06 [0.97, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002823 | PGS000907 (PRS_MDD) |
PSS001265| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Amitriptyline takers | OR: 1.12 [0.97, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.25 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002824 | PGS000907 (PRS_MDD) |
PSS001271| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Mirtazapine takers | OR: 1.06 [0.94, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002826 | PGS000907 (PRS_MDD) |
PSS001266| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Citalopram takers | OR: 0.98 [0.86, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002827 | PGS000907 (PRS_MDD) |
PSS001270| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Fluoxetine takers | OR: 1.02 [0.92, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002829 | PGS000907 (PRS_MDD) |
PSS001272| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Paroxetine takers | OR: 0.96 [0.82, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002831 | PGS000907 (PRS_MDD) |
PSS001429| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Escitalopram takers | OR: 1.04 [0.97, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002832 | PGS000907 (PRS_MDD) |
PSS001434| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Venlafaxine takers | OR: 1.03 [0.96, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002833 | PGS000907 (PRS_MDD) |
PSS001425| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Amitriptyline takers | OR: 1.06 [0.95, 1.19] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002834 | PGS000907 (PRS_MDD) |
PSS001431| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Mirtazapine takers | OR: 1.02 [0.93, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002835 | PGS000907 (PRS_MDD) |
PSS001427| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Desvenlafaxine takers | OR: 1.11 [1.02, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.33 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002836 | PGS000907 (PRS_MDD) |
PSS001426| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Citalopram takers | OR: 1.14 [1.03, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.4 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002837 | PGS000907 (PRS_MDD) |
PSS001430| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Fluoxetine takers | OR: 1.04 [0.96, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002838 | PGS000907 (PRS_MDD) |
PSS001428| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Duloxetine takers | OR: 1.0 [0.91, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002839 | PGS000907 (PRS_MDD) |
PSS001432| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Paroxetine takers | OR: 1.11 [0.99, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.28 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002840 | PGS000907 (PRS_MDD) |
PSS001443| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Sertraline takers | OR: 0.9 [0.75, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002841 | PGS000907 (PRS_MDD) |
PSS001439| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Escitalopram takers | OR: 1.07 [0.88, 1.32] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002842 | PGS000907 (PRS_MDD) |
PSS001444| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Venlafaxine takers | OR: 1.05 [0.84, 1.3] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002844 | PGS000907 (PRS_MDD) |
PSS001441| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Mirtazapine takers | OR: 1.21 [0.85, 1.71] | — | Variance explained (Nagelkerke's R2*100): 0.37 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002845 | PGS000907 (PRS_MDD) |
PSS001437| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Desvenlafaxine takers | OR: 0.95 [0.74, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002846 | PGS000907 (PRS_MDD) |
PSS001436| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Citalopram takers | OR: 0.87 [0.61, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.19 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002847 | PGS000907 (PRS_MDD) |
PSS001440| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Fluoxetine takers | OR: 1.16 [0.96, 1.39] | — | Variance explained (Nagelkerke's R2*100): 0.26 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002848 | PGS000907 (PRS_MDD) |
PSS001438| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Duloxetine takers | OR: 0.96 [0.75, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002849 | PGS000907 (PRS_MDD) |
PSS001442| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Paroxetine takers | OR: 1.36 [0.88, 2.1] | — | Variance explained (Nagelkerke's R2*100): 0.99 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002852 | PGS000907 (PRS_MDD) |
PSS001344| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Venlafaxine takers | OR: 1.0 [0.74, 1.36] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002853 | PGS000907 (PRS_MDD) |
PSS001335| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Amitriptyline takers | OR: 1.22 [0.73, 2.04] | — | Variance explained (Nagelkerke's R2*100): 0.42 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002854 | PGS000907 (PRS_MDD) |
PSS001341| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Mirtazapine takers | OR: 1.0 [0.65, 1.52] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002855 | PGS000907 (PRS_MDD) |
PSS001337| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Desvenlafaxine takers | OR: 1.58 [1.13, 2.23] | — | Variance explained (Nagelkerke's R2*100): 2.19 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002856 | PGS000907 (PRS_MDD) |
PSS001336| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Citalopram takers | OR: 1.1 [0.7, 1.74] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002857 | PGS000907 (PRS_MDD) |
PSS001340| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Fluoxetine takers | OR: 1.34 [0.91, 1.97] | — | Variance explained (Nagelkerke's R2*100): 0.75 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002858 | PGS000907 (PRS_MDD) |
PSS001338| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Duloxetine takers | OR: 1.13 [0.75, 1.7] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002859 | PGS000907 (PRS_MDD) |
PSS001342| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Paroxetine takers | OR: 1.16 [0.69, 1.95] | — | Variance explained (Nagelkerke's R2*100): 0.22 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002860 | PGS000907 (PRS_MDD) |
PSS001363| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Sertraline takers | OR: 1.0 [0.79, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002861 | PGS000907 (PRS_MDD) |
PSS001359| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Escitalopram takers | OR: 0.91 [0.69, 1.19] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002862 | PGS000907 (PRS_MDD) |
PSS001364| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Venlafaxine takers | OR: 1.06 [0.8, 1.42] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002863 | PGS000907 (PRS_MDD) |
PSS001355| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Amitriptyline takers | OR: 0.59 [0.36, 0.98] | — | Variance explained (Nagelkerke's R2*100): 2.43 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002864 | PGS000907 (PRS_MDD) |
PSS001361| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Mirtazapine takers | OR: 0.85 [0.55, 1.3] | — | Variance explained (Nagelkerke's R2*100): 0.25 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002865 | PGS000907 (PRS_MDD) |
PSS001357| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Desvenlafaxine takers | OR: 0.8 [0.59, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.58 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002868 | PGS000907 (PRS_MDD) |
PSS001358| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Duloxetine takers | OR: 0.99 [0.71, 1.38] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002869 | PGS000907 (PRS_MDD) |
PSS001362| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Paroxetine takers | OR: 0.9 [0.53, 1.52] | — | Variance explained (Nagelkerke's R2*100): 0.11 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002870 | PGS000907 (PRS_MDD) |
PSS001353| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Sertraline takers | OR: 1.0 [0.95, 1.06] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002871 | PGS000907 (PRS_MDD) |
PSS001349| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Escitalopram takers | OR: 0.99 [0.93, 1.06] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002872 | PGS000907 (PRS_MDD) |
PSS001354| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Venlafaxine takers | OR: 1.05 [0.99, 1.13] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002873 | PGS000907 (PRS_MDD) |
PSS001345| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Amitriptyline takers | OR: 1.08 [0.96, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.16 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002878 | PGS000907 (PRS_MDD) |
PSS001348| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Duloxetine takers | OR: 0.99 [0.91, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002879 | PGS000907 (PRS_MDD) |
PSS001352| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Paroxetine takers | OR: 1.0 [0.9, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002883 | PGS000907 (PRS_MDD) |
PSS001205| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Amitriptyline takers | OR: 1.08 [0.86, 1.36] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002884 | PGS000907 (PRS_MDD) |
PSS001211| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Mirtazapine takers | OR: 1.05 [0.84, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002885 | PGS000907 (PRS_MDD) |
PSS001207| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Desvenlafaxine takers | OR: 1.13 [0.94, 1.37] | — | Variance explained (Nagelkerke's R2*100): 0.22 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002886 | PGS000907 (PRS_MDD) |
PSS001206| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Citalopram takers | OR: 1.39 [1.08, 1.79] | — | Variance explained (Nagelkerke's R2*100): 1.2 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002887 | PGS000907 (PRS_MDD) |
PSS001210| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Fluoxetine takers | OR: 1.03 [0.85, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002888 | PGS000907 (PRS_MDD) |
PSS001208| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Duloxetine takers | OR: 1.04 [0.87, 1.26] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002889 | PGS000907 (PRS_MDD) |
PSS001212| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Paroxetine takers | OR: 1.32 [1.0, 1.75] | — | Variance explained (Nagelkerke's R2*100): 0.99 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002890 | PGS000907 (PRS_MDD) |
PSS001393| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Sertraline takers | OR: 1.24 [1.14, 1.34] | — | Variance explained (Nagelkerke's R2*100): 0.9 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002894 | PGS000907 (PRS_MDD) |
PSS001391| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Mirtazapine takers | OR: 1.09 [0.94, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002895 | PGS000907 (PRS_MDD) |
PSS001387| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Desvenlafaxine takers | OR: 1.06 [0.94, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002896 | PGS000907 (PRS_MDD) |
PSS001386| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Citalopram takers | OR: 1.06 [0.92, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002897 | PGS000907 (PRS_MDD) |
PSS001390| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Fluoxetine takers | OR: 1.12 [1.02, 1.23] | — | Variance explained (Nagelkerke's R2*100): 0.27 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002898 | PGS000907 (PRS_MDD) |
PSS001388| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Duloxetine takers | OR: 0.98 [0.86, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002899 | PGS000907 (PRS_MDD) |
PSS001392| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Paroxetine takers | OR: 1.22 [1.05, 1.42] | — | Variance explained (Nagelkerke's R2*100): 0.8 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002900 | PGS000907 (PRS_MDD) |
PSS001383| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Sertraline takers | OR: 1.15 [1.01, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.28 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002901 | PGS000907 (PRS_MDD) |
PSS001379| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Escitalopram takers | OR: 1.06 [0.9, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002902 | PGS000907 (PRS_MDD) |
PSS001384| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Venlafaxine takers | OR: 1.36 [1.18, 1.58] | — | Variance explained (Nagelkerke's R2*100): 1.35 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002903 | PGS000907 (PRS_MDD) |
PSS001375| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Amitriptyline takers | OR: 0.97 [0.75, 1.24] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002904 | PGS000907 (PRS_MDD) |
PSS001381| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Mirtazapine takers | OR: 1.11 [0.88, 1.4] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002905 | PGS000907 (PRS_MDD) |
PSS001377| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Desvenlafaxine takers | OR: 0.97 [0.78, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002906 | PGS000907 (PRS_MDD) |
PSS001376| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Citalopram takers | OR: 0.96 [0.76, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002907 | PGS000907 (PRS_MDD) |
PSS001380| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Fluoxetine takers | OR: 1.09 [0.95, 1.26] | — | Variance explained (Nagelkerke's R2*100): 0.11 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002908 | PGS000907 (PRS_MDD) |
PSS001378| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Duloxetine takers | OR: 1.11 [0.89, 1.38] | — | Variance explained (Nagelkerke's R2*100): 0.15 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002909 | PGS000907 (PRS_MDD) |
PSS001382| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide attempt in Paroxetine takers | OR: 1.22 [0.95, 1.55] | — | Variance explained (Nagelkerke's R2*100): 0.54 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002910 | PGS000907 (PRS_MDD) |
PSS001333| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Sertraline takers | OR: 0.99 [0.91, 1.09] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002911 | PGS000907 (PRS_MDD) |
PSS001329| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Escitalopram takers | OR: 0.96 [0.86, 1.07] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002912 | PGS000907 (PRS_MDD) |
PSS001334| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Venlafaxine takers | OR: 1.14 [1.03, 1.27] | — | Variance explained (Nagelkerke's R2*100): 0.31 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002913 | PGS000907 (PRS_MDD) |
PSS001325| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Amitriptyline takers | OR: 1.07 [0.88, 1.29] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002914 | PGS000907 (PRS_MDD) |
PSS001331| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Mirtazapine takers | OR: 1.03 [0.87, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002915 | PGS000907 (PRS_MDD) |
PSS001327| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Desvenlafaxine takers | OR: 1.02 [0.88, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002916 | PGS000907 (PRS_MDD) |
PSS001326| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Citalopram takers | OR: 0.95 [0.82, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002917 | PGS000907 (PRS_MDD) |
PSS001330| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Fluoxetine takers | OR: 1.05 [0.93, 1.18] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002918 | PGS000907 (PRS_MDD) |
PSS001328| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Duloxetine takers | OR: 1.04 [0.89, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002919 | PGS000907 (PRS_MDD) |
PSS001332| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Other side effects in Paroxetine takers | OR: 0.97 [0.81, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002920 | PGS000907 (PRS_MDD) |
PSS001323| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Sertraline takers | OR: 1.04 [0.89, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002921 | PGS000907 (PRS_MDD) |
PSS001319| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Escitalopram takers | OR: 1.04 [0.89, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002922 | PGS000907 (PRS_MDD) |
PSS001324| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Venlafaxine takers | OR: 0.94 [0.79, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.05 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002923 | PGS000907 (PRS_MDD) |
PSS001315| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Amitriptyline takers | OR: 1.03 [0.84, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002924 | PGS000907 (PRS_MDD) |
PSS001321| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Mirtazapine takers | OR: 1.05 [0.83, 1.33] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002925 | PGS000907 (PRS_MDD) |
PSS001317| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Desvenlafaxine takers | OR: 0.82 [0.68, 0.98] | — | Variance explained (Nagelkerke's R2*100): 0.6 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002950 | PGS000908 (PRS_Insomnia) |
PSS001293| European Ancestry| 5,713 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Sertraline takers | OR: 1.06 [0.99, 1.14] | — | Variance explained (Nagelkerke's R2*100): 0.09 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002951 | PGS000908 (PRS_Insomnia) |
PSS001289| European Ancestry| 4,362 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Escitalopram takers | OR: 1.12 [1.03, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.27 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002952 | PGS000908 (PRS_Insomnia) |
PSS001294| European Ancestry| 3,964 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Venlafaxine takers | OR: 1.03 [0.95, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002953 | PGS000908 (PRS_Insomnia) |
PSS001285| European Ancestry| 1,655 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Amitriptyline takers | OR: 1.28 [1.07, 1.52] | — | Variance explained (Nagelkerke's R2*100): 1.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002954 | PGS000908 (PRS_Insomnia) |
PSS001291| European Ancestry| 1,986 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Mirtazapine takers | OR: 1.03 [0.88, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002955 | PGS000908 (PRS_Insomnia) |
PSS001287| European Ancestry| 2,523 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Desvenlafaxine takers | OR: 1.13 [1.03, 1.25] | — | Variance explained (Nagelkerke's R2*100): 0.38 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002956 | PGS000908 (PRS_Insomnia) |
PSS001286| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Citalopram takers | OR: 1.08 [0.96, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.12 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002957 | PGS000908 (PRS_Insomnia) |
PSS001290| European Ancestry| 3,665 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Fluoxetine takers | OR: 1.03 [0.94, 1.13] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002958 | PGS000908 (PRS_Insomnia) |
PSS001288| European Ancestry| 1,994 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Duloxetine takers | OR: 1.14 [1.02, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.4 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002960 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10) | — |
| PPM002961 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | AUROC: 0.605 [0.583, 0.626] | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), presence of warfarin prescription | — |
| PPM002962 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases who had not been prescribed warfarin | OR: 1.14 [1.05, 1.24] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10) | — |
| PPM002963 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), cumulative CHA2DS2-VASc score | — |
| PPM002964 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), individual components of CHA2DS2-VASc score | — |
| PPM002965 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | HR: 1.13 [1.04, 1.21] | C-index: 0.56 [0.54, 0.58] | — | Sex, UK Biobank array, PCs(1-10) | — |
| PPM002966 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | HR: 1.14 [1.01, 1.23] | C-index: 0.56 [0.54, 0.58] | — | Sex, age, UK Biobank array, PCs(1-10) | — |
| PPM002967 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases who had not been prescribed warfarin | HR: 1.13 [1.04, 1.22] | C-index: 0.57 [0.54, 0.59] | — | Sex, UK Biobank array, PCs(1-10) | — |
| PPM002968 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | — | C-index: 0.61 [0.58, 0.63] | — | Sex, UK Biobank array, PCs(1-10), cumulative CHA2DS2-VASc score | — |
| PPM002680 | PGS000907 (PRS_MDD) |
PSS001283| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Sertraline takers | OR: 1.03 [0.95, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002683 | PGS000907 (PRS_MDD) |
PSS001275| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Headaches in Amitriptyline takers | OR: 0.96 [0.81, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.04 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002706 | PGS000907 (PRS_MDD) |
PSS001366| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Shakes in Citalopram takers | OR: 1.16 [0.98, 1.38] | — | Variance explained (Nagelkerke's R2*100): 0.32 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002714 | PGS000907 (PRS_MDD) |
PSS001301| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Mirtazapine takers | OR: 1.13 [0.9, 1.43] | — | Variance explained (Nagelkerke's R2*100): 0.2 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002719 | PGS000907 (PRS_MDD) |
PSS001302| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Muscle pain in Paroxetine takers | OR: 1.18 [0.87, 1.61] | — | Variance explained (Nagelkerke's R2*100): 0.34 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002740 | PGS000907 (PRS_MDD) |
PSS001313| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Nausea in Sertraline takers | OR: 1.08 [1.01, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.13 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002753 | PGS000907 (PRS_MDD) |
PSS001415| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Vomit in Amitriptyline takers | OR: 0.93 [0.65, 1.33] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002766 | PGS000907 (PRS_MDD) |
PSS001216| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Constipation in Citalopram takers | OR: 1.02 [0.85, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002770 | PGS000907 (PRS_MDD) |
PSS001233| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Diarrhoea in Sertraline takers | OR: 1.05 [0.94, 1.16] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002781 | PGS000907 (PRS_MDD) |
PSS001249| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Drowsiness in Escitalopram takers | OR: 0.96 [0.89, 1.05] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002799 | PGS000907 (PRS_MDD) |
PSS001412| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Trouble sleeping in Paroxetine takers | OR: 1.06 [0.92, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002815 | PGS000907 (PRS_MDD) |
PSS001187| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Agitation in Desvenlafaxine takers | OR: 1.07 [0.94, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.08 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002825 | PGS000907 (PRS_MDD) |
PSS001267| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Desvenlafaxine takers | OR: 1.02 [0.91, 1.15] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002828 | PGS000907 (PRS_MDD) |
PSS001268| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Fatigue in Duloxetine takers | OR: 0.93 [0.83, 1.04] | — | Variance explained (Nagelkerke's R2*100): 0.14 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002830 | PGS000907 (PRS_MDD) |
PSS001433| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight gain in Sertraline takers | OR: 1.02 [0.96, 1.08] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002843 | PGS000907 (PRS_MDD) |
PSS001435| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Weight loss in Amitriptyline takers | OR: 1.09 [0.67, 1.78] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002850 | PGS000907 (PRS_MDD) |
PSS001343| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Sertraline takers | OR: 1.04 [0.8, 1.36] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002851 | PGS000907 (PRS_MDD) |
PSS001339| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Rashes in Escitalopram takers | OR: 1.09 [0.79, 1.5] | — | Variance explained (Nagelkerke's R2*100): 0.07 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002866 | PGS000907 (PRS_MDD) |
PSS001356| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Citalopram takers | OR: 1.05 [0.73, 1.51] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002867 | PGS000907 (PRS_MDD) |
PSS001360| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Runny nose in Fluoxetine takers | OR: 1.03 [0.76, 1.4] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002874 | PGS000907 (PRS_MDD) |
PSS001351| European Ancestry| 1,987 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Mirtazapine takers | OR: 0.99 [0.9, 1.1] | — | Variance explained (Nagelkerke's R2*100): 0.0 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002875 | PGS000907 (PRS_MDD) |
PSS001347| European Ancestry| 2,524 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Desvenlafaxine takers | OR: 1.11 [1.02, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.34 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002876 | PGS000907 (PRS_MDD) |
PSS001346| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Citalopram takers | OR: 1.1 [1.01, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.28 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002877 | PGS000907 (PRS_MDD) |
PSS001350| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Reduced sexual desire in Fluoxetine takers | OR: 1.05 [0.98, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002880 | PGS000907 (PRS_MDD) |
PSS001213| European Ancestry| 5,719 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Sertraline takers | OR: 0.96 [0.83, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002881 | PGS000907 (PRS_MDD) |
PSS001209| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Escitalopram takers | OR: 1.03 [0.87, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.01 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002882 | PGS000907 (PRS_MDD) |
PSS001214| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Blurry vision in Venlafaxine takers | OR: 0.97 [0.84, 1.12] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002891 | PGS000907 (PRS_MDD) |
PSS001389| European Ancestry| 4,365 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Escitalopram takers | OR: 1.09 [0.99, 1.2] | — | Variance explained (Nagelkerke's R2*100): 0.15 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002892 | PGS000907 (PRS_MDD) |
PSS001394| European Ancestry| 3,967 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Venlafaxine takers | OR: 1.19 [1.09, 1.31] | — | Variance explained (Nagelkerke's R2*100): 0.63 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002893 | PGS000907 (PRS_MDD) |
PSS001385| European Ancestry| 1,657 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Suicide thoughts in Amitriptyline takers | OR: 0.94 [0.8, 1.11] | — | Variance explained (Nagelkerke's R2*100): 0.06 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002926 | PGS000907 (PRS_MDD) |
PSS001316| European Ancestry| 2,585 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Citalopram takers | OR: 1.08 [0.92, 1.28] | — | Variance explained (Nagelkerke's R2*100): 0.1 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002927 | PGS000907 (PRS_MDD) |
PSS001320| European Ancestry| 3,670 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Fluoxetine takers | OR: 1.05 [0.91, 1.21] | — | Variance explained (Nagelkerke's R2*100): 0.03 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002928 | PGS000907 (PRS_MDD) |
PSS001318| European Ancestry| 1,995 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Duloxetine takers | OR: 0.91 [0.74, 1.13] | — | Variance explained (Nagelkerke's R2*100): 0.12 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002929 | PGS000907 (PRS_MDD) |
PSS001322| European Ancestry| 1,580 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: No side effects in Paroxetine takers | OR: 0.97 [0.77, 1.22] | — | Variance explained (Nagelkerke's R2*100): 0.02 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002959 | PGS000908 (PRS_Insomnia) |
PSS001292| European Ancestry| 1,577 individuals |
PGP000238 | Campos AI et al. Commun Med (Lond) (2021) |
Reported Trait: Insomnia in Paroxetine takers | OR: 1.16 [1.01, 1.33] | — | Variance explained (Nagelkerke's R2*100): 0.47 | sex, age at study enrollment, genetic PCs 1-20 | — |
| PPM002397 | PGS000862 (DR) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.01 [0.96, 1.07] | — | — | PC1-10 | — |
| PPM002394 | PGS000862 (DR) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.03 [0.96, 1.1] | — | — | PC1-10 | — |
| PPM002396 | PGS000862 (DR) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM009233 | PGS001774 (PRS12_PD) |
PSS007662| European Ancestry| 699 individuals |
PGP000254 | Chairta PP et al. Genes (Basel) (2021) |
Reported Trait: Parkinson's disease | OR: 1.39 [1.06, 1.84] | AUROC: 0.55 | — | — | Prior to imputation of missing data |
| PPM009234 | PGS001774 (PRS12_PD) |
PSS007662| European Ancestry| 699 individuals |
PGP000254 | Chairta PP et al. Genes (Basel) (2021) |
Reported Trait: Parkinson's disease | — | AUROC: 0.79 [0.75, 0.83] | — | Age, gender, head injury, family history of Parkinson's disease, depression, smoking (current or ever), body mass index | Prior to imputation of missing data |
| PPM009235 | PGS001774 (PRS12_PD) |
PSS007662| European Ancestry| 699 individuals |
PGP000254 | Chairta PP et al. Genes (Basel) (2021) |
Reported Trait: Parkinson's disease | OR: 1.39 [1.06, 1.83] | AUROC: 0.55 | — | — | Following imputation of missing data |
| PPM009236 | PGS001774 (PRS12_PD) |
PSS007662| European Ancestry| 699 individuals |
PGP000254 | Chairta PP et al. Genes (Basel) (2021) |
Reported Trait: Parkinson's disease | — | AUROC: 0.8 [0.77, 0.84] | — | Age, gender, head injury, family history of Parkinson's disease, depression, smoking (current or ever), body mass index | Following imputation of missing data |
| PPM007472 | PGS000929 (GBE_HC1583) |
PSS004302| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD all cause dementia | — | AUROC: 0.87071 [0.81635, 0.92507] | R²: 0.20833 Incremental AUROC (full-covars): 0.0113 PGS R2 (no covariates): 0.01979 PGS AUROC (no covariates): 0.61107 [0.52126, 0.70088] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007473 | PGS000929 (GBE_HC1583) |
PSS004303| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD all cause dementia | — | AUROC: 0.95182 [0.90381, 0.99984] | R²: 0.22288 Incremental AUROC (full-covars): 0.00617 PGS R2 (no covariates): 0.01638 PGS AUROC (no covariates): 0.54656 [0.0, 1.0] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007474 | PGS000929 (GBE_HC1583) |
PSS004304| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD all cause dementia | — | AUROC: 0.81502 [0.78, 0.85005] | R²: 0.12968 Incremental AUROC (full-covars): 0.00636 PGS R2 (no covariates): 0.01492 PGS AUROC (no covariates): 0.59229 [0.54215, 0.64242] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007475 | PGS000929 (GBE_HC1583) |
PSS004305| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD all cause dementia | — | AUROC: 0.82116 [0.74776, 0.89457] | R²: 0.1345 Incremental AUROC (full-covars): 0.00919 PGS R2 (no covariates): 0.02074 PGS AUROC (no covariates): 0.56393 [0.44983, 0.67804] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007476 | PGS000929 (GBE_HC1583) |
PSS004306| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD all cause dementia | — | AUROC: 0.81557 [0.79434, 0.8368] | R²: 0.11649 Incremental AUROC (full-covars): 0.02294 PGS R2 (no covariates): 0.02346 PGS AUROC (no covariates): 0.62703 [0.59629, 0.65777] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007551 | PGS000945 (GBE_HC710) |
PSS004614| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE dementia in alzheimer's disease | — | AUROC: 0.98515 [0.97381, 0.9965] | R²: 0.33632 Incremental AUROC (full-covars): 0.00807 PGS R2 (no covariates): 0.02667 PGS AUROC (no covariates): 0.7414 [0.59579, 0.88702] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007552 | PGS000945 (GBE_HC710) |
PSS004615| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE dementia in alzheimer's disease | — | AUROC: 0.8807 [0.81377, 0.94763] | R²: 0.16889 Incremental AUROC (full-covars): 0.0235 PGS R2 (no covariates): 0.04331 PGS AUROC (no covariates): 0.66609 [0.55451, 0.77766] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007553 | PGS000945 (GBE_HC710) |
PSS004616| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE dementia in alzheimer's disease | — | AUROC: 0.9584 [0.92052, 0.99629] | R²: 0.25982 Incremental AUROC (full-covars): 0.0131 PGS R2 (no covariates): 0.0675 PGS AUROC (no covariates): 0.67849 [0.36185, 0.99513] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007554 | PGS000945 (GBE_HC710) |
PSS004617| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE dementia in alzheimer's disease | — | AUROC: 0.8916 [0.86249, 0.9207] | R²: 0.16679 Incremental AUROC (full-covars): 0.05458 PGS R2 (no covariates): 0.06543 PGS AUROC (no covariates): 0.75273 [0.69847, 0.80699] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007555 | PGS000946 (GBE_HC713) |
PSS004622| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified dementia | — | AUROC: 0.82014 [0.73087, 0.90941] | R²: 0.13536 Incremental AUROC (full-covars): 0.02407 PGS R2 (no covariates): 0.01431 PGS AUROC (no covariates): 0.57071 [0.42666, 0.71476] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007556 | PGS000946 (GBE_HC713) |
PSS004624| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified dementia | — | AUROC: 0.82275 [0.77979, 0.86571] | R²: 0.12092 Incremental AUROC (full-covars): 0.00342 PGS R2 (no covariates): 0.00838 PGS AUROC (no covariates): 0.57672 [0.50856, 0.64487] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007557 | PGS000946 (GBE_HC713) |
PSS004625| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified dementia | — | AUROC: 0.90804 [0.86257, 0.9535] | R²: 0.20027 Incremental AUROC (full-covars): 0.0061 PGS R2 (no covariates): 0.0151 PGS AUROC (no covariates): 0.56115 [0.41165, 0.71066] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007558 | PGS000946 (GBE_HC713) |
PSS004626| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified dementia | — | AUROC: 0.83545 [0.80839, 0.8625] | R²: 0.11896 Incremental AUROC (full-covars): 0.02339 PGS R2 (no covariates): 0.02543 PGS AUROC (no covariates): 0.64149 [0.59989, 0.68308] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007718 | PGS000990 (GBE_HC878) |
PSS004682| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal detachments and breaks | — | AUROC: 0.61927 [0.54935, 0.68918] | R²: 0.0247 Incremental AUROC (full-covars): -0.01882 PGS R2 (no covariates): 0.00198 PGS AUROC (no covariates): 0.46633 [0.38893, 0.54373] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007719 | PGS000990 (GBE_HC878) |
PSS004683| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal detachments and breaks | — | AUROC: 0.75788 [0.63933, 0.87643] | R²: 0.10693 Incremental AUROC (full-covars): 0.0196 PGS R2 (no covariates): 0.01417 PGS AUROC (no covariates): 0.5954 [0.44975, 0.74105] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007720 | PGS000990 (GBE_HC878) |
PSS004684| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal detachments and breaks | — | AUROC: 0.64308 [0.61279, 0.67337] | R²: 0.02565 Incremental AUROC (full-covars): 0.00606 PGS R2 (no covariates): 0.00213 PGS AUROC (no covariates): 0.54152 [0.50847, 0.57457] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007721 | PGS000990 (GBE_HC878) |
PSS004685| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal detachments and breaks | — | AUROC: 0.71433 [0.66221, 0.76646] | R²: 0.05371 Incremental AUROC (full-covars): 0.0098 PGS R2 (no covariates): 0.00492 PGS AUROC (no covariates): 0.56225 [0.49739, 0.62711] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007722 | PGS000990 (GBE_HC878) |
PSS004686| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal detachments and breaks | — | AUROC: 0.63532 [0.61784, 0.65279] | R²: 0.02226 Incremental AUROC (full-covars): 0.00479 PGS R2 (no covariates): 0.00207 PGS AUROC (no covariates): 0.53945 [0.52027, 0.55863] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007828 | PGS001013 (GBE_BIN_FC5006148) |
PSS003974| African Ancestry| 3,196 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eye problems/disorders Macular degeneration | — | AUROC: 0.7052 [0.63504, 0.77537] | R²: 0.07369 Incremental AUROC (full-covars): -0.00271 PGS R2 (no covariates): 6e-05 PGS AUROC (no covariates): 0.50582 [0.43466, 0.57699] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007829 | PGS001013 (GBE_BIN_FC5006148) |
PSS003975| East Asian Ancestry| 711 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eye problems/disorders Macular degeneration | — | AUROC: 0.90123 [0.8354, 0.96707] | R²: 0.32752 Incremental AUROC (full-covars): -0.00016 PGS R2 (no covariates): 0.01068 PGS AUROC (no covariates): 0.59339 [0.45683, 0.72996] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007830 | PGS001013 (GBE_BIN_FC5006148) |
PSS003976| European Ancestry| 9,755 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eye problems/disorders Macular degeneration | — | AUROC: 0.72878 [0.69745, 0.76011] | R²: 0.07729 Incremental AUROC (full-covars): 0.00516 PGS R2 (no covariates): 0.00265 PGS AUROC (no covariates): 0.53845 [0.49847, 0.57843] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007831 | PGS001013 (GBE_BIN_FC5006148) |
PSS003977| South Asian Ancestry| 3,327 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eye problems/disorders Macular degeneration | — | AUROC: 0.76624 [0.71098, 0.8215] | R²: 0.10324 Incremental AUROC (full-covars): -0.00396 PGS R2 (no covariates): 0.00053 PGS AUROC (no covariates): 0.47169 [0.39626, 0.54712] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007832 | PGS001013 (GBE_BIN_FC5006148) |
PSS003978| European Ancestry| 22,208 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eye problems/disorders Macular degeneration | — | AUROC: 0.70257 [0.6826, 0.72253] | R²: 0.06704 Incremental AUROC (full-covars): 0.00573 PGS R2 (no covariates): 0.00599 PGS AUROC (no covariates): 0.55283 [0.52939, 0.57627] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008412 | PGS001137 (GBE_HC302) |
PSS004418| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Retinal detachment | — | AUROC: 0.65217 [0.57926, 0.72508] | R²: 0.03407 Incremental AUROC (full-covars): -0.00918 PGS R2 (no covariates): 1e-05 PGS AUROC (no covariates): 0.49921 [0.41839, 0.58004] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008413 | PGS001137 (GBE_HC302) |
PSS004419| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Retinal detachment | — | AUROC: 0.7872 [0.68424, 0.89016] | R²: 0.13209 Incremental AUROC (full-covars): 0.01471 PGS R2 (no covariates): 0.00931 PGS AUROC (no covariates): 0.57064 [0.39309, 0.74819] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008414 | PGS001137 (GBE_HC302) |
PSS004420| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Retinal detachment | — | AUROC: 0.65311 [0.62153, 0.68468] | R²: 0.02791 Incremental AUROC (full-covars): 0.01854 PGS R2 (no covariates): 0.00663 PGS AUROC (no covariates): 0.57317 [0.53771, 0.60862] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008415 | PGS001137 (GBE_HC302) |
PSS004421| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Retinal detachment | — | AUROC: 0.73537 [0.67789, 0.79285] | R²: 0.0635 Incremental AUROC (full-covars): 0.01358 PGS R2 (no covariates): 0.00738 PGS AUROC (no covariates): 0.55915 [0.48569, 0.63261] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008416 | PGS001137 (GBE_HC302) |
PSS004422| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Retinal detachment | — | AUROC: 0.63847 [0.61945, 0.65749] | R²: 0.02286 Incremental AUROC (full-covars): 0.00912 PGS R2 (no covariates): 0.00357 PGS AUROC (no covariates): 0.55079 [0.52979, 0.57179] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008585 | PGS001179 (GBE_HC711) |
PSS004618| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.89609 [0.78011, 1.0] | R²: 0.23133 Incremental AUROC (full-covars): -0.00271 PGS R2 (no covariates): 0.00098 PGS AUROC (no covariates): 0.45314 [0.26337, 0.6429] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008586 | PGS001179 (GBE_HC711) |
PSS004619| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.86436 [0.80883, 0.91989] | R²: 0.14328 Incremental AUROC (full-covars): 0.00289 PGS R2 (no covariates): 0.00776 PGS AUROC (no covariates): 0.59245 [0.49395, 0.69095] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008587 | PGS001179 (GBE_HC711) |
PSS004620| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.83842 [0.72824, 0.9486] | R²: 0.14604 Incremental AUROC (full-covars): 0.00843 PGS R2 (no covariates): 0.0135 PGS AUROC (no covariates): 0.61894 [0.47358, 0.76431] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008588 | PGS001179 (GBE_HC711) |
PSS004621| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.82562 [0.78593, 0.86531] | R²: 0.10475 Incremental AUROC (full-covars): 0.00707 PGS R2 (no covariates): 0.01123 PGS AUROC (no covariates): 0.61306 [0.55366, 0.67245] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009528 | PGS001829 (portability-PLR_296.2) |
PSS008401| Greater Middle Eastern Ancestry| 1,055 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0527 [-0.0082, 0.1133] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM008769 | PGS001252 (GBE_BIN_FC3002247) |
PSS003899| African Ancestry| 6,123 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty and Deafness | — | AUROC: 0.58635 [0.56411, 0.60859] | R²: 0.01752 Incremental AUROC (full-covars): -0.00041 PGS R2 (no covariates): 0.00138 PGS AUROC (no covariates): 0.52307 [0.50054, 0.54561] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008770 | PGS001252 (GBE_BIN_FC3002247) |
PSS003900| East Asian Ancestry| 1,568 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty and Deafness | — | AUROC: 0.62777 [0.58865, 0.66688] | R²: 0.04973 Incremental AUROC (full-covars): 0.00284 PGS R2 (no covariates): 0.00305 PGS AUROC (no covariates): 0.53516 [0.49316, 0.57716] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008771 | PGS001252 (GBE_BIN_FC3002247) |
PSS003901| European Ancestry| 23,697 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty and Deafness | — | AUROC: 0.62252 [0.61446, 0.63058] | R²: 0.05132 Incremental AUROC (full-covars): 0.00531 PGS R2 (no covariates): 0.00527 PGS AUROC (no covariates): 0.53867 [0.53034, 0.54699] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008772 | PGS001252 (GBE_BIN_FC3002247) |
PSS003902| South Asian Ancestry| 7,266 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty and Deafness | — | AUROC: 0.61586 [0.5994, 0.63232] | R²: 0.04282 Incremental AUROC (full-covars): 0.00304 PGS R2 (no covariates): 0.00345 PGS AUROC (no covariates): 0.53204 [0.5154, 0.54867] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008773 | PGS001252 (GBE_BIN_FC3002247) |
PSS003903| European Ancestry| 65,065 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty and Deafness | — | AUROC: 0.62548 [0.62074, 0.63023] | R²: 0.05558 Incremental AUROC (full-covars): 0.00728 PGS R2 (no covariates): 0.00646 PGS AUROC (no covariates): 0.54216 [0.53723, 0.54709] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008774 | PGS001253 (GBE_BIN_FC1002247) |
PSS003755| African Ancestry| 6,121 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty | — | AUROC: 0.58714 [0.56491, 0.60938] | R²: 0.01786 Incremental AUROC (full-covars): 0.00082 PGS R2 (no covariates): 0.00162 PGS AUROC (no covariates): 0.52504 [0.50255, 0.54753] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008775 | PGS001253 (GBE_BIN_FC1002247) |
PSS003756| East Asian Ancestry| 1,568 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty | — | AUROC: 0.62831 [0.58912, 0.6675] | R²: 0.04992 Incremental AUROC (full-covars): 0.00338 PGS R2 (no covariates): 0.003 PGS AUROC (no covariates): 0.53605 [0.49383, 0.57827] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008776 | PGS001253 (GBE_BIN_FC1002247) |
PSS003757| European Ancestry| 23,689 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty | — | AUROC: 0.62276 [0.6147, 0.63082] | R²: 0.0516 Incremental AUROC (full-covars): 0.00532 PGS R2 (no covariates): 0.00515 PGS AUROC (no covariates): 0.53825 [0.52992, 0.54658] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008777 | PGS001253 (GBE_BIN_FC1002247) |
PSS003758| South Asian Ancestry| 7,257 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty | — | AUROC: 0.61668 [0.60019, 0.63317] | R²: 0.04334 Incremental AUROC (full-covars): 0.00291 PGS R2 (no covariates): 0.00324 PGS AUROC (no covariates): 0.53126 [0.51459, 0.54793] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009529 | PGS001829 (portability-PLR_296.2) |
PSS008181| South Asian Ancestry| 5,870 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): -0.0051 [-0.0307, 0.0205] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM008778 | PGS001253 (GBE_BIN_FC1002247) |
PSS003759| European Ancestry| 65,054 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hearing difficulty | — | AUROC: 0.62552 [0.62077, 0.63026] | R²: 0.05561 Incremental AUROC (full-covars): 0.00726 PGS R2 (no covariates): 0.00632 PGS AUROC (no covariates): 0.54175 [0.53682, 0.54668] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008850 | PGS001270 (GBE_HC151) |
PSS004273| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.78603 [0.68344, 0.88862] | R²: 0.07124 Incremental AUROC (full-covars): -0.04449 PGS R2 (no covariates): 0.02639 PGS AUROC (no covariates): 0.35945 [0.2174, 0.5015] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008851 | PGS001270 (GBE_HC151) |
PSS004274| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.65766 [0.60651, 0.7088] | R²: 0.02306 Incremental AUROC (full-covars): 0.0559 PGS R2 (no covariates): 0.01225 PGS AUROC (no covariates): 0.61627 [0.56233, 0.67022] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008852 | PGS001270 (GBE_HC151) |
PSS004275| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.9739 [0.9358, 1.0] | R²: 0.3229 Incremental AUROC (full-covars): 0.01955 PGS R2 (no covariates): 0.02901 PGS AUROC (no covariates): 0.64875 [0.24603, 1.0] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008853 | PGS001270 (GBE_HC151) |
PSS004276| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.69658 [0.66502, 0.72814] | R²: 0.04105 Incremental AUROC (full-covars): 0.08355 PGS R2 (no covariates): 0.02904 PGS AUROC (no covariates): 0.65856 [0.62428, 0.69284] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008854 | PGS001271 (GBE_HC810) |
PSS004637| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.8033 [0.6935, 0.91311] | PGS R2 (no covariates): 0.01095 R²: 0.10788 Incremental AUROC (full-covars): -0.03509 PGS AUROC (no covariates): 0.39974 [0.23738, 0.56211] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008855 | PGS001271 (GBE_HC810) |
PSS004639| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.65561 [0.60622, 0.705] | R²: 0.02347 Incremental AUROC (full-covars): 0.05454 PGS R2 (no covariates): 0.01258 PGS AUROC (no covariates): 0.61601 [0.56326, 0.66875] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009371 | PGS001808 (portability-PLR_191.11) |
PSS007947| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0004 [-0.0461, 0.0468] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM008856 | PGS001271 (GBE_HC810) |
PSS004640| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.97595 [0.94159, 1.0] | R²: 0.33555 Incremental AUROC (full-covars): 0.01648 PGS R2 (no covariates): 0.01091 PGS AUROC (no covariates): 0.55629 [0.19512, 0.91745] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008857 | PGS001271 (GBE_HC810) |
PSS004641| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.6895 [0.65926, 0.71974] | R²: 0.03906 Incremental AUROC (full-covars): 0.07145 PGS R2 (no covariates): 0.02562 PGS AUROC (no covariates): 0.64688 [0.61364, 0.68013] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008873 | PGS001275 (GBE_HC880) |
PSS004687| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other retinal disorders | — | AUROC: 0.70701 [0.6592, 0.75482] | R²: 0.06654 Incremental AUROC (full-covars): -0.00077 PGS R2 (no covariates): 0.00011 PGS AUROC (no covariates): 0.50886 [0.45807, 0.55965] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008874 | PGS001275 (GBE_HC880) |
PSS004688| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other retinal disorders | — | AUROC: 0.76408 [0.70187, 0.8263] | R²: 0.11034 Incremental AUROC (full-covars): 0.00238 PGS R2 (no covariates): 0.00124 PGS AUROC (no covariates): 0.54196 [0.45417, 0.62976] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008875 | PGS001275 (GBE_HC880) |
PSS004689| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other retinal disorders | — | AUROC: 0.68838 [0.66508, 0.71167] | R²: 0.04946 Incremental AUROC (full-covars): 0.00295 PGS R2 (no covariates): 0.00217 PGS AUROC (no covariates): 0.53609 [0.50994, 0.56223] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008876 | PGS001275 (GBE_HC880) |
PSS004690| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other retinal disorders | — | AUROC: 0.73994 [0.71282, 0.76707] | R²: 0.09449 Incremental AUROC (full-covars): 0.00101 PGS R2 (no covariates): 0.00053 PGS AUROC (no covariates): 0.51345 [0.47882, 0.54808] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008877 | PGS001275 (GBE_HC880) |
PSS004691| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other retinal disorders | — | AUROC: 0.67575 [0.6628, 0.6887] | R²: 0.04416 Incremental AUROC (full-covars): 0.00229 PGS R2 (no covariates): 0.00203 PGS AUROC (no covariates): 0.53038 [0.51532, 0.54545] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008878 | PGS001276 (GBE_HC881) |
PSS004692| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal disorders in diseases classified elsewhere | — | AUROC: 0.69535 [0.65164, 0.73906] | R²: 0.04898 Incremental AUROC (full-covars): -0.01537 PGS R2 (no covariates): 0.00048 PGS AUROC (no covariates): 0.47863 [0.42888, 0.52839] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008879 | PGS001276 (GBE_HC881) |
PSS004693| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal disorders in diseases classified elsewhere | — | AUROC: 0.78112 [0.63575, 0.92649] | R²: 0.09795 Incremental AUROC (full-covars): -0.03107 PGS R2 (no covariates): 0.00124 PGS AUROC (no covariates): 0.45159 [0.20305, 0.70013] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008880 | PGS001276 (GBE_HC881) |
PSS004694| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal disorders in diseases classified elsewhere | — | AUROC: 0.70588 [0.66187, 0.7499] | R²: 0.04864 Incremental AUROC (full-covars): 0.02939 PGS R2 (no covariates): 0.01461 PGS AUROC (no covariates): 0.60872 [0.55828, 0.65917] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008881 | PGS001276 (GBE_HC881) |
PSS004695| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal disorders in diseases classified elsewhere | — | AUROC: 0.73414 [0.70226, 0.76602] | R²: 0.08369 Incremental AUROC (full-covars): -7e-05 PGS R2 (no covariates): 0.00183 PGS AUROC (no covariates): 0.53682 [0.49711, 0.57653] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008882 | PGS001276 (GBE_HC881) |
PSS004696| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE retinal disorders in diseases classified elsewhere | — | AUROC: 0.67399 [0.64743, 0.70056] | R²: 0.03213 Incremental AUROC (full-covars): 0.02207 PGS R2 (no covariates): 0.00817 PGS AUROC (no covariates): 0.57664 [0.54625, 0.60704] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008903 | PGS001281 (GBE_HC86) |
PSS004672| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.68314 [0.64175, 0.72454] | R²: 0.04548 Incremental AUROC (full-covars): 0.00141 PGS R2 (no covariates): 7e-05 PGS AUROC (no covariates): 0.51212 [0.4664, 0.55784] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008904 | PGS001281 (GBE_HC86) |
PSS004673| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.70929 [0.59332, 0.82526] | Incremental AUROC (full-covars): 0.00197 R²: 0.0907 PGS R2 (no covariates): 0.00054 PGS AUROC (no covariates): 0.51635 [0.40666, 0.62605] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008905 | PGS001281 (GBE_HC86) |
PSS004674| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.65031 [0.63271, 0.66791] | R²: 0.03585 Incremental AUROC (full-covars): 0.00524 PGS R2 (no covariates): 0.00376 PGS AUROC (no covariates): 0.54846 [0.52849, 0.56843] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008906 | PGS001281 (GBE_HC86) |
PSS004675| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.71746 [0.68326, 0.75166] | R²: 0.07262 Incremental AUROC (full-covars): 0.00414 PGS R2 (no covariates): 0.0051 PGS AUROC (no covariates): 0.55594 [0.51785, 0.59403] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008907 | PGS001281 (GBE_HC86) |
PSS004676| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.6514 [0.64118, 0.66162] | R²: 0.03715 Incremental AUROC (full-covars): 0.00474 PGS R2 (no covariates): 0.0025 PGS AUROC (no covariates): 0.53959 [0.52853, 0.55066] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008908 | PGS001282 (GBE_HC815) |
PSS004642| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.68512 [0.64613, 0.72411] | PGS R2 (no covariates): 0.00032 R²: 0.04881 Incremental AUROC (full-covars): 0.00144 PGS AUROC (no covariates): 0.5084 [0.46412, 0.55269] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008909 | PGS001282 (GBE_HC815) |
PSS004643| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.71233 [0.61741, 0.80724] | R²: 0.08258 Incremental AUROC (full-covars): 0.00023 PGS R2 (no covariates): 3e-05 PGS AUROC (no covariates): 0.49923 [0.40691, 0.59154] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008910 | PGS001282 (GBE_HC815) |
PSS004644| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.63835 [0.62244, 0.65426] | R²: 0.03299 Incremental AUROC (full-covars): 0.00984 PGS R2 (no covariates): 0.00527 PGS AUROC (no covariates): 0.55358 [0.53641, 0.57074] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008911 | PGS001282 (GBE_HC815) |
PSS004645| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.71231 [0.68018, 0.74443] | R²: 0.07365 Incremental AUROC (full-covars): 0.00305 PGS R2 (no covariates): 0.00344 PGS AUROC (no covariates): 0.54217 [0.50698, 0.57735] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008912 | PGS001282 (GBE_HC815) |
PSS004646| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.64859 [0.63934, 0.65784] | R²: 0.03899 Incremental AUROC (full-covars): 0.00619 PGS R2 (no covariates): 0.0031 PGS AUROC (no covariates): 0.5408 [0.53085, 0.55076] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009531 | PGS001829 (portability-PLR_296.2) |
PSS007747| African Ancestry| 2,272 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): -0.0294 [-0.0706, 0.0119] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009532 | PGS001829 (portability-PLR_296.2) |
PSS008851| African Ancestry| 3,678 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0034 [-0.029, 0.0358] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009221 | PGS001348 (GBE_HC1584) |
PSS004307| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD alzheimer's disease | — | AUROC: 0.96694 [0.94819, 0.98568] | R²: 0.31464 Incremental AUROC (full-covars): 0.01598 PGS R2 (no covariates): 0.04322 PGS AUROC (no covariates): 0.69389 [0.49462, 0.89316] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009222 | PGS001348 (GBE_HC1584) |
PSS004309| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD alzheimer's disease | — | AUROC: 0.8626 [0.81314, 0.91206] | R²: 0.15552 Incremental AUROC (full-covars): 0.03113 PGS R2 (no covariates): 0.05179 PGS AUROC (no covariates): 0.66389 [0.57085, 0.75693] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009223 | PGS001348 (GBE_HC1584) |
PSS004310| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD alzheimer's disease | — | AUROC: 0.91522 [0.82612, 1.0] | R²: 0.23563 Incremental AUROC (full-covars): 0.0091 PGS R2 (no covariates): 0.01731 PGS AUROC (no covariates): 0.59348 [0.39906, 0.7879] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009224 | PGS001348 (GBE_HC1584) |
PSS004311| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD alzheimer's disease | — | AUROC: 0.8686 [0.84242, 0.89478] | R²: 0.1517 Incremental AUROC (full-covars): 0.05292 PGS R2 (no covariates): 0.05685 PGS AUROC (no covariates): 0.72349 [0.67813, 0.76886] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009225 | PGS001349 (GBE_HC807) |
PSS004632| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE alzheimer's disease | — | AUROC: 0.96248 [0.93046, 0.9945] | R²: 0.31063 Incremental AUROC (full-covars): 0.00757 PGS R2 (no covariates): 0.03204 PGS AUROC (no covariates): 0.63583 [0.42385, 0.84781] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009226 | PGS001349 (GBE_HC807) |
PSS004634| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE alzheimer's disease | — | AUROC: 0.86841 [0.82079, 0.91602] | R²: 0.16057 Incremental AUROC (full-covars): 0.03323 PGS R2 (no covariates): 0.05188 PGS AUROC (no covariates): 0.67961 [0.58969, 0.76952] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009227 | PGS001349 (GBE_HC807) |
PSS004635| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE alzheimer's disease | — | AUROC: 0.9136 [0.8364, 0.9908] | R²: 0.24293 Incremental AUROC (full-covars): 0.00891 PGS R2 (no covariates): 0.01019 PGS AUROC (no covariates): 0.53145 [0.34417, 0.71873] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009228 | PGS001349 (GBE_HC807) |
PSS004636| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE alzheimer's disease | — | AUROC: 0.8666 [0.84246, 0.89075] | R²: 0.15418 Incremental AUROC (full-covars): 0.04665 PGS R2 (no covariates): 0.05271 PGS AUROC (no covariates): 0.71238 [0.66844, 0.75632] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009367 | PGS001808 (portability-PLR_191.11) |
PSS009278| European Ancestry| 19,895 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0144 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009368 | PGS001808 (portability-PLR_191.11) |
PSS009052| European Ancestry| 4,114 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0179 [-0.0128, 0.0485] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009369 | PGS001808 (portability-PLR_191.11) |
PSS008606| European Ancestry| 6,626 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0237 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009370 | PGS001808 (portability-PLR_191.11) |
PSS008160| South Asian Ancestry| 6,310 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0098 [-0.0149, 0.0345] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009372 | PGS001808 (portability-PLR_191.11) |
PSS007729| African Ancestry| 2,477 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0217 [-0.0179, 0.0612] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009373 | PGS001808 (portability-PLR_191.11) |
PSS008832| African Ancestry| 3,913 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cancer of brain | — | — | Partial Correlation (partial-r): 0.0343 [0.0029, 0.0657] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009452 | PGS001819 (portability-PLR_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0366 [0.0226, 0.0507] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009453 | PGS001819 (portability-PLR_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0638 [0.033, 0.0946] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009454 | PGS001819 (portability-PLR_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0315 [0.0071, 0.0559] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009455 | PGS001819 (portability-PLR_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0471 [-0.1048, 0.011] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009456 | PGS001819 (portability-PLR_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0325 [0.0074, 0.0577] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009457 | PGS001819 (portability-PLR_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0249 [-0.0718, 0.022] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009509 | PGS001827 (portability-PLR_290.1) |
PSS009297| European Ancestry| 19,618 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0455 [0.0315, 0.0595] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009510 | PGS001827 (portability-PLR_290.1) |
PSS009071| European Ancestry| 4,070 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.025 [-0.0058, 0.0558] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009511 | PGS001827 (portability-PLR_290.1) |
PSS008625| European Ancestry| 6,562 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0324 [0.0081, 0.0565] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009512 | PGS001827 (portability-PLR_290.1) |
PSS008399| Greater Middle Eastern Ancestry| 1,186 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0695 [0.0122, 0.1264] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009513 | PGS001827 (portability-PLR_290.1) |
PSS008179| South Asian Ancestry| 6,222 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.046 [0.0211, 0.0708] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009514 | PGS001827 (portability-PLR_290.1) |
PSS007964| East Asian Ancestry| 1,802 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0477 [0.0013, 0.094] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009515 | PGS001827 (portability-PLR_290.1) |
PSS007745| African Ancestry| 2,441 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0445 [0.0047, 0.0842] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009516 | PGS001827 (portability-PLR_290.1) |
PSS008849| African Ancestry| 3,852 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0522 [0.0206, 0.0837] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009517 | PGS001828 (portability-PLR_290.11) |
PSS009298| European Ancestry| 19,563 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0482 [0.0342, 0.0622] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009519 | PGS001828 (portability-PLR_290.11) |
PSS008626| European Ancestry| 6,544 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0354 [0.0111, 0.0596] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009520 | PGS001828 (portability-PLR_290.11) |
PSS008400| Greater Middle Eastern Ancestry| 1,183 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0684 [0.011, 0.1254] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009521 | PGS001828 (portability-PLR_290.11) |
PSS008180| South Asian Ancestry| 6,205 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0283 [0.0034, 0.0532] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009522 | PGS001828 (portability-PLR_290.11) |
PSS007965| East Asian Ancestry| 1,802 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.045 [-0.0015, 0.0912] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009523 | PGS001828 (portability-PLR_290.11) |
PSS007746| African Ancestry| 2,429 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0414 [0.0015, 0.0812] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009524 | PGS001828 (portability-PLR_290.11) |
PSS008850| African Ancestry| 3,836 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): 0.0338 [0.002, 0.0654] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009525 | PGS001829 (portability-PLR_296.2) |
PSS009299| European Ancestry| 17,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0323 [0.0176, 0.047] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009526 | PGS001829 (portability-PLR_296.2) |
PSS009073| European Ancestry| 3,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0074 [-0.0248, 0.0396] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009527 | PGS001829 (portability-PLR_296.2) |
PSS008627| European Ancestry| 5,989 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.027 [0.0017, 0.0524] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009541 | PGS001831 (portability-PLR_335) |
PSS009301| European Ancestry| 19,299 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0367 [0.0226, 0.0508] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009542 | PGS001831 (portability-PLR_335) |
PSS009075| European Ancestry| 4,011 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0122 [-0.0188, 0.0432] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009543 | PGS001831 (portability-PLR_335) |
PSS008629| European Ancestry| 6,463 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0578 [0.0334, 0.0821] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009544 | PGS001831 (portability-PLR_335) |
PSS008403| Greater Middle Eastern Ancestry| 1,164 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0242 [-0.0338, 0.082] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009545 | PGS001831 (portability-PLR_335) |
PSS008183| South Asian Ancestry| 6,094 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0064 [-0.0188, 0.0315] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009546 | PGS001831 (portability-PLR_335) |
PSS007749| African Ancestry| 2,390 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0032 [-0.037, 0.0435] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009547 | PGS001831 (portability-PLR_335) |
PSS008853| African Ancestry| 3,790 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): -0.0104 [-0.0423, 0.0216] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009548 | PGS001832 (portability-PLR_351) |
PSS009302| European Ancestry| 19,840 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0393 [0.0253, 0.0531] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009549 | PGS001832 (portability-PLR_351) |
PSS009076| European Ancestry| 4,112 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0324 [0.0018, 0.063] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009550 | PGS001832 (portability-PLR_351) |
PSS008630| European Ancestry| 6,611 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0341 [0.0099, 0.0582] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009552 | PGS001832 (portability-PLR_351) |
PSS008184| South Asian Ancestry| 6,277 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0367 [0.0119, 0.0614] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009553 | PGS001832 (portability-PLR_351) |
PSS007968| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0055 [-0.041, 0.0519] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009554 | PGS001832 (portability-PLR_351) |
PSS007750| African Ancestry| 2,471 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): -0.0227 [-0.0623, 0.0169] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009555 | PGS001832 (portability-PLR_351) |
PSS008854| African Ancestry| 3,898 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): -0.0063 [-0.0378, 0.0252] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009556 | PGS001833 (portability-PLR_361) |
PSS009303| European Ancestry| 19,445 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0218 [0.0078, 0.0359] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009557 | PGS001833 (portability-PLR_361) |
PSS009077| European Ancestry| 4,055 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0304 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009558 | PGS001833 (portability-PLR_361) |
PSS008631| European Ancestry| 6,514 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0086 [-0.0157, 0.0329] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009559 | PGS001833 (portability-PLR_361) |
PSS008405| Greater Middle Eastern Ancestry| 1,169 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): -0.0283 [-0.086, 0.0296] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009560 | PGS001833 (portability-PLR_361) |
PSS008185| South Asian Ancestry| 6,095 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0155 [-0.0096, 0.0406] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009561 | PGS001833 (portability-PLR_361) |
PSS007969| East Asian Ancestry| 1,773 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0326 [-0.0142, 0.0793] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009562 | PGS001833 (portability-PLR_361) |
PSS007751| African Ancestry| 2,384 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0172 [-0.0231, 0.0575] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009563 | PGS001833 (portability-PLR_361) |
PSS008855| African Ancestry| 3,743 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.012 [-0.0201, 0.0441] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009565 | PGS001834 (portability-PLR_362.29) |
PSS009078| European Ancestry| 4,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0258 [-0.0051, 0.0567] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009566 | PGS001834 (portability-PLR_362.29) |
PSS008632| European Ancestry| 6,470 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0177 [-0.0067, 0.0421] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009567 | PGS001834 (portability-PLR_362.29) |
PSS008406| Greater Middle Eastern Ancestry| 1,165 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): -0.03 [-0.0877, 0.028] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009568 | PGS001834 (portability-PLR_362.29) |
PSS008186| South Asian Ancestry| 6,037 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0368 [0.0116, 0.062] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009569 | PGS001834 (portability-PLR_362.29) |
PSS007970| East Asian Ancestry| 1,775 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): -0.0304 [-0.0771, 0.0164] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009570 | PGS001834 (portability-PLR_362.29) |
PSS007752| African Ancestry| 2,374 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0015 [-0.0389, 0.0419] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009571 | PGS001834 (portability-PLR_362.29) |
PSS008856| African Ancestry| 3,723 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0144 [-0.0178, 0.0466] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010013 | PGS001891 (portability-PLR_bad_hearing) |
PSS009161| European Ancestry| 3,907 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0758 [0.0445, 0.107] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010014 | PGS001891 (portability-PLR_bad_hearing) |
PSS008715| European Ancestry| 6,265 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0537 [0.0289, 0.0784] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010015 | PGS001891 (portability-PLR_bad_hearing) |
PSS008489| Greater Middle Eastern Ancestry| 1,089 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0251 [-0.0349, 0.0849] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010016 | PGS001891 (portability-PLR_bad_hearing) |
PSS008267| South Asian Ancestry| 5,858 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0738 [0.0482, 0.0993] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010017 | PGS001891 (portability-PLR_bad_hearing) |
PSS008045| East Asian Ancestry| 1,684 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0734 [0.0254, 0.121] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010018 | PGS001891 (portability-PLR_bad_hearing) |
PSS007831| African Ancestry| 2,325 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0133 [-0.0275, 0.0541] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010019 | PGS001891 (portability-PLR_bad_hearing) |
PSS008935| African Ancestry| 3,691 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.011 [-0.0213, 0.0434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010299 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS009415| European Ancestry| 3,905 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0537 [0.0223, 0.0851] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010300 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS009189| European Ancestry| 1,095 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0316 [-0.0282, 0.0912] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010301 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS008743| European Ancestry| 1,537 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0245 [-0.0259, 0.0747] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010302 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS008517| Greater Middle Eastern Ancestry| 363 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): -0.0025 [-0.1084, 0.1034] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010303 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS008295| South Asian Ancestry| 1,716 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0294 [-0.0182, 0.0769] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010304 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS008072| East Asian Ancestry| 390 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): -0.1007 [-0.2005, 0.0013] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010305 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS007859| African Ancestry| 570 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0752 [-0.0084, 0.1578] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010306 | PGS001928 (portability-PLR_headaches_for_3m) |
PSS008963| African Ancestry| 1,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0294 [-0.0319, 0.0905] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010331 | PGS001932 (portability-PLR_insomnia) |
PSS009419| European Ancestry| 19,978 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1248 [0.1111, 0.1384] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010332 | PGS001932 (portability-PLR_insomnia) |
PSS009193| European Ancestry| 4,116 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1003 [0.0699, 0.1305] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010333 | PGS001932 (portability-PLR_insomnia) |
PSS008747| European Ancestry| 6,626 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1093 [0.0854, 0.133] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010334 | PGS001932 (portability-PLR_insomnia) |
PSS008521| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0776 [0.0195, 0.1353] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010335 | PGS001932 (portability-PLR_insomnia) |
PSS008299| South Asian Ancestry| 6,199 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0768 [0.052, 0.1015] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010337 | PGS001932 (portability-PLR_insomnia) |
PSS007863| African Ancestry| 2,460 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0475 [0.0078, 0.087] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010338 | PGS001932 (portability-PLR_insomnia) |
PSS008967| African Ancestry| 3,863 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.033 [0.0013, 0.0645] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012014 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS008963| African Ancestry| 1,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.069 [0.0077, 0.1297] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011090 | PGS002027 (portability-ldpred2_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0451 [0.031, 0.0592] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011091 | PGS002027 (portability-ldpred2_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0607 [0.0298, 0.0915] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011092 | PGS002027 (portability-ldpred2_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0241 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011093 | PGS002027 (portability-ldpred2_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0311 [-0.0889, 0.027] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011094 | PGS002027 (portability-ldpred2_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0351 [0.01, 0.0603] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011095 | PGS002027 (portability-ldpred2_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0302 [-0.077, 0.0168] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011096 | PGS002027 (portability-ldpred2_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0204 [-0.0606, 0.0199] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011147 | PGS002035 (portability-ldpred2_290.1) |
PSS009297| European Ancestry| 19,618 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0425 [0.0285, 0.0564] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011148 | PGS002035 (portability-ldpred2_290.1) |
PSS009071| European Ancestry| 4,070 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0206 [-0.0102, 0.0513] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011149 | PGS002035 (portability-ldpred2_290.1) |
PSS008625| European Ancestry| 6,562 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0343 [0.0101, 0.0585] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011150 | PGS002035 (portability-ldpred2_290.1) |
PSS008399| Greater Middle Eastern Ancestry| 1,186 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0658 [0.0084, 0.1227] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011151 | PGS002035 (portability-ldpred2_290.1) |
PSS008179| South Asian Ancestry| 6,222 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0453 [0.0205, 0.0701] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011152 | PGS002035 (portability-ldpred2_290.1) |
PSS007964| East Asian Ancestry| 1,802 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.0494 [0.003, 0.0956] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011153 | PGS002035 (portability-ldpred2_290.1) |
PSS007745| African Ancestry| 2,441 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.044 [0.0042, 0.0837] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011154 | PGS002035 (portability-ldpred2_290.1) |
PSS008849| African Ancestry| 3,852 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Dementias | — | — | Partial Correlation (partial-r): 0.04 [0.0083, 0.0715] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011155 | PGS002036 (portability-ldpred2_296.2) |
PSS009299| European Ancestry| 17,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0556 [0.041, 0.0703] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011156 | PGS002036 (portability-ldpred2_296.2) |
PSS009073| European Ancestry| 3,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0583 [0.0261, 0.0903] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011158 | PGS002036 (portability-ldpred2_296.2) |
PSS008401| Greater Middle Eastern Ancestry| 1,055 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0239 [-0.0371, 0.0847] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011159 | PGS002036 (portability-ldpred2_296.2) |
PSS008181| South Asian Ancestry| 5,870 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0224 [-0.0033, 0.048] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011160 | PGS002036 (portability-ldpred2_296.2) |
PSS007966| East Asian Ancestry| 1,742 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0549 [0.0077, 0.1019] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011161 | PGS002036 (portability-ldpred2_296.2) |
PSS007747| African Ancestry| 2,272 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0029 [-0.0384, 0.0442] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011162 | PGS002036 (portability-ldpred2_296.2) |
PSS008851| African Ancestry| 3,678 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0178 [-0.0147, 0.0501] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012040 | PGS002149 (portability-ldpred2_insomnia) |
PSS009193| European Ancestry| 4,116 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1208 [0.0905, 0.1508] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011172 | PGS002038 (portability-ldpred2_335) |
PSS009075| European Ancestry| 4,011 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0083 [-0.0228, 0.0393] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011173 | PGS002038 (portability-ldpred2_335) |
PSS008629| European Ancestry| 6,463 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0447 [0.0203, 0.069] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011174 | PGS002038 (portability-ldpred2_335) |
PSS008403| Greater Middle Eastern Ancestry| 1,164 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0296 [-0.0284, 0.0874] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011175 | PGS002038 (portability-ldpred2_335) |
PSS008183| South Asian Ancestry| 6,094 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0149 [-0.0103, 0.04] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011176 | PGS002038 (portability-ldpred2_335) |
PSS007749| African Ancestry| 2,390 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.006 [-0.0343, 0.0463] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011177 | PGS002038 (portability-ldpred2_335) |
PSS008853| African Ancestry| 3,790 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): -0.0243 [-0.0561, 0.0077] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011178 | PGS002039 (portability-ldpred2_351) |
PSS009302| European Ancestry| 19,840 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0728 [0.059, 0.0867] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011179 | PGS002039 (portability-ldpred2_351) |
PSS009076| European Ancestry| 4,112 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0556 [0.025, 0.0861] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011180 | PGS002039 (portability-ldpred2_351) |
PSS008630| European Ancestry| 6,611 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0652 [0.0412, 0.0892] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011182 | PGS002039 (portability-ldpred2_351) |
PSS008184| South Asian Ancestry| 6,277 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0433 [0.0186, 0.068] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011183 | PGS002039 (portability-ldpred2_351) |
PSS007968| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0229 [-0.0235, 0.0693] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011184 | PGS002039 (portability-ldpred2_351) |
PSS007750| African Ancestry| 2,471 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0037 [-0.0359, 0.0432] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011185 | PGS002039 (portability-ldpred2_351) |
PSS008854| African Ancestry| 3,898 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.005 [-0.0265, 0.0365] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011186 | PGS002040 (portability-ldpred2_361) |
PSS009303| European Ancestry| 19,445 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0276 [0.0135, 0.0416] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011187 | PGS002040 (portability-ldpred2_361) |
PSS009077| European Ancestry| 4,055 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0184 [-0.0125, 0.0492] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011188 | PGS002040 (portability-ldpred2_361) |
PSS008631| European Ancestry| 6,514 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0125 [-0.0119, 0.0368] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011189 | PGS002040 (portability-ldpred2_361) |
PSS008405| Greater Middle Eastern Ancestry| 1,169 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): -0.0028 [-0.0607, 0.055] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011190 | PGS002040 (portability-ldpred2_361) |
PSS008185| South Asian Ancestry| 6,095 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0276 [0.0024, 0.0527] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011191 | PGS002040 (portability-ldpred2_361) |
PSS007969| East Asian Ancestry| 1,773 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0368 [-0.0101, 0.0835] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011192 | PGS002040 (portability-ldpred2_361) |
PSS007751| African Ancestry| 2,384 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0222 [-0.0181, 0.0625] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011193 | PGS002040 (portability-ldpred2_361) |
PSS008855| African Ancestry| 3,743 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Retinal detachments and defects | — | — | Partial Correlation (partial-r): 0.0024 [-0.0297, 0.0345] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011195 | PGS002041 (portability-ldpred2_362.29) |
PSS009078| European Ancestry| 4,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0248 [-0.0061, 0.0556] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011196 | PGS002041 (portability-ldpred2_362.29) |
PSS008632| European Ancestry| 6,470 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0179 [-0.0065, 0.0423] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011197 | PGS002041 (portability-ldpred2_362.29) |
PSS008406| Greater Middle Eastern Ancestry| 1,165 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): -0.0344 [-0.0921, 0.0236] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011198 | PGS002041 (portability-ldpred2_362.29) |
PSS008186| South Asian Ancestry| 6,037 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0372 [0.0119, 0.0624] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011199 | PGS002041 (portability-ldpred2_362.29) |
PSS007970| East Asian Ancestry| 1,775 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): -0.0312 [-0.0779, 0.0156] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011200 | PGS002041 (portability-ldpred2_362.29) |
PSS007752| African Ancestry| 2,374 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0038 [-0.0366, 0.0442] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011201 | PGS002041 (portability-ldpred2_362.29) |
PSS008856| African Ancestry| 3,723 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.018 [-0.0143, 0.0501] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011278 | PGS002052 (portability-ldpred2_433.1) |
PSS009316| European Ancestry| 19,445 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0199 [0.0058, 0.034] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011279 | PGS002052 (portability-ldpred2_433.1) |
PSS009090| European Ancestry| 4,046 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0001 [-0.0308, 0.031] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011280 | PGS002052 (portability-ldpred2_433.1) |
PSS008644| European Ancestry| 6,521 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0191 [-0.0052, 0.0434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011282 | PGS002052 (portability-ldpred2_433.1) |
PSS008198| South Asian Ancestry| 6,173 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0003 [-0.0247, 0.0253] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011283 | PGS002052 (portability-ldpred2_433.1) |
PSS007980| East Asian Ancestry| 1,789 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): -0.0132 [-0.0598, 0.0334] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011284 | PGS002052 (portability-ldpred2_433.1) |
PSS007763| African Ancestry| 2,407 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0003 [-0.0398, 0.0404] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011285 | PGS002052 (portability-ldpred2_433.1) |
PSS008867| African Ancestry| 3,806 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0054 [-0.0265, 0.0372] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011286 | PGS002053 (portability-ldpred2_433) |
PSS009315| European Ancestry| 19,915 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0233 [0.0094, 0.0371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011287 | PGS002053 (portability-ldpred2_433) |
PSS009089| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0114 [-0.0193, 0.042] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011288 | PGS002053 (portability-ldpred2_433) |
PSS008643| European Ancestry| 6,641 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0244 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011289 | PGS002053 (portability-ldpred2_433) |
PSS008417| Greater Middle Eastern Ancestry| 1,198 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0536 [-0.0036, 0.1103] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011290 | PGS002053 (portability-ldpred2_433) |
PSS008197| South Asian Ancestry| 6,308 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0165 [-0.0082, 0.0412] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011291 | PGS002053 (portability-ldpred2_433) |
PSS007979| East Asian Ancestry| 1,804 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0131 [-0.0333, 0.0595] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011293 | PGS002053 (portability-ldpred2_433) |
PSS008866| African Ancestry| 3,912 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0287 [-0.0027, 0.0601] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011688 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS009387| European Ancestry| 19,161 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.1065 [0.0925, 0.1205] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011689 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS009161| European Ancestry| 3,907 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0785 [0.0471, 0.1096] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011690 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS008715| European Ancestry| 6,265 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0784 [0.0537, 0.103] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011691 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS008489| Greater Middle Eastern Ancestry| 1,089 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0425 [-0.0175, 0.1022] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011692 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS008267| South Asian Ancestry| 5,858 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0702 [0.0446, 0.0956] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011693 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS008045| East Asian Ancestry| 1,684 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0612 [0.0132, 0.1089] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011695 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS008935| African Ancestry| 3,691 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0136 [-0.0187, 0.046] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012007 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS009415| European Ancestry| 3,905 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0659 [0.0346, 0.0972] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012008 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS009189| European Ancestry| 1,095 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0619 [0.0021, 0.1212] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012009 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS008743| European Ancestry| 1,537 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0753 [0.0251, 0.1252] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012010 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS008517| Greater Middle Eastern Ancestry| 363 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.062 [-0.0442, 0.1668] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012011 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS008295| South Asian Ancestry| 1,716 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0288 [-0.0188, 0.0763] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012012 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS008072| East Asian Ancestry| 390 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): -0.0629 [-0.1638, 0.0393] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012013 | PGS002145 (portability-ldpred2_headaches_for_3m) |
PSS007859| African Ancestry| 570 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Headaches for 3+ months | — | — | Partial Correlation (partial-r): 0.0605 [-0.0232, 0.1434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012039 | PGS002149 (portability-ldpred2_insomnia) |
PSS009419| European Ancestry| 19,978 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1411 [0.1275, 0.1547] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012041 | PGS002149 (portability-ldpred2_insomnia) |
PSS008747| European Ancestry| 6,626 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.1253 [0.1015, 0.149] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012042 | PGS002149 (portability-ldpred2_insomnia) |
PSS008521| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0852 [0.0271, 0.1427] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012043 | PGS002149 (portability-ldpred2_insomnia) |
PSS008299| South Asian Ancestry| 6,199 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0985 [0.0737, 0.1231] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012044 | PGS002149 (portability-ldpred2_insomnia) |
PSS008076| East Asian Ancestry| 1,788 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0345 [-0.0122, 0.081] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012045 | PGS002149 (portability-ldpred2_insomnia) |
PSS007863| African Ancestry| 2,460 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0283 [-0.0114, 0.0679] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012046 | PGS002149 (portability-ldpred2_insomnia) |
PSS008967| African Ancestry| 3,863 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0314 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009459 | PGS001819 (portability-PLR_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0089 [-0.0233, 0.041] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009458 | PGS001819 (portability-PLR_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0193 [-0.0596, 0.021] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009518 | PGS001828 (portability-PLR_290.11) |
PSS009072| European Ancestry| 4,062 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | — | — | Partial Correlation (partial-r): -0.0098 [-0.0406, 0.021] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009530 | PGS001829 (portability-PLR_296.2) |
PSS007966| East Asian Ancestry| 1,742 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0274 [-0.0199, 0.0745] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009551 | PGS001832 (portability-PLR_351) |
PSS008404| Greater Middle Eastern Ancestry| 1,191 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): -0.039 [-0.0961, 0.0183] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009564 | PGS001834 (portability-PLR_362.29) |
PSS009304| European Ancestry| 19,413 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0175 [0.0034, 0.0315] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010012 | PGS001891 (portability-PLR_bad_hearing) |
PSS009387| European Ancestry| 19,161 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): 0.0921 [0.0781, 0.1062] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010336 | PGS001932 (portability-PLR_insomnia) |
PSS008076| East Asian Ancestry| 1,788 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Sleeplessness / insomnia | — | — | Partial Correlation (partial-r): 0.0473 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011097 | PGS002027 (portability-ldpred2_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0062 [-0.0259, 0.0384] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011157 | PGS002036 (portability-ldpred2_296.2) |
PSS008627| European Ancestry| 5,989 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Depression | — | — | Partial Correlation (partial-r): 0.0415 [0.0162, 0.0668] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011171 | PGS002038 (portability-ldpred2_335) |
PSS009301| European Ancestry| 19,299 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Multiple sclerosis | — | — | Partial Correlation (partial-r): 0.0396 [0.0255, 0.0536] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011181 | PGS002039 (portability-ldpred2_351) |
PSS008404| Greater Middle Eastern Ancestry| 1,191 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other peripheral nerve disorders | — | — | Partial Correlation (partial-r): 0.0081 [-0.0492, 0.0654] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011194 | PGS002041 (portability-ldpred2_362.29) |
PSS009304| European Ancestry| 19,413 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Macular degeneration (senile) of retina NOS | — | — | Partial Correlation (partial-r): 0.0159 [0.0018, 0.0299] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011281 | PGS002052 (portability-ldpred2_433.1) |
PSS008418| Greater Middle Eastern Ancestry| 1,183 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): -0.0093 [-0.0667, 0.0482] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011292 | PGS002053 (portability-ldpred2_433) |
PSS007762| African Ancestry| 2,470 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0139 [-0.0257, 0.0535] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011694 | PGS002104 (portability-ldpred2_bad_hearing) |
PSS007831| African Ancestry| 2,325 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hearing difficulty/problems | — | — | Partial Correlation (partial-r): -0.0054 [-0.0462, 0.0354] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012797 | PGS002249 (AD_PRS_0.5) |
PSS009559| European Ancestry| 196,383 individuals |
PGP000276 | Lourida I et al. JAMA (2019) |
Reported Trait: Incident dementia | — | — | Hazard Ratio (HR, high vs. low genetic risk): 1.91 [1.64, 2.23] | Age, sex, education, socioeconomic status, relatedness, number of alleles, weighted lifestyle categories | — |
| PPM012798 | PGS002249 (AD_PRS_0.5) |
PSS009559| European Ancestry| 196,383 individuals |
PGP000276 | Lourida I et al. JAMA (2019) |
Reported Trait: Incident dementia in individuals with high genetic risk | — | — | Incidence (%): 1.23 [1.13, 1.35] Incidence (%, individuals with unfavourable lifestyle): 1.78 [1.38, 2.28] Incidence (%, individuals with favourable lifestyle): 1.13 [1.01, 1.26] |
— | — |
| PPM012831 | PGS000903 (PRS1805_PD) |
PSS009572| European Ancestry| 6,378 individuals |
PGP000281 | Koch S et al. Genes (Basel) (2021) |Ext. |
Reported Trait: Parkinson's disease | — | AUROC: 0.645 [0.63, 0.66] | Nagelkerke’s Pseudo-R2: 0.348 | sex, age and first three PCs | Quality control led to the exclusion of 62 of the original 1805 PD-PRS SNPs |
| PPM012832 | PGS000903 (PRS1805_PD) |
PSS009572| European Ancestry| 6,378 individuals |
PGP000281 | Koch S et al. Genes (Basel) (2021) |Ext. |
Reported Trait: Parkinson's disease prognosis | — | — | Sensitivity: 0.581 [0.479, 0.625] Specificity: 0.625 [0.472, 0.725] |
— | Cost of 1: optimal threshold for PD-PRS as determined by maximizing a weighted Youden index = 0.33 |
| PPM012833 | PGS000903 (PRS1805_PD) |
PSS009572| European Ancestry| 6,378 individuals |
PGP000281 | Koch S et al. Genes (Basel) (2021) |Ext. |
Reported Trait: Parkinson's disease (age at onset) | — | AUROC: 0.59 [0.551, 0.629] | Nagelkerke’s Pseudo-R2: 0.039 | sex, age and first three PCs | Quality control led to the exclusion of 62 of the original 1805 PD-PRS SNPs |
| PPM012867 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident stroke | HR: 1.28 [1.21, 1.36] | — | Hazard Ratio (HR, highest vs lowest quintile): 1.99 [1.66, 2.38] | Sex | — |
| PPM012868 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident ischemic stroke | HR: 1.29 [1.2, 1.39] | — | Hazard Ratio (HR, highest vs lowest quintile): 2.13 [1.69, 2.69] | Sex | — |
| PPM012869 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident hemorrhagic stroke | HR: 1.3 [1.17, 1.45] | — | Hazard Ratio (HR, highest vs lowest quintile): 1.98 [1.41, 2.77] | Sex | — |
| PPM012873 | PGS002261 (PRS22_NB) |
PSS009587| African Ancestry| 3,619 individuals |
PGP000287 | Testori A et al. Cancer Epidemiol Biomarkers Prev (2022) |
Reported Trait: Neuroblastoma risk | — | — | R²: 0.0203 | — | — |
| PPM012991 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) time to complete in person round 1 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 5.3 | — | — |
| PPM012992 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) no. of incorrect in person round 1 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 4.4 | — | — |
| PPM012993 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) time to complete online round 1 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 3.5 | — | — |
| PPM012994 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) time to complete in person round 2 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 2.5 | — | — |
| PPM012995 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Numeric memory (short-term memory and attention) no. of correct online x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 8.8 | — | — |
| PPM012996 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Symbol digit substitution (processing speed) no. of correct in person x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 5.8 | — | — |
| PPM012997 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Symbol digit substitution (processing speed) no. attempted in person x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 5.7 | — | — |
| PPM012998 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Symbol digit substitution (processing speed) time to complete 10 substitutions online x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 4.5 | — | — |
| PPM012999 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Symbol digit substitution (processing speed) no. of correct online x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 2.4 | — | — |
| PPM013000 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Symbol digit substitution (processing speed) no. attempted online x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 2.0 | — | — |
| PPM014736 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009879| European Ancestry| 403,489 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.16, 1.21] | C-index: 0.645 | ∆C-index (improvement in C-index over covariates-only model): 0.01 | age, sex, 5 PCs | — |
| PPM014749 | PGS002726 (PGS_MS_Brain) |
PSS009883| European Ancestry| 253,419 individuals |
PGP000334 | Shams H et al. Brain (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.73 [0.72, 0.74] | Odds ratio (OR, top 10% vs median): 5.3 [4.7, 6.0] | — | — |
| PPM014750 | PGS002726 (PGS_MS_Brain) |
PSS009882| European Ancestry| 938 individuals |
PGP000334 | Shams H et al. Brain (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.8 [0.76, 0.82] | Odds ratio (OR, top 10% vs median): 15.0 [10.4, 24.0] | — | — |
| PPM012920 | PGS002269 (PRS47_AMD) |
PSS009618| Multi-ancestry (including European)| 44,823 individuals |
PGP000299 | Zekavat SM et al. Ophthalmology (2022) |
Reported Trait: Rentinal layer thickness (photoreceptor inner and outer segments) | β: -0.21 [-0.23, -0.19] | — | — | Age, age2 (to adjust for non-linear relationships with age), sex, smoking status, and the first ten principal components of genetic ancestry | — |
| PPM012921 | PGS002269 (PRS47_AMD) |
PSS009618| Multi-ancestry (including European)| 44,823 individuals |
PGP000299 | Zekavat SM et al. Ophthalmology (2022) |
Reported Trait: Rentinal layer thickness (retinal pigment epithelium and Bruch’s membrane complex) | β: -0.14 [-0.16, -0.12] | — | — | Age, age2 (to adjust for non-linear relationships with age), sex, smoking status, and the first ten principal components of genetic ancestry | — |
| PPM012922 | PGS002269 (PRS47_AMD) |
PSS009618| Multi-ancestry (including European)| 44,823 individuals |
PGP000299 | Zekavat SM et al. Ophthalmology (2022) |
Reported Trait: Rentinal layer thickness (choroid-sclera interface) | β: -0.03 [-0.06, -0.01] | — | — | Age, age2 (to adjust for non-linear relationships with age), sex, smoking status, and the first ten principal components of genetic ancestry | — |
| PPM014747 | PGS002725 (GIGASTROKE_iPGS_EAS) |
PSS009881| East Asian Ancestry| 87,682 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.18 [1.12, 1.25] | AUROC: 0.765 | ∆AUROC (improvement in AUROC over covariates-only model): 0.003 | age, sex, 5 PCs | — |
| PPM012966 | PGS002280 (GRS83_AD) |
PSS009635| European Ancestry| 17,545 individuals |
PGP000309 | Bellenguez C et al. Nat Genet (2022) |
Reported Trait: Conversion to Alzheimer disease | HR: 1.076 [1.064, 1.088] | — | Hazard Ratio (HR; highest vs. lowest decile): 1.93 [1.75, 2.13] | Age, sex, number of APOE-ε4 and APOE-ε2 alleles and genetic principal components | Fixed-effect meta-analysis |
| PPM012967 | PGS002280 (GRS83_AD) |
PSS009634| European Ancestry| 4,114 individuals |
PGP000309 | Bellenguez C et al. Nat Genet (2022) |
Reported Trait: Conversion to Alzheimer disease (in mild cognitive impairment) | HR: 1.056 [1.04, 1.072] | — | Hazard Ratio (HR; highest vs. lowest decile): 1.63 [1.42, 1.87] | Age, sex, number of APOE-ε4 and APOE-ε2 alleles and genetic principal components | Fixed-effect meta-analysis |
| PPM012968 | PGS002280 (GRS83_AD) |
PSS009635| European Ancestry| 17,545 individuals |
PGP000309 | Bellenguez C et al. Nat Genet (2022) |
Reported Trait: Conversion to Alzheimer disease within 5 years | — | — | NRI (net reclassification improvement): 0.248 [0.159, 0.336] Delta C-index: 0.002 [0.0004, 0.004] |
Age, sex, number of APOE-ε4 and APOE-ε2 alleles and genetic principal components | Fixed-effect meta-analysis |
| PPM012969 | PGS002280 (GRS83_AD) |
PSS009635| European Ancestry| 17,545 individuals |
PGP000309 | Bellenguez C et al. Nat Genet (2022) |
Reported Trait: Conversion to Alzheimer disease within 3 years (in mild cognitive impairment) | — | — | NRI (net reclassification improvement): 0.232 [0.14, 0.325] Delta C-index: 0.007 [0.001, 0.012] |
Age, sex, number of APOE-ε4 and APOE-ε2 alleles and genetic principal components | Fixed-effect meta-analysis |
| PPM012988 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) no. of correct online round 1 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 11.5 | — | — |
| PPM012989 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) no. of correct in person round 1 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 7.9 | — | — |
| PPM012990 | PGS002289 (GRS23_AD) |
PSS009642| European Ancestry| 497,087 individuals |
PGP000316 | Zimmerman SC et al. JAMA Netw Open (2022) |
Reported Trait: Pairs matching (short-term memory and attention) no. of correct in person round 2 x age interaction | — | — | Difference in mean cognition per decacde increase in age per 1-SD higher GRS (%): 9.4 | — | — |
| PPM012987 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009641| European Ancestry| 3,071 individuals |
PGP000315 | Hämmerle M et al. Stroke (2022) |Ext. |
Reported Trait: Stroke | — | — | Odds ratio (OR, top 1% vs. rest): 5.82 [2.08, 14.0] | Age, sex, BMI, hypertension, cholesterol, diabetes, smoker | — |
| PPM014809 | PGS002731 (oA-PRS) |
PSS009897| Ancestry Not Reported| 228 individuals |
PGP000339 | Xicota L et al. Neurology (2022) |
Reported Trait: Amyloid burden | OR: 3.38 [1.02, 11.63] | — | — | — | — |
| PPM014810 | PGS002731 (oA-PRS) |
PSS009897| Ancestry Not Reported| 228 individuals |
PGP000339 | Xicota L et al. Neurology (2022) |
Reported Trait: Amyloid burden in E4 carriers | OR: 44.94 [3.03, 1277.0] | — | — | — | — |
| PPM014811 | PGS000026 (PHS) |
PSS009898| Ancestry Not Reported| 780 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in neocortical region | β: 19.98 [14.3, 25.7] | — | — | — | — |
| PPM014812 | PGS000026 (PHS) |
PSS009898| Ancestry Not Reported| 780 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in posterior cingulate region | β: 25.54 [18.4, 32.6] | — | — | — | — |
| PPM014814 | PGS000026 (PHS) |
PSS009900| Ancestry Not Reported| 278 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in neocortical region (in APOE E4 carriers) | β: 25.28 [17.4, 33.2] | — | — | — | — |
| PPM014815 | PGS000026 (PHS) |
PSS009900| Ancestry Not Reported| 278 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in posterior cingulate region (in APOE E4 carriers) | β: 33.06 [23.3, 42.8] | — | — | — | — |
| PPM014816 | PGS000026 (PHS) |
PSS009900| Ancestry Not Reported| 278 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in frontal cortex region (in APOE E4 carriers) | β: 26.63 [18.0, 35.3] | — | — | — | — |
| PPM014817 | PGS000026 (PHS) |
PSS009899| Ancestry Not Reported| 502 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in neocortical region (in APOE E4 non-carriers) | β: 12.61 [3.9, 21.3] | — | — | — | — |
| PPM014818 | PGS000026 (PHS) |
PSS009899| Ancestry Not Reported| 502 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in posterior cingulate region (in APOE E4 non-carriers) | β: 14.28 [3.42, 25.1] | — | — | — | — |
| PPM014819 | PGS000026 (PHS) |
PSS009899| Ancestry Not Reported| 502 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in frontal cortex region (in APOE E4 non-carriers) | β: 13.62 [4.24, 23.0] | — | — | — | — |
| PPM013031 | PGS002302 (PRS28_glioma) |
PSS009663| European Ancestry| 312 individuals |
PGP000328 | Choi J et al. Int J Cancer (2020) |
Reported Trait: Glioma | — | AUROC: 0.61 [0.57, 0.64] | — | — | — |
| PPM013039 | PGS002302 (PRS28_glioma) |
PSS009663| European Ancestry| 312 individuals |
PGP000328 | Choi J et al. Int J Cancer (2020) |
Reported Trait: Glioma | — | — | Hazard ratio (HR top 5% vs average): 2.55 [1.72, 3.77] | Age, birth cohort, genotyping array, top 10 PCs for ancestry and sex (for nonsex specific cancer only) | — |
| PPM017176 | PGS003440 (GRS11_nonapoeAD) |
PSS010155| Ancestry Not Reported| 117 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via cortical thickness in adoptees | β: 0.008 (0.005) | — | — | — | — |
| PPM017177 | PGS003440 (GRS11_nonapoeAD) |
PSS010156| Ancestry Not Reported| 4,382 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via cortical thickness in non-adoptees | β: 0.0001 (0.001) | — | — | — | — |
| PPM017178 | PGS003441 (GRS28_AD) |
PSS010155| Ancestry Not Reported| 117 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via cortical thickness in adoptees | β: 0.011 (0.006) | — | — | — | — |
| PPM017179 | PGS003441 (GRS28_AD) |
PSS010156| Ancestry Not Reported| 4,382 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via cortical thickness in non-adoptees | β: -0.001 (0.001) | — | — | — | — |
| PPM017180 | PGS003442 (GRS8_MD) |
PSS010155| Ancestry Not Reported| 117 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via average SST BOLD activation in adoptees | β: 0.064 (0.027) | — | — | — | — |
| PPM017181 | PGS003442 (GRS8_MD) |
PSS010156| Ancestry Not Reported| 4,382 individuals |
PGP000444 | Petrican R et al. Sci Rep (2023) |
Reported Trait: Fluid cognition via verage SST BOLD activation in non-adoptees | β: 0.0 (0.004) | — | — | — | — |
| PPM014813 | PGS000026 (PHS) |
PSS009898| Ancestry Not Reported| 780 individuals |
PGP000340 | Vacher M et al. BMC Genomics (2022) |Ext. |
Reported Trait: Aβ-amyloid deposition in frontal cortex region | β: 21.19 [15.0, 27.4] | — | — | — | — |
| PPM014920 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: Specific internalizing (at baseline) | β: -0.06 (0.02) | — | — | — | — |
| PPM009306 | PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007705| Additional Asian Ancestries| 8,091 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.745 | Nagelkerke's R2 (covariates regressed out): 0.01187 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM014953 | PGS002753 (Alzheimer_s_disease_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Alzheimer's disease | OR: 1.64 [1.5, 1.79] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM009314 | PGS001798 (1kgeur_gbmi_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007696| European Ancestry| 7,128 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.704 | Nagelkerke's R2 (covariates regressed out): 0.00746 | sex,age, 20PCs | — |
| PPM014921 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: Specific conduct problem (1-year follow-up) | β: 0.09 (0.02) | — | — | — | — |
| PPM014922 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: Specific ADHD (1-year follow-up) | β: 0.11 (0.03) | — | — | — | — |
| PPM014924 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: UPPS Impulsive Behavior Scale (Positive urgency) | β: 0.046 (0.016) | — | — | Age, sex, and the first 10 principal components of population structure | — |
| PPM014925 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: Latent executive functioning | β: -0.042 | — | — | Age, sex, and the first 10 principal components of population structure | — |
| PPM014928 | PGS000903 (PRS1805_PD) |
PSS009933| South Asian Ancestry| 90 individuals |
PGP000360 | Kukkle PL et al. Adv Biol (Weinh) (2022) |Ext. |
Reported Trait: Young onset Parkinson’s disease | — | — | Odds ratio, OR (high vs low risk): 1.92 | — | — |
| PPM015033 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00016 | age, PCs1-3 | — |
| PPM015034 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00116 | age, PCs1-3 | — |
| PPM009297 | PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007716| European Ancestry| 350,408 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.706 | Nagelkerke's R2 (covariates regressed out): 0.00278 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM014919 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: General factor of psychological problems (1-year follow-up) | β: 0.07 (0.02) | — | — | — | — |
| PPM014923 | PGS002746 (PRS_ADHD) |
PSS009931| European Ancestry| 4,483 individuals |
PGP000358 | Lahey BB et al. J Psychiatr Res (2022) |
Reported Trait: UPPS Impulsive Behavior Scale (Low perseverance) | β: 0.043 (0.017) | — | — | Age, sex, and the first 10 principal components of population structure | — |
| PPM014992 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00015 | age, PCs1-3 | — |
| PPM015043 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015111 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.00032 | age, PCs1-3 | — |
| PPM015112 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015179 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015180 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00065 | age, PCs1-3 | — |
| PPM015246 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00268 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015300 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00106 | age, PCs1-3 | — |
| PPM015302 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 4.69e-07 | age, PCs1-3 | — |
| PPM015363 | PGS002790 (ASD_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00176 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015364 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Corticospinal tract R | — | — | partial R²: 0.00123 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015408 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Posterior corona radiata R | — | — | partial R²: 0.00088 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM014737 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009879| European Ancestry| 403,489 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.13 [1.1, 1.15] | C-index: 0.64 | ∆C-index (improvement in C-index over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014738 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009876| European Ancestry| 51,288 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.11, 1.27] | C-index: 0.644 | ∆C-index (improvement in C-index over covariates-only model): 0.008 | age, sex, 5 PCs | — |
| PPM014739 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009876| European Ancestry| 51,288 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.14 [1.06, 1.21] | C-index: 0.641 | ∆C-index (improvement in C-index over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014740 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009878| African Ancestry| 107,343 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.11 [1.06, 1.17] | C-index: 0.653 | ∆C-index (improvement in C-index over covariates-only model): 0.003 | age, sex, 5 PCs | — |
| PPM014741 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009878| African Ancestry| 107,343 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.09 [1.04, 1.14] | C-index: 0.652 | ∆C-index (improvement in C-index over covariates-only model): 0.002 | age, sex, 5 PCs | — |
| PPM014742 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009880| African Ancestry| 3,434 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.09 [1.02, 1.17] | AUROC: 0.548 | ∆AUROC (improvement in AUROC over covariates-only model): 0.007 | age, sex, 5 PCs | — |
| PPM014744 | PGS002725 (GIGASTROKE_iPGS_EAS) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.33 [1.26, 1.4] | AUROC: 0.653 | ∆AUROC (improvement in AUROC over covariates-only model): 0.019 | age, sex, 5 PCs | — |
| PPM014745 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.18 [1.12, 1.25] | AUROC: 0.643 | ∆AUROC (improvement in AUROC over covariates-only model): 0.009 | age, sex, 5 PCs | — |
| PPM014748 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009881| East Asian Ancestry| 87,682 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.1 [1.04, 1.16] | AUROC: 0.763 | ∆AUROC (improvement in AUROC over covariates-only model): 0.001 | age, sex, 5 PCs | — |
| PPM015035 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015036 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00025 | age, PCs1-3 | — |
| PPM015037 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00011 | age, PCs1-3 | — |
| PPM015038 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015039 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 6.77e-06 | age, PCs1-3 | — |
| PPM015040 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.0019 | age, PCs1-3 | — |
| PPM014993 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00085 | age, PCs1-3 | — |
| PPM014994 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 4.36e-07 | age, PCs1-3 | — |
| PPM014995 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00032 | age, PCs1-3 | — |
| PPM014996 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00093 | age, PCs1-3 | — |
| PPM014997 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00041 | age, PCs1-3 | — |
| PPM014998 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00028 | age, PCs1-3 | — |
| PPM014999 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00048 | age, PCs1-3 | — |
| PPM015000 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00026 | age, PCs1-3 | — |
| PPM015001 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00046 | age, PCs1-3 | — |
| PPM015002 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00056 | age, PCs1-3 | — |
| PPM015003 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00089 | age, PCs1-3 | — |
| PPM015005 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00021 | age, PCs1-3 | — |
| PPM015006 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00081 | age, PCs1-3 | — |
| PPM015007 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00021 | age, PCs1-3 | — |
| PPM015008 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00039 | age, PCs1-3 | — |
| PPM015009 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00038 | age, PCs1-3 | — |
| PPM015010 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015011 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00088 | age, PCs1-3 | — |
| PPM015013 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00179 | age, PCs1-3 | — |
| PPM015014 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00287 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015015 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.0039 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015016 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00279 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015017 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00062 | age, PCs1-3 | — |
| PPM015018 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.0027 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015019 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00502 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015020 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.00661 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015021 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00806 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015022 | PGS002785 (SCZ_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00398 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015023 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015024 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 4.06e-06 | age, PCs1-3 | — |
| PPM015025 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00087 | age, PCs1-3 | — |
| PPM015026 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015027 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00053 | age, PCs1-3 | — |
| PPM015044 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00017 | age, PCs1-3 | — |
| PPM015045 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00411 | age, PCs1-3 | — |
| PPM015046 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00034 | age, PCs1-3 | — |
| PPM015047 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00019 | age, PCs1-3 | — |
| PPM015048 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015049 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.0001 | age, PCs1-3 | — |
| PPM015050 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00146 | age, PCs1-3 | — |
| PPM015051 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015052 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00082 | age, PCs1-3 | — |
| PPM015054 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 1e-05 | age, PCs1-3 | — |
| PPM015055 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015056 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015057 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00045 | age, PCs1-3 | — |
| PPM015058 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 1.31e-06 | age, PCs1-3 | — |
| PPM015059 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015060 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00029 | age, PCs1-3 | — |
| PPM015061 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 9e-05 | age, PCs1-3 | — |
| PPM015062 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015063 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00015 | age, PCs1-3 | — |
| PPM015064 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015065 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015066 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015067 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00028 | age, PCs1-3 | — |
| PPM015068 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015070 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015071 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015072 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.0005 | age, PCs1-3 | — |
| PPM015073 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015074 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00014 | age, PCs1-3 | — |
| PPM015075 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015076 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00061 | age, PCs1-3 | — |
| PPM015077 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015078 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00251 | age, PCs1-3 | — |
| PPM015079 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00023 | age, PCs1-3 | — |
| PPM015080 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015082 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 7.85e-06 | age, PCs1-3 | — |
| PPM015083 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00087 | age, PCs1-3 | — |
| PPM015084 | PGS002786 (BD_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 7e-05 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015085 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00119 | age, PCs1-3 | — |
| PPM015086 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00051 | age, PCs1-3 | — |
| PPM015087 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00027 | age, PCs1-3 | — |
| PPM015088 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00079 | age, PCs1-3 | — |
| PPM015089 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.0005 | age, PCs1-3 | — |
| PPM015090 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015091 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00077 | age, PCs1-3 | — |
| PPM015093 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00101 | age, PCs1-3 | — |
| PPM015094 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00034 | age, PCs1-3 | — |
| PPM015095 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00092 | age, PCs1-3 | — |
| PPM015096 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00196 | age, PCs1-3 | — |
| PPM015097 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00198 | age, PCs1-3 | — |
| PPM015098 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 1.76e-06 | age, PCs1-3 | — |
| PPM015099 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 7.78e-07 | age, PCs1-3 | — |
| PPM015100 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00022 | age, PCs1-3 | — |
| PPM015101 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00032 | age, PCs1-3 | — |
| PPM015102 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00067 | age, PCs1-3 | — |
| PPM015104 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00101 | age, PCs1-3 | — |
| PPM015105 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00186 | age, PCs1-3 | — |
| PPM015106 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 8.61e-07 | age, PCs1-3 | — |
| PPM015107 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015108 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015109 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015113 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.00135 | age, PCs1-3 | — |
| PPM015114 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00016 | age, PCs1-3 | — |
| PPM015116 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 3.60e-06 | age, PCs1-3 | — |
| PPM015117 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 9e-05 | age, PCs1-3 | — |
| PPM015118 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015119 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00025 | age, PCs1-3 | — |
| PPM015120 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015121 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015122 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00015 | age, PCs1-3 | — |
| PPM015123 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 1e-05 | age, PCs1-3 | — |
| PPM015124 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 7.64e-07 | age, PCs1-3 | — |
| PPM015125 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015126 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 1.57e-09 | age, PCs1-3 | — |
| PPM015127 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00019 | age, PCs1-3 | — |
| PPM015128 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 3.52e-06 | age, PCs1-3 | — |
| PPM015129 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00014 | age, PCs1-3 | — |
| PPM015130 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 2.44e-06 | age, PCs1-3 | — |
| PPM015132 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 3.41e-06 | age, PCs1-3 | — |
| PPM015133 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015134 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00031 | age, PCs1-3 | — |
| PPM015135 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015136 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015137 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 9e-05 | age, PCs1-3 | — |
| PPM015138 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00046 | age, PCs1-3 | — |
| PPM015139 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00067 | age, PCs1-3 | — |
| PPM015140 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00164 | age, PCs1-3 | — |
| PPM015141 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00045 | age, PCs1-3 | — |
| PPM015142 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015144 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015145 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00115 | age, PCs1-3 | — |
| PPM015146 | PGS002787 (BD1_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00013 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015147 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00068 | age, PCs1-3 | — |
| PPM015148 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 7.61e-07 | age, PCs1-3 | — |
| PPM015149 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00059 | age, PCs1-3 | — |
| PPM015150 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00013 | age, PCs1-3 | — |
| PPM015151 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00051 | age, PCs1-3 | — |
| PPM015152 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015153 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00053 | age, PCs1-3 | — |
| PPM015155 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00055 | age, PCs1-3 | — |
| PPM015156 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015157 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00066 | age, PCs1-3 | — |
| PPM015158 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00275 | age, PCs1-3 | — |
| PPM015159 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00081 | age, PCs1-3 | — |
| PPM015160 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015161 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 1.13e-06 | age, PCs1-3 | — |
| PPM015162 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00032 | age, PCs1-3 | — |
| PPM015163 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015164 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00022 | age, PCs1-3 | — |
| PPM015166 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00057 | age, PCs1-3 | — |
| PPM015167 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00079 | age, PCs1-3 | — |
| PPM015168 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00021 | age, PCs1-3 | — |
| PPM015169 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00022 | age, PCs1-3 | — |
| PPM015170 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015171 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00016 | age, PCs1-3 | — |
| PPM015172 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015173 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.00036 | age, PCs1-3 | — |
| PPM015174 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 5.31e-06 | age, PCs1-3 | — |
| PPM015175 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.00072 | age, PCs1-3 | — |
| PPM015176 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00027 | age, PCs1-3 | — |
| PPM015181 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00039 | age, PCs1-3 | — |
| PPM015182 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015183 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00092 | age, PCs1-3 | — |
| PPM015185 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00217 | age, PCs1-3 | — |
| PPM015186 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00055 | age, PCs1-3 | — |
| PPM015187 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00192 | age, PCs1-3 | — |
| PPM015188 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00114 | age, PCs1-3 | — |
| PPM015189 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 2.60e-06 | age, PCs1-3 | — |
| PPM015190 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00045 | age, PCs1-3 | — |
| PPM015191 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00071 | age, PCs1-3 | — |
| PPM015192 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.0006 | age, PCs1-3 | — |
| PPM015193 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00195 | age, PCs1-3 | — |
| PPM015194 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00088 | age, PCs1-3 | — |
| PPM015196 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00097 | age, PCs1-3 | — |
| PPM015197 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00138 | age, PCs1-3 | — |
| PPM015198 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00049 | age, PCs1-3 | — |
| PPM015199 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015200 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00036 | age, PCs1-3 | — |
| PPM015201 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00014 | age, PCs1-3 | — |
| PPM015202 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015203 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00011 | age, PCs1-3 | — |
| PPM015204 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 1e-05 | age, PCs1-3 | — |
| PPM015205 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.0003 | age, PCs1-3 | — |
| PPM015206 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015207 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00026 | age, PCs1-3 | — |
| PPM015209 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00163 | age, PCs1-3 | — |
| PPM015210 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00156 | age, PCs1-3 | — |
| PPM015211 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00085 | age, PCs1-3 | — |
| PPM015212 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00123 | age, PCs1-3 | — |
| PPM015213 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015214 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015215 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00057 | age, PCs1-3 | — |
| PPM015216 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015217 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00197 | age, PCs1-3 | — |
| PPM015218 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00016 | age, PCs1-3 | — |
| PPM015220 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.0006 | age, PCs1-3 | — |
| PPM015221 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00145 | age, PCs1-3 | — |
| PPM015222 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00071 | age, PCs1-3 | — |
| PPM015223 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015224 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015225 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015226 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.0001 | age, PCs1-3 | — |
| PPM015227 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00125 | age, PCs1-3 | — |
| PPM015228 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00025 | age, PCs1-3 | — |
| PPM015230 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 1.91e-06 | age, PCs1-3 | — |
| PPM015231 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 3.47e-06 | age, PCs1-3 | — |
| PPM015232 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 8.67e-06 | age, PCs1-3 | — |
| PPM015233 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 9.91e-06 | age, PCs1-3 | — |
| PPM015234 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015235 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.0001 | age, PCs1-3 | — |
| PPM015236 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015237 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015238 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 3.27e-06 | age, PCs1-3 | — |
| PPM015239 | PGS002788 (BD2_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 5.36e-06 | age, PCs1-10 | — |
| PPM015241 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00533 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015242 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00626 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015303 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00125 | age, PCs1-3 | — |
| PPM015304 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00061 | age, PCs1-3 | — |
| PPM015243 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00358 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015244 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00276 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015247 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00203 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015248 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00815 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015249 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00246 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015250 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00528 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015251 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00752 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015252 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00657 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015253 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00516 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015254 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00088 | age, PCs1-3 | — |
| PPM015255 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00172 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015256 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00205 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015257 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.0067 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015258 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00297 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015259 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00464 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015260 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00077 | age, PCs1-3 | — |
| PPM015261 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 7e-05 | age, PCs1-3 | — |
| PPM015262 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00112 | age, PCs1-3 | — |
| PPM015263 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00064 | age, PCs1-3 | — |
| PPM015264 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015265 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00045 | age, PCs1-3 | — |
| PPM015266 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.00281 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015267 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00047 | age, PCs1-3 | — |
| PPM015268 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.00222 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015269 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00155 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015270 | PGS002789 (MDD_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00137 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015271 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00213 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015272 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00201 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015273 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00469 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015274 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00414 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015275 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00322 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015276 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00218 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015277 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00165 | age, PCs1-3 | — |
| PPM015279 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00397 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015280 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00439 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015281 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00566 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015282 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00515 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015283 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00335 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015284 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00266 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015285 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00154 | age, PCs1-3 | — |
| PPM015286 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00642 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015287 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00155 | age, PCs1-3 | — |
| PPM015288 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00254 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015289 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00049 | age, PCs1-3 | — |
| PPM015290 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.0055 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015291 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00143 | age, PCs1-3 | — |
| PPM015292 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00019 | age, PCs1-3 | — |
| PPM015293 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00068 | age, PCs1-3 | — |
| PPM015294 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015295 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015296 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00048 | age, PCs1-3 | — |
| PPM015297 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.00014 | age, PCs1-3 | — |
| PPM015301 | PGS002789 (MDD_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00137 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015305 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015306 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00063 | age, PCs1-3 | — |
| PPM015307 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.0025 | age, PCs1-3 | — |
| PPM015308 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.0002 | age, PCs1-3 | — |
| PPM015309 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00071 | age, PCs1-3 | — |
| PPM015310 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015311 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00059 | age, PCs1-3 | — |
| PPM015313 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00043 | age, PCs1-3 | — |
| PPM015314 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 1.74e-06 | age, PCs1-3 | — |
| PPM015315 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00075 | age, PCs1-3 | — |
| PPM015316 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00167 | age, PCs1-3 | — |
| PPM015317 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00068 | age, PCs1-3 | — |
| PPM015318 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00049 | age, PCs1-3 | — |
| PPM015319 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.0033 | age, PCs1-3 | — |
| PPM015320 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00017 | age, PCs1-3 | — |
| PPM015321 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00052 | age, PCs1-3 | — |
| PPM015323 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00024 | age, PCs1-3 | — |
| PPM015324 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00119 | age, PCs1-3 | — |
| PPM015325 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 0.00056 | age, PCs1-3 | — |
| PPM015326 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 0.00012 | age, PCs1-3 | — |
| PPM015327 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00063 | age, PCs1-3 | — |
| PPM015328 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.0005 | age, PCs1-3 | — |
| PPM015329 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 4e-05 | age, PCs1-3 | — |
| PPM015330 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.0013 | age, PCs1-3 | — |
| PPM015331 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00017 | age, PCs1-3 | — |
| PPM015333 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00313 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015334 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (withdrawn) | — | — | partial R²: 0.00546 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015335 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (somatic symptoms) | — | — | partial R²: 0.00032 | age, PCs1-3 | — |
| PPM015336 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (social problems) | — | — | partial R²: 0.00287 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015337 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (thought problems) | — | — | partial R²: 0.00221 | age, PCs1-3 | — |
| PPM015338 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00377 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015339 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00135 | age, PCs1-3 | — |
| PPM015340 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00138 | age, PCs1-3 | — |
| PPM015341 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00344 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015342 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 0.00156 | age, PCs1-3 | — |
| PPM015343 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00382 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015344 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 depression) | — | — | partial R²: 0.00429 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015345 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 0.00227 | age, PCs1-3 | — |
| PPM015346 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 somatic problem) | — | — | partial R²: 0.00025 | age, PCs1-3 | — |
| PPM015347 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 adhd) | — | — | partial R²: 0.00296 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015348 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 0.00205 | age, PCs1-3 | — |
| PPM015349 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 conduct) | — | — | partial R²: 0.00133 | age, PCs1-3 | — |
| PPM015350 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00422 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015352 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00239 | age, PCs1-3 | — |
| PPM015353 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 1e-05 | age, PCs1-3 | — |
| PPM015354 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Flanker test) | — | — | partial R²: 0.00035 | age, PCs1-3 | — |
| PPM015355 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (list sorting) | — | — | partial R²: 0.00075 | age, PCs1-3 | — |
| PPM015356 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (card sorting) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015357 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (pattern comparison) | — | — | partial R²: 2.82e-07 | age, PCs1-3 | — |
| PPM015358 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00121 | age, PCs1-3 | — |
| PPM015359 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (reading) | — | — | partial R²: 0.00013 | age, PCs1-3 | — |
| PPM015360 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00021 | age, PCs1-3 | — |
| PPM015361 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015365 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_61 | — | — | partial R²: 0.00131 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015366 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_103 | — | — | partial R²: 0.00146 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015367 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_109 | — | — | partial R²: 0.00191 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015368 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_130 | — | — | partial R²: 0.00179 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015369 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_132 | — | — | partial R²: 0.00116 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015370 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_149 | — | — | partial R²: 0.00186 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015371 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_184 | — | — | partial R²: 0.00137 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015372 | PGS002785 (SCZ_SDPR) |
PSS009954| European Ancestry| 11,180 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_185 | — | — | partial R²: 0.00234 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015373 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulate gyrus anterior division right | — | — | partial R²: 0.00074 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015374 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Middle cerebellar peduncle | — | — | partial R²: 0.00076 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015375 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior cerebellar peduncle R | — | — | partial R²: 0.00097 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015376 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior cerebellar peduncle L | — | — | partial R²: 0.00085 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015377 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cerebral peduncle R | — | — | partial R²: 0.00101 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015378 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Retrolenticular part of internal capsule R | — | — | partial R²: 0.00097 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015379 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: External capsule R | — | — | partial R²: 0.00074 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015380 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulum (cingulate gyrus) R | — | — | partial R²: 0.00121 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015381 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulum (cingulate gyrus) L | — | — | partial R²: 0.0008 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015382 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior longitudinal fasciculus R | — | — | partial R²: 0.00107 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015383 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior longitudinal fasciculus L | — | — | partial R²: 0.00105 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015384 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior fronto-occipital fasciculus R | — | — | partial R²: 0.00085 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015385 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulum (cingulate gyrus) R | — | — | partial R²: 0.00137 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015386 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Inferior fronto-occipital fasciculus R | — | — | partial R²: 0.00072 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015387 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_11 | — | — | partial R²: 0.00121 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015388 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_16 | — | — | partial R²: 0.00091 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015389 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_24 | — | — | partial R²: 0.00139 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015390 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_36 | — | — | partial R²: 0.00078 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015391 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_55 | — | — | partial R²: 0.0009 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015392 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_66 | — | — | partial R²: 0.00094 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015393 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_68 | — | — | partial R²: 0.00095 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015395 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_83 | — | — | partial R²: 0.00119 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015396 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_90 | — | — | partial R²: 0.00092 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015397 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_91 | — | — | partial R²: 0.00087 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015398 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_123 | — | — | partial R²: 0.00084 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015399 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_136 | — | — | partial R²: 0.00072 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015400 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_137 | — | — | partial R²: 0.0009 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015401 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_142 | — | — | partial R²: 0.00098 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015402 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_161 | — | — | partial R²: 0.00098 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015403 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_175 | — | — | partial R²: 0.00071 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015404 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_189 | — | — | partial R²: 0.00126 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015405 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_191 | — | — | partial R²: 0.0033 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015406 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_199 | — | — | partial R²: 0.00085 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015409 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulum (cingulate gyrus) R | — | — | partial R²: 0.00095 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015410 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Splenium of corpus callosum | — | — | partial R²: 0.00099 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015411 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Sagittal stratum | — | — | partial R²: 0.00095 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015412 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Uncinate fasciculus L | — | — | partial R²: 0.0009 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015413 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Forceps major | — | — | partial R²: 0.00092 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015415 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Inferior longitudinal fasciculus L | — | — | partial R²: 0.00108 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015416 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Inferior longitudinal fasciculus R | — | — | partial R²: 0.00128 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015417 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Uncinate fasciculus L | — | — | partial R²: 0.00104 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015418 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Uncinate fasciculus R | — | — | partial R²: 0.00089 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015419 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_83 | — | — | partial R²: 0.00095 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015420 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_137 | — | — | partial R²: 0.00119 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015421 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_176 | — | — | partial R²: 0.00116 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015422 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Genu of corpus callosum | — | — | partial R²: 0.00139 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015423 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Body of corpus callosum | — | — | partial R²: 0.00095 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015424 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior limb of internal capsule R | — | — | partial R²: 0.00161 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015425 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior limb of internal capsule L | — | — | partial R²: 0.00093 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015426 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Posterior limb of internal capsule R | — | — | partial R²: 0.0008 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015427 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior corona radiata R | — | — | partial R²: 0.00087 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015428 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior corona radiata L | — | — | partial R²: 0.00092 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015429 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cingulum cingulate gyrus R | — | — | partial R²: 0.00105 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015430 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior frontooccipital fasciculus R | — | — | partial R²: 0.00096 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015431 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Genu of corpus callosum | — | — | partial R²: 0.00106 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015432 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Body of corpus callosum | — | — | partial R²: 0.00123 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015433 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior limb of internal capsule R | — | — | partial R²: 0.00155 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015434 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior corona radiata R | — | — | partial R²: 0.00097 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015435 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior corona radiata L | — | — | partial R²: 0.00097 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015436 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior corona radiata R | — | — | partial R²: 0.00146 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015437 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior corona radiata L | — | — | partial R²: 0.00099 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015438 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior longitudinal fasciculus R | — | — | partial R²: 0.00094 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015439 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior longitudinal fasciculus L | — | — | partial R²: 0.00109 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015440 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior frontooccipital fasciculus R | — | — | partial R²: 0.00081 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015441 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Anterior thalamic radiation right | — | — | partial R²: 0.00102 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015442 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Forceps minor | — | — | partial R²: 0.00115 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015443 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior longitudinal fasciculus L | — | — | partial R²: 0.00099 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015444 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Superior thalamic radiation R | — | — | partial R²: 0.00131 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015445 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_83 | — | — | partial R²: 0.00079 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015446 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_104 | — | — | partial R²: 0.00119 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015447 | PGS002789 (MDD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_202 | — | — | partial R²: 0.00058 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015028 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00043 | age, PCs1-3 | — |
| PPM015029 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 8e-05 | age, PCs1-3 | — |
| PPM015030 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 2e-05 | age, PCs1-3 | — |
| PPM015031 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (internalising) | — | — | partial R²: 0.00023 | age, PCs1-3 | — |
| PPM015032 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (externalising) | — | — | partial R²: 3e-05 | age, PCs1-3 | — |
| PPM015041 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 1.46e-06 | age, PCs1-3 | — |
| PPM015004 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 anxety disorder) | — | — | partial R²: 6e-05 | age, PCs1-3 | — |
| PPM015012 | PGS002785 (SCZ_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00682 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015042 | PGS002785 (SCZ_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (stress) | — | — | partial R²: 0.00038 | age, PCs1-3 | — |
| PPM015053 | PGS002785 (SCZ_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00399 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015069 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 5e-05 | age, PCs1-3 | — |
| PPM015081 | PGS002786 (BD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00163 | age, PCs1-3 | — |
| PPM015092 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00017 | age, PCs1-3 | — |
| PPM015103 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.0005 | age, PCs1-3 | — |
| PPM015110 | PGS002786 (BD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture sequence) | — | — | partial R²: 0.00037 | age, PCs1-3 | — |
| PPM015115 | PGS002786 (BD_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 7e-05 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015131 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Dsm5 opppsit) | — | — | partial R²: 2.94e-06 | age, PCs1-3 | — |
| PPM015143 | PGS002787 (BD1_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00151 | age, PCs1-3 | — |
| PPM015154 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00026 | age, PCs1-3 | — |
| PPM015165 | PGS002787 (BD1_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.0001 | age, PCs1-3 | — |
| PPM015177 | PGS002787 (BD1_SDPR) |
PSS009951| European Ancestry| 78,561 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00012 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015178 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00052 | age, PCs1-3 | — |
| PPM015184 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (rule breaking) | — | — | partial R²: 0.00084 | age, PCs1-3 | — |
| PPM015195 | PGS002788 (BD2_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Sluggish cognitive tempo) | — | — | partial R²: 0.00307 | age, PCs1-3 | — |
| PPM015208 | PGS002788 (BD2_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 9.85e-06 | age, PCs1-10 | — |
| PPM015219 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00068 | age, PCs1-3 | — |
| PPM015229 | PGS002788 (BD2_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00035 | age, PCs1-3 | — |
| PPM015240 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (anxious/depressed) | — | — | partial R²: 0.00486 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015245 | PGS002789 (MDD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (attention problems) | — | — | partial R²: 0.00211 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015278 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (aggressive behaviour) | — | — | partial R²: 0.00498 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015298 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00067 | age, PCs1-3 | — |
| PPM015299 | PGS002789 (MDD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Crystallized composite) | — | — | partial R²: 0.00088 | age, PCs1-3 | — |
| PPM015312 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (total problems) | — | — | partial R²: 0.00075 | age, PCs1-3 | — |
| PPM015322 | PGS002790 (ASD_SDPR) |
PSS009950| European Ancestry| 2,524 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Picture vocabulary) | — | — | partial R²: 0.00168 | age, PCs1-3 | — |
| PPM015332 | PGS002790 (ASD_SDPR) |
PSS009953| European Ancestry| 68,614 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (fluid composite) | — | — | partial R²: 0.00026 | age, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015351 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Psychiatric behavior (Obsessive compulsive disorder) | — | — | partial R²: 0.00258 | age, PCs1-3 | the observed partial R² were higher than random R²s |
| PPM015362 | PGS002790 (ASD_SDPR) |
PSS009949| European Ancestry| 2,198 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Cognitive function (Cognitive total) | — | — | partial R²: 0.00021 | age, PCs1-3 | — |
| PPM015394 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_69 | — | — | partial R²: 0.00078 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015407 | PGS002785 (SCZ_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: ICA component_206 | — | — | partial R²: 0.00124 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM015414 | PGS002786 (BD_SDPR) |
PSS009952| European Ancestry| 10,343 individuals |
PGP000370 | Gui Y et al. Transl Psychiatry (2022) |
Reported Trait: Inferior fronto-occipital fasciculus R | — | — | partial R²: 0.00105 | age, headsize scaling factor, PCs1-10 | the observed partial R² were higher than random R²s |
| PPM014734 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009877| European Ancestry| 102,099 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.26 [1.19, 1.34] | C-index: 0.631 | ∆C-index (improvement in C-index over covariates-only model): 0.027 | age, sex, 5 PCs | — |
| PPM014735 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009877| European Ancestry| 102,099 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.12, 1.26] | C-index: 0.618 | ∆C-index (improvement in C-index over covariates-only model): 0.014 | age, sex, 5 PCs | — |
| PPM014743 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009880| African Ancestry| 3,434 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.07 [1.0, 1.15] | AUROC: 0.547 | ∆AUROC (improvement in AUROC over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014746 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.17 [1.11, 1.23] | AUROC: 0.641 | ∆AUROC (improvement in AUROC over covariates-only model): 0.007 | age, sex, 5 PCs | — |
| PPM014959 | PGS002759 (Depression_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Depression | OR: 1.26 [1.22, 1.3] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014960 | PGS002760 (Generalised_epilepsy_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Epilepsy | OR: 1.12 [1.05, 1.2] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014970 | PGS002770 (Stroke_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Stroke | OR: 1.15 [1.08, 1.22] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM015907 | PGS003322 (ExPRSweb_Insomnia_1160_DBSLMM_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 0.97 [0.931, 1.01] β: -0.0309 (0.0206) |
AUROC: 0.492 [0.481, 0.504] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015908 | PGS003319 (ExPRSweb_Insomnia_1160_LASSOSUM_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 0.978 [0.932, 1.028] β: -0.0217 (0.025) |
AUROC: 0.498 [0.486, 0.51] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015909 | PGS003321 (ExPRSweb_Insomnia_1160_PLINK_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 0.975 [0.934, 1.017] β: -0.0258 (0.0218) |
AUROC: 0.493 [0.481, 0.505] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015910 | PGS003323 (ExPRSweb_Insomnia_1160_PRSCS_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 0.988 [0.947, 1.031] β: -0.0122 (0.0218) |
AUROC: 0.499 [0.487, 0.511] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015911 | PGS003320 (ExPRSweb_Insomnia_1160_PT_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 0.977 [0.937, 1.02] β: -0.0228 (0.0218) |
AUROC: 0.494 [0.483, 0.505] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015912 | PGS003327 (ExPRSweb_Insomnia_1200_DBSLMM_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 1.038 [0.997, 1.081] β: 0.0375 (0.0206) |
AUROC: 0.51 [0.499, 0.521] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015913 | PGS003324 (ExPRSweb_Insomnia_1200_LASSOSUM_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 1.026 [0.985, 1.069] β: 0.0254 (0.0209) |
AUROC: 0.507 [0.496, 0.518] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015914 | PGS003326 (ExPRSweb_Insomnia_1200_PLINK_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 1.085 [1.041, 1.131] β: 0.0817 (0.021) |
AUROC: 0.522 [0.511, 0.534] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015915 | PGS003328 (ExPRSweb_Insomnia_1200_PRSCS_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 1.101 [1.056, 1.147] β: 0.096 (0.021) |
AUROC: 0.524 [0.513, 0.536] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015916 | PGS003325 (ExPRSweb_Insomnia_1200_PT_MGI_20211120) |
PSS010009| European Ancestry| 18,641 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Insomnia | OR: 1.092 [1.048, 1.137] β: 0.0876 (0.021) |
AUROC: 0.524 [0.512, 0.535] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016144 | PGS003333 (MDD-PRS) |
PSS010048| European Ancestry| 34,703 individuals |
PGP000399 | Fang Y et al. Biol Psychiatry (2022) |
Reported Trait: Major Depressive Disorder | — | — | Nagelkerke pseudo-R2: 0.022 | — | — |
| PPM016151 | PGS000039 (metaGRS_ischaemicstroke) |
PSS010050| Ancestry Not Reported| 454,756 individuals |
PGP000401 | Cho BPH et al. JAMA Neurol (2022) |Ext. |
Reported Trait: Stroke | HR: 1.23 [1.2, 1.26] | — | — | age, sex, ethnicity, exome sequencing batch, and the first 10 principal components of genetic ancestry | — |
| PPM016153 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident Alzheimer’s Disease | — | — | Hazard ratio (HR, high vs low tertile): 1.75 [1.58, 1.93] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016154 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident vascular dementia | — | — | Hazard ratio (HR, high vs low tertile): 1.55 [1.32, 1.82] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016155 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident dementia without cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 1.6 [1.48, 1.73] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016156 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident Alzheimer’s Disease without cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 1.84 [1.64, 2.07] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016152 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident dementia | — | — | Hazard ratio (HR, high vs low tertile): 1.5 [1.41, 1.6] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016157 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident vascular dementia without cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 1.63 [1.31, 2.03] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016158 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident dementia with cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 2.62 [2.36, 2.91] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016159 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident Alzheimer’s Disease with cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 2.38 [2.02, 2.81] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016160 | PGS003334 (PRS_dementia) |
PSS010051| European Ancestry| 204,646 individuals |
PGP000402 | Chen Y et al. Arch Gerontol Geriatr (2022) |
Reported Trait: Incident vascular dementia with cardiometabolic diseases | — | — | Hazard ratio (HR, high vs low tertile): 4.45 [3.47, 5.71] | Sex, age, education levels, socioeconomic status, body mass index (BMI), smoking status, alcohol intake frequency, physical activity, diet pattern, hypertension, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and C-reactive protein (CRP), and the first 10 principal components of ancestry | — |
| PPM016259 | PGS003384 (best_GBM) |
PSS010078| European Ancestry| 269,806 individuals |
PGP000413 | Namba S et al. Cancer Res (2022) |
Reported Trait: glioblastoma | — | AUROC: 0.758 | R²: 0.0216 | age, sex, top 20 genetic principal components | — |
| PPM017048 | PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard | HR: 1.344 | C-index: 0.652 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017049 | PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (men only) | HR: 1.254 | C-index: 0.571 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017050 | PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (women only) | HR: 1.374 | C-index: 0.727 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017051 | PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard | HR: 1.254 | C-index: 0.65 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017052 | PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (men only) | HR: 1.199 | C-index: 0.593 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017053 | PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (women only) | HR: 1.295 | C-index: 0.722 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017054 | PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases | OR: 1.094 | C-index: 0.763 | — | — | — |
| PPM017055 | PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (men only) | OR: 1.091 | C-index: 0.762 | — | — | — |
| PPM017056 | PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (women only) | OR: 1.089 | C-index: 0.77 | — | — | — |
| PPM017057 | PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases | OR: 1.124 | C-index: 0.764 | — | — | — |
| PPM017058 | PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (men only) | OR: 1.165 | C-index: 0.763 | — | — | — |
| PPM017059 | PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (women only) | OR: 1.085 | C-index: 0.77 | — | — | — |
| PPM000050 | PGS000025 (GRS) |
PSS000033| European Ancestry| 19,687 individuals |
PGP000015 | Chouraki V et al. J Alzheimers Dis (2016) |
Reported Trait: Incident Alzheimer's disease | HR: 1.17 [1.13, 1.21] | — | ΔC-index between models with and without GRS: 0.0043 [0.0019, 0.0067] | age at baseline, sex, education level, APOE Ɛ4 status | HRs are derived from a meta-analysis of studies (adjusted for study center, and participant relatedness) |
| PPM002215 | PGS000823 (GRS23_AD) |
PSS001080| European Ancestry| 12,255 individuals |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Reported Trait: Incident Alzheimer's disease at age 80 in individuals homozygous for APOE ε4 | — | — | Cumulative risk p-value (top 33.3% vs bottom 33.3%): 0.0056 | Non-Alzheimer's disease dementia, mortality | — |
| PPM002217 | PGS000823 (GRS23_AD) |
PSS001080| European Ancestry| 12,255 individuals |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Reported Trait: Incident Alzheimer's disease at age 85 | — | — | Cumulative risk p-value (top 33.3% vs bottom 33.3%): 7.90e-14 | Non-Alzheimer's disease dementia, mortality | — |
| PPM002214 | PGS000823 (GRS23_AD) |
PSS001080| European Ancestry| 12,255 individuals |
PGP000207 | van der Lee SJ et al. Lancet Neurol (2018) |
Reported Trait: Incident Alzheimer's disease at age 85 in individuals homozygous for APOE ε4 | — | — | Cumulative risk p-value (top 33.3% vs bottom 33.3%): 0.0085 | Non-Alzheimer's disease dementia, mortality | — |
| PPM009238 | PGS001775 (PRS39_AD) |
PSS007663| European Ancestry| 532 individuals |
PGP000255 | Ebenau JL et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Other dementia (excluding all-type dementia and Alzheimer's disease) | HR: 0.5 [0.3, 0.9] | — | — | Age, sex, population substructure, Mini-Mental State Examination (predictor: APOE ε4 allele or normalized PRS, outcome: clinical progression to dementia) | — |
| PPM009237 | PGS001775 (PRS39_AD) |
PSS007663| European Ancestry| 532 individuals |
PGP000255 | Ebenau JL et al. Alzheimers Dement (Amst) (2021) |
Reported Trait: Alzheimer's disease dementia | HR: 1.7 [1.1, 2.8] | — | — | Age, sex, population substructure, Mini-Mental State Examination (predictor: APOE ε4 allele or normalized PRS, outcome: clinical progression to dementia) | — |
| PPM017258 | PGS003457 (GRS_ICH) |
PSS010179| Multi-ancestry (including European)| 5,530 individuals |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Reported Trait: Incident intracerebral hemorrhage in anticoagulation therapy | HR: 1.24 [1.01, 1.53] | — | R²: 0.02 | age at baseline (controls) or ICH event (cases), sex, PC1 to 10, and genotyping array | — |
| PPM017259 | PGS003457 (GRS_ICH) |
PSS010179| Multi-ancestry (including European)| 5,530 individuals |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Reported Trait: Incident intracerebral hemorrhage in anticoagulation therapy | HR: 1.33 [1.11, 1.59] | C-index: 0.57 [0.5, 0.64] | — | age at baseline (controls) or ICH event (cases), sex, PC1 to 10, and genotyping array, clinical risk score | — |
| PPM018176 | PGS003574 (GRS_Dementia21) |
PSS010944| Multi-ancestry (including European)| 378,471 individuals |
PGP000459 | Mukadam N et al. PLoS One (2022) |
Reported Trait: Dementia | OR: 1.21 [1.18, 1.24] | — | — | age, sex, ethnic group, PRS*ethnicity | Excluding APOE variants |
| PPM018180 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00898 | PCs 1-10 | — |
| PPM018181 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00726 | PCs 1-10 | — |
| PPM018182 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0044 | PCs 1-10 | — |
| PPM018183 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00842 | PCs 1-10 | — |
| PPM018184 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00537 | PCs 1-10 | — |
| PPM018185 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0207 | PCs 1-10 | — |
| PPM018187 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00508 | PCs 1-20 | — |
| PPM018188 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0071 | PCs 1-20 | — |
| PPM018189 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01722 | PCs 1-20 | — |
| PPM018190 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01492 | PCs 1-10 | — |
| PPM018191 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00395 | PCs 1-10 | — |
| PPM018192 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00491 | PCs 1-10 | — |
| PPM018193 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00837 | PCs 1-10 | — |
| PPM018194 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00546 | PCs 1-10 | — |
| PPM018196 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0121 | PCs 1-10 | — |
| PPM018197 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01598 | PCs 1-20 | — |
| PPM018198 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02548 | PCs 1-20 | — |
| PPM018199 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01284 | PCs 1-20 | — |
| PPM018200 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00727 | PCs 1-10 | — |
| PPM018201 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01033 | PCs 1-10 | — |
| PPM018202 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00658 | PCs 1-10 | — |
| PPM018174 | PGS000902 (PRS90_PD) |
PSS010943| Ancestry Not Reported| 986 individuals |
PGP000458 | Pavelka L et al. NPJ Parkinsons Dis (2022) |Ext. |
Reported Trait: Age at onset of parkinson disease | — | — | Correlation: -0.11 | — | — |
| PPM018175 | PGS003574 (GRS_Dementia21) |
PSS010944| Multi-ancestry (including European)| 378,471 individuals |
PGP000459 | Mukadam N et al. PLoS One (2022) |
Reported Trait: Dementia | OR: 1.73 [1.69, 1.77] | — | — | age, sex, ethnic group, PRS*ethnicity | — |
| PPM018204 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00491 | PCs 1-10 | — |
| PPM018205 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0241 | PCs 1-10 | — |
| PPM018206 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0181 | PCs 1-10 | — |
| PPM018207 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01668 | PCs 1-20 | — |
| PPM018208 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02062 | PCs 1-20 | — |
| PPM018209 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01847 | PCs 1-20 | — |
| PPM018210 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01013 | PCs 1-10 | — |
| PPM018211 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00938 | PCs 1-10 | — |
| PPM018212 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00505 | PCs 1-10 | — |
| PPM018213 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00482 | PCs 1-10 | — |
| PPM018214 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00405 | PCs 1-10 | — |
| PPM018215 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0182 | PCs 1-10 | — |
| PPM018216 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0141 | PCs 1-10 | — |
| PPM018217 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00953 | PCs 1-20 | — |
| PPM018219 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01454 | PCs 1-20 | — |
| PPM018220 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00551 | PCs 1-10 | — |
| PPM018221 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01906 | PCs 1-10 | — |
| PPM018222 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00363 | PCs 1-10 | — |
| PPM018223 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00962 | PCs 1-10 | — |
| PPM018224 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00957 | PCs 1-10 | — |
| PPM018226 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0145 | PCs 1-10 | — |
| PPM018227 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01562 | PCs 1-20 | — |
| PPM018228 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01608 | PCs 1-20 | — |
| PPM018229 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01652 | PCs 1-20 | — |
| PPM018230 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00169 | PCs 1-10 | — |
| PPM018231 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00598 | PCs 1-10 | — |
| PPM018232 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00234 | PCs 1-10 | — |
| PPM018233 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00581 | PCs 1-10 | — |
| PPM018235 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0182 | PCs 1-10 | — |
| PPM018236 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0147 | PCs 1-10 | — |
| PPM018237 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01186 | PCs 1-20 | — |
| PPM018238 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01336 | PCs 1-20 | — |
| PPM018239 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01224 | PCs 1-20 | — |
| PPM018240 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00305 | PCs 1-10 | — |
| PPM018241 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01232 | PCs 1-10 | — |
| PPM018242 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00193 | PCs 1-10 | — |
| PPM018244 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00819 | PCs 1-10 | — |
| PPM018245 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0104 | PCs 1-10 | — |
| PPM018246 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0064 | PCs 1-10 | — |
| PPM018247 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00441 | PCs 1-20 | — |
| PPM018248 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01656 | PCs 1-20 | — |
| PPM018249 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01091 | PCs 1-20 | — |
| PPM018250 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00955 | PCs 1-10 | — |
| PPM018251 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02257 | PCs 1-10 | — |
| PPM018253 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0115 | PCs 1-10 | — |
| PPM018254 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01013 | PCs 1-10 | — |
| PPM018255 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0204 | PCs 1-10 | — |
| PPM018256 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0155 | PCs 1-10 | — |
| PPM018257 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01754 | PCs 1-20 | — |
| PPM018258 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01951 | PCs 1-20 | — |
| PPM018259 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01771 | PCs 1-20 | — |
| PPM018260 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00134 | PCs 1-10 | — |
| PPM018262 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00539 | PCs 1-10 | — |
| PPM018263 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01207 | PCs 1-10 | — |
| PPM018264 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00827 | PCs 1-10 | — |
| PPM018265 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0254 | PCs 1-10 | — |
| PPM018266 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0207 | PCs 1-10 | — |
| PPM018267 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02512 | PCs 1-20 | — |
| PPM018268 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01435 | PCs 1-20 | — |
| PPM018269 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02075 | PCs 1-20 | — |
| PPM018271 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01 | PCs 1-10 | — |
| PPM018272 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0048 | PCs 1-10 | — |
| PPM018273 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01087 | PCs 1-10 | — |
| PPM018274 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00943 | PCs 1-10 | — |
| PPM018275 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0257 | PCs 1-10 | — |
| PPM018276 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0199 | PCs 1-10 | — |
| PPM018277 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010951| African Ancestry| 687 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02024 | PCs 1-20 | — |
| PPM018278 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.02182 | PCs 1-20 | — |
| PPM018203 | PGS003576 (AutoImpAll.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01563 | PCs 1-10 | — |
| PPM018186 | PGS003584 (SoftImpAll.LifetimeMDD) |
PSS010955| European Ancestry| 23,351 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.016 | PCs 1-10 | — |
| PPM018195 | PGS003585 (SoftImpOnly.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0176 | PCs 1-10 | — |
| PPM018218 | PGS003577 (AutoImpOnly.LifetimeMDD) |
PSS010952| Additional Asian Ancestries| 334 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01605 | PCs 1-20 | — |
| PPM018225 | PGS003583 (MTAG.GPpsy.LifetimeMDD) |
PSS010954| European Ancestry| 42,250 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0198 | PCs 1-10 | — |
| PPM018234 | PGS003581 (MTAG.Envs.LifetimeMDD) |
PSS010950| East Asian Ancestry| 10,502 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00336 | PCs 1-10 | — |
| PPM018243 | PGS003582 (MTAG.FamHist.LifetimeMDD) |
PSS010949| Hispanic or Latin American Ancestry| 2,454 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00709 | PCs 1-10 | — |
| PPM018252 | PGS003579 (MTAG.AllDep.LifetimeMDD) |
PSS010948| European Ancestry| 14,388 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.00435 | PCs 1-10 | — |
| PPM018261 | PGS003580 (MTAG.AllDepEnvs.LifetimeMDD) |
PSS010947| Additional Asian Ancestries| 1,996 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0156 | PCs 1-10 | — |
| PPM018270 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010946| African Ancestry| 1,158 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.0038 | PCs 1-10 | — |
| PPM018279 | PGS003578 (MTAG.All.LifetimeMDD) |
PSS010953| European Ancestry| 10,193 individuals |
PGP000461 | Dahl A et al. bioRxiv (2022) |Pre |
Reported Trait: Major depressive disorder | — | — | R²: 0.01995 | PCs 1-20 | — |
| PPM018493 | PGS003737 (PRS26_BrC) |
PSS010987| European Ancestry| 890 individuals |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Reported Trait: Brain cancer | OR: 1.5 [1.38, 1.63] | — | — | — | — |
| PPM018515 | PGS003753 (PRS35445_ADHD) |
PSS011004| Hispanic or Latin American Ancestry| 237 individuals |
PGP000473 | Sato JR et al. Genes Brain Behav (2023) |
Reported Trait: ADHD scores from DAWBA questionnaire | β: 1.35e-06 | — | — | — | — |
| PPM018516 | PGS003753 (PRS35445_ADHD) |
PSS011004| Hispanic or Latin American Ancestry| 237 individuals |
PGP000473 | Sato JR et al. Genes Brain Behav (2023) |
Reported Trait: Segregation of brain functional network (cingulo-opercular network) | β: -3e-05 (1.28e-05) | — | — | — | — |
| PPM018517 | PGS003753 (PRS35445_ADHD) |
PSS011004| Hispanic or Latin American Ancestry| 237 individuals |
PGP000473 | Sato JR et al. Genes Brain Behav (2023) |
Reported Trait: Segregation of brain functional network (default mode) | β: 2e-05 (1.05e-05) | — | — | — | — |
| PPM018547 | PGS000902 (PRS90_PD) |
PSS011016| Multi-ancestry (including European)| 3,427 individuals |
PGP000479 | Blauwendraat C et al. Mov Disord (2023) |Ext. |
Reported Trait: Parkinson's disease | OR: 1.575 [1.444, 1.717] β: 0.4541 (0.0443) |
— | — | — | 85 of 90 variants of PGS000902 was used excluding full GBA1 region, and two additional variants (chr10:119776815:G:A and chr19:2341049:C:T) |
| PPM018548 | PGS000902 (PRS90_PD) |
PSS011017| Multi-ancestry (including European)| 225 individuals |
PGP000479 | Blauwendraat C et al. Mov Disord (2023) |Ext. |
Reported Trait: Parkinson's disease with Gaucher Disease | OR: 1.687 [1.099, 2.589] β: 0.5228 (0.2186) |
— | — | — | 85 of 90 variants of PGS000902 was used excluding full GBA1 region, and two additional variants (chr10:119776815:G:A and chr19:2341049:C:T) |
| PPM018556 | PGS002259 (metaPRS_Stroke) |
PSS011021| East Asian Ancestry| 41,006 individuals |
PGP000483 | Cui Q et al. Sci China Life Sci (2023) |Ext. |
Reported Trait: Incident stroke | — | — | Hazard ratio (HR, high vs low tertile): 3.01 [2.03, 4.45] | Sex, cohort | Age as the underlying time scale |
| PPM018557 | PGS002259 (metaPRS_Stroke) |
PSS011021| East Asian Ancestry| 41,006 individuals |
PGP000483 | Cui Q et al. Sci China Life Sci (2023) |Ext. |
Reported Trait: Incident stroke with high clinical risk | — | — | Hazard ratio (HR, high vs low tertile): 2.12 [1.38, 3.27] | Sex, cohort | Age as the underlying time scale |
| PPM018563 | PGS003763 (PRS44_PD) |
PSS011026| European Ancestry| 314,998 individuals |
PGP000486 | Zheng Z et al. JAMA Neurol (2023) |
Reported Trait: Incident Parkinson Disease | — | — | Hazard ratio (HR, high vs low tertile): 1.72 [1.54, 1.93] | genotyping array and the first 10 principal components of ancestry | — |
| PPM018564 | PGS003763 (PRS44_PD) |
PSS011026| European Ancestry| 314,998 individuals |
PGP000486 | Zheng Z et al. JAMA Neurol (2023) |
Reported Trait: Incident Parkinson Disease with frailty | — | — | Hazard ratio (HR, high vs low tertile): 3.22 [2.35, 4.41] | age, sex, Townsend deprivation index, assessment centers, alcohol consumption, smoking status, BMI, the number of long-term morbidities, genotyping array, and the first 10 principal components of ancestry long-term morbidities, genotyping array, and the first 10 principal components of ancestry | — |
| PPM019085 | PGS003955 (AD_Jun) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.15 [1.01, 1.31] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL-INCA visit, sex, study center, 5 principal components, and APOE-ϵ4 and APOE-ϵ2 allele counts | — |
| PPM019086 | PGS003957 (AD_Kunkle) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.34 [1.05, 1.71] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL-INCA visit, sex, study center, 5 principal components, and APOE-ϵ4 and APOE-ϵ2 allele counts | — |
| PPM019087 | PGS003956 (AD_Kunkle_AFR) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.14 [1.02, 1.28] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL-INCA visit, sex, study center, 5 principal components, and APOE-ϵ4 and APOE-ϵ2 allele counts | — |
| PPM019088 | PGS003953 (AD_Bellenguez) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.06 [0.96, 1.18] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL-INCA visit, sex, study center, 5 principal components, and APOE-ϵ4 and APOE-ϵ2 allele counts | — |
| PPM019089 | PGS003958 (AD_Unweighted_PRSsum) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.28 [1.12, 1.46] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL‑INCA visit, sex, study center, 5 principal components, and APOE‑E4 and APOE‑E2 allele counts | — |
| PPM019090 | PGS003953 (AD_Bellenguez) |
PSS011179| Multi-ancestry (including European)| 23,157 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment (with Alzheimer's disease) | OR: 1.13 (0.04) | — | — | two SNPs defining the APOE alleles | — |
| PPM019091 | PGS003958 (AD_Unweighted_PRSsum) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (SEVLT recall change) | β: -0.13 [-0.24, -0.02] | — | — | APOE alleles | — |
| PPM019092 | PGS003955 (AD_Jun) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (G-Factor change) | β: -0.03 [-0.06, -0.01] | — | — | — | — |
| PPM019093 | PGS003958 (AD_Unweighted_PRSsum) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (G-Factor change) | β: -0.04 [-0.06, -0.01] | — | — | — | — |
| PPM019094 | PGS003955 (AD_Jun) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (SEVLT recall change) | β: -0.09 [-0.17, -0.01] | — | — | — | — |
| PPM019095 | PGS003957 (AD_Kunkle) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (SEVLT recall change) | β: -0.2 [-0.4, 0.0] | — | — | — | — |
| PPM019096 | PGS003956 (AD_Kunkle_AFR) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Cognititve function (SEVLT recall change) | β: -0.08 [-0.17, 0.0] | — | — | — | — |
| PPM019084 | PGS003954 (AD_FINNGEN) |
PSS011180| Hispanic or Latin American Ancestry| 4,189 individuals |
PGP000503 | Sofer T et al. Alzheimers Res Ther (2023) |
Reported Trait: Mild cognitive impairment | OR: 1.19 [1.06, 1.33] | — | — | age at the HCHS/SOL baseline visit, time from HCHS/SOL baseline to the SOL-INCA visit, sex, study center, 5 principal components, and APOE-ϵ4 and APOE-ϵ2 allele counts | — |
| PPM019431 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11588 [1.08343617, 1.14930168] β: 0.10965 [0.08013763, 0.13915452] |
AUROC: 0.5311 [0.52258315, 0.53960799] | R²: 0.00249 [0.00124561, 0.00391129] | 0 | beta = log(or)/sd_pgs |
| PPM019432 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16332 [1.14877996, 1.17804017] β: 0.15128 [0.13870048, 0.16385218] |
AUROC: 0.54311 [0.53949521, 0.54672704] | R²: 0.00473 [0.00398409, 0.00555064] | 0 | beta = log(or)/sd_pgs |
| PPM019433 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1116 [1.01001276, 1.22340576] β: 0.1058 [0.00996296, 0.20163858] |
AUROC: 0.53257 [0.50585239, 0.55929704] | R²: 0.00172 [0.0000423, 0.00562594] | 0 | beta = log(or)/sd_pgs |
| PPM019434 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13921 [1.10739553, 1.17193764] β: 0.13033 [0.10201089, 0.15865848] |
AUROC: 0.53729 [0.52919837, 0.54537871] | R²: 0.00351 [0.002153, 0.00526917] | 0 | beta = log(or)/sd_pgs |
| PPM019435 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21092 [1.05660791, 1.38776963] β: 0.19138 [0.05506369, 0.32769787] |
AUROC: 0.5645 [0.52632653, 0.60268065] | R²: 0.00568 [0.000437, 0.01665509] | 0 | beta = log(or)/sd_pgs |
| PPM019436 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20936 [1.15728071, 1.26378987] β: 0.19009 [0.14607304, 0.23411504] |
AUROC: 0.55309 [0.54044775, 0.56573307] | R²: 0.00745 [0.00442536, 0.01118625] | 0 | beta = log(or)/sd_pgs |
| PPM019437 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08291 [1.0515096, 1.11523886] β: 0.07965 [0.05022684, 0.10906861] |
AUROC: 0.52243 [0.51400537, 0.53085786] | R²: 0.00132 [0.000512, 0.0024261] | 0 | beta = log(or)/sd_pgs |
| PPM019438 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06579 [1.05251543, 1.07923704] β: 0.06372 [0.05118295, 0.07625435] |
AUROC: 0.51814 [0.51449934, 0.52177675] | R²: 0.00084 [0.000519, 0.00120992] | 0 | beta = log(or)/sd_pgs |
| PPM019439 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.97393 [0.88492665, 1.07188237] β: -0.02642 [-0.1222505, 0.06941632] |
AUROC: 0.51051 [0.4829624, 0.53805337] | R²: 0.00011 [0.0, 0.00229604] | 0 | beta = log(or)/sd_pgs |
| PPM019440 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06709 [1.03737253, 1.09765048] β: 0.06493 [0.0366911, 0.09317197] |
AUROC: 0.5176 [0.50942967, 0.5257663] | R²: 0.00088 [0.00027871, 0.00193499] | 0 | beta = log(or)/sd_pgs |
| PPM019441 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.99729 [0.87003302, 1.1431701] β: -0.00271 [-0.1392241, 0.13380519] |
AUROC: 0.49948 [0.4589389, 0.54002276] | R²: 1.14e-06 [0.0, 0.00307562] | 0 | beta = log(or)/sd_pgs |
| PPM019442 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08405 [1.03738951, 1.13280412] β: 0.0807 [0.03670747, 0.12469608] |
AUROC: 0.52424 [0.51165085, 0.53683071] | R²: 0.00134 [0.0003, 0.00302841] | 0 | beta = log(or)/sd_pgs |
| PPM019443 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06894 [1.03785867, 1.10095983] β: 0.06667 [0.03715962, 0.09618237] |
AUROC: 0.51987 [0.51135121, 0.52838787] | R²: 0.00092 [0.00032, 0.00188246] | 0 | beta = log(or)/sd_pgs |
| PPM019444 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10078 [1.08703793, 1.11469876] β: 0.09602 [0.0834565, 0.1085842] |
AUROC: 0.527 [0.52339166, 0.53061368] | R²: 0.00191 [0.00143669, 0.00245807] | 0 | beta = log(or)/sd_pgs |
| PPM019445 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12773 [1.02478049, 1.24102559] β: 0.12021 [0.02447843, 0.21593812] |
AUROC: 0.53267 [0.5056658, 0.55967946] | R²: 0.00223 [0.00015, 0.00674387] | 0 | beta = log(or)/sd_pgs |
| PPM019446 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.1023 [0.07398085, 0.13062111] OR: 1.10772 [1.07678618, 1.13953594] |
AUROC: 0.52919 [0.52105192, 0.53732734] | R²: 0.00216 [0.00113918, 0.003649] | 0 | beta = log(or)/sd_pgs |
| PPM019447 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14403 [0.99833483, 1.31097774] β: 0.13455 [-0.0016666, 0.27077322] |
AUROC: 0.54498 [0.50570189, 0.58425451] | R²: 0.00281 [0.0, 0.01104227] | 0 | beta = log(or)/sd_pgs |
| PPM019448 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13266 [1.08394966, 1.18356209] β: 0.12457 [0.08061146, 0.16852861] |
AUROC: 0.53537 [0.52278904, 0.54795879] | R²: 0.00321 [0.00129459, 0.00578736] | 0 | beta = log(or)/sd_pgs |
| PPM019449 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12083 [1.08824491, 1.15438327] β: 0.11407 [0.08456622, 0.14356623] |
AUROC: 0.53316 [0.52473906, 0.54158598] | R²: 0.00269 [0.00138125, 0.00425231] | 0 | beta = log(or)/sd_pgs |
| PPM019450 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15341 [1.13900681, 1.16800282] β: 0.14273 [0.13015666, 0.1552953] |
AUROC: 0.54057 [0.53695, 0.54418221] | R²: 0.00422 [0.00347622, 0.00499623] | 0 | beta = log(or)/sd_pgs |
| PPM019451 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09189 [0.99222365, 1.20156871] β: 0.08791 [-0.0078067, 0.18362796] |
AUROC: 0.52519 [0.49747233, 0.55290272] | R²: 0.00119 [0.0, 0.00512013] | 0 | beta = log(or)/sd_pgs |
| PPM019452 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12141 [1.09009411, 1.15362816] β: 0.11459 [0.08626403, 0.1429119] |
AUROC: 0.53176 [0.52370534, 0.53981953] | R²: 0.00271 [0.00155187, 0.00420533] | 0 | beta = log(or)/sd_pgs |
| PPM019453 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18126 [1.0309514, 1.3534912] β: 0.16658 [0.03048206, 0.30268733] |
AUROC: 0.54628 [0.50596882, 0.58659045] | R²: 0.00432 [0.0000589, 0.0151188] | 0 | beta = log(or)/sd_pgs |
| PPM019454 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20912 [1.15705376, 1.26353856] β: 0.1899 [0.14587692, 0.23391617] |
AUROC: 0.55395 [0.54139946, 0.56649182] | R²: 0.00744 [0.00445914, 0.01137928] | 0 | beta = log(or)/sd_pgs |
| PPM019455 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08855 [1.05690373, 1.12115148] β: 0.08485 [0.05534362, 0.11435627] |
AUROC: 0.52349 [0.51495565, 0.53202719] | R²: 0.00149 [0.000605, 0.00274949] | 0 | beta = log(or)/sd_pgs |
| PPM019456 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14381 [1.12951156, 1.15828947] β: 0.13436 [0.1217853, 0.14694432] |
AUROC: 0.53828 [0.53466313, 0.5419004] | R²: 0.00373 [0.00305951, 0.00454449] | 0 | beta = log(or)/sd_pgs |
| PPM019457 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09703 [0.99682003, 1.20732376] β: 0.09261 [-0.003185, 0.18840614] |
AUROC: 0.5291 [0.50288518, 0.55530775] | R²: 0.00132 [0.00000145, 0.00481747] | 0 | beta = log(or)/sd_pgs |
| PPM019458 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09561 [1.06503669, 1.12705809] β: 0.09131 [0.06300925, 0.11961078] |
AUROC: 0.52636 [0.518281, 0.53443847] | R²: 0.00173 [0.000859, 0.0029266] | 0 | beta = log(or)/sd_pgs |
| PPM019459 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15035 [1.00389913, 1.31816921] β: 0.14007 [0.00389155, 0.27624381] |
AUROC: 0.546 [0.50679306, 0.5852031] | R²: 0.00305 [0.00000558, 0.0114294] | 0 | beta = log(or)/sd_pgs |
| PPM019460 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20185 [1.1499474, 1.25608606] β: 0.18386 [0.1397162, 0.22800058] |
AUROC: 0.55073 [0.53804918, 0.56340897] | R²: 0.00693 [0.00408496, 0.01084329] | 0 | beta = log(or)/sd_pgs |
| PPM019927 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.79245 [1.71513669, 1.87323956] β: 0.58358 [0.53949278, 0.62766932] |
AUROC: 0.67094 [0.65667793, 0.68519515] | R²: 0.06987 [0.05877563, 0.08216167] | 0 | beta = log(or)/sd_pgs |
| PPM019462 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17327 [1.15860257, 1.18812042] β: 0.15979 [0.1472146, 0.17237258] |
AUROC: 0.54565 [0.54203694, 0.54925403] | R²: 0.00528 [0.00445693, 0.00618855] | 0 | beta = log(or)/sd_pgs |
| PPM019463 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08287 [0.98396133, 1.19171469] β: 0.07961 [-0.0161687, 0.17539318] |
AUROC: 0.52297 [0.49629776, 0.54965208] | R²: 0.00098 [0.0, 0.00425361] | 0 | beta = log(or)/sd_pgs |
| PPM019464 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14197 [1.11007941, 1.17478122] β: 0.13276 [0.10443155, 0.16108194] |
AUROC: 0.53789 [0.52982296, 0.5459495] | R²: 0.00364 [0.00225276, 0.00536145] | 0 | beta = log(or)/sd_pgs |
| PPM019466 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23115 [1.17806817, 1.28661969] β: 0.20795 [0.16387596, 0.25201838] |
AUROC: 0.55734 [0.54468967, 0.56999809] | R²: 0.0089 [0.00560709, 0.01298353] | 0 | beta = log(or)/sd_pgs |
| PPM019467 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10756 [1.07535568, 1.14073718] β: 0.10216 [0.07265147, 0.13167471] |
AUROC: 0.5292 [0.52067772, 0.53772878] | R²: 0.00216 [0.00102377, 0.00349455] | 0 | beta = log(or)/sd_pgs |
| PPM019468 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16199 [1.1474617, 1.17669591] β: 0.15013 [0.13755229, 0.16271043] |
AUROC: 0.5426 [0.53897714, 0.5462198] | R²: 0.00466 [0.00392453, 0.00548885] | 0 | beta = log(or)/sd_pgs |
| PPM019469 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13492 [1.03111003, 1.24918283] β: 0.12656 [0.03063592, 0.2224896] |
AUROC: 0.53686 [0.51016061, 0.56355653] | R²: 0.00246 [0.000238, 0.00707626] | 0 | beta = log(or)/sd_pgs |
| PPM019470 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1247 [1.09330509, 1.15699978] β: 0.11752 [0.08920531, 0.14583026] |
AUROC: 0.53363 [0.52552193, 0.54173886] | R²: 0.00286 [0.00168306, 0.0043577] | 0 | beta = log(or)/sd_pgs |
| PPM019471 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23606 [1.07905703, 1.41590013] β: 0.21193 [0.07608754, 0.34776547] |
AUROC: 0.56859 [0.52989812, 0.60728942] | R²: 0.00702 [0.000879, 0.01908019] | 0 | beta = log(or)/sd_pgs |
| PPM019472 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21946 [1.16691439, 1.27436893] β: 0.19841 [0.154363, 0.2424511] |
AUROC: 0.55462 [0.54203646, 0.56719931] | R²: 0.00811 [0.00490666, 0.01217568] | 0 | beta = log(or)/sd_pgs |
| PPM019473 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.11337 [0.0838625, 0.14287805] OR: 1.12005 [1.08747936, 1.15358912] |
AUROC: 0.53265 [0.52410638, 0.54119598] | R²: 0.00266 [0.00137051, 0.00420657] | 0 | beta = log(or)/sd_pgs |
| PPM019474 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16971 [1.15508988, 1.18450788] β: 0.15675 [0.14417816, 0.16932739] |
AUROC: 0.54467 [0.54105858, 0.54827219] | R²: 0.00508 [0.00428569, 0.00597661] | 0 | beta = log(or)/sd_pgs |
| PPM019475 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09218 [0.99244315, 1.20193532] β: 0.08817 [-0.0075855, 0.18393302] |
AUROC: 0.52469 [0.49822599, 0.55115016] | R²: 0.0012 [0.0, 0.00477209] | 0 | beta = log(or)/sd_pgs |
| PPM019476 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1469 [1.11485209, 1.17987041] β: 0.13706 [0.10872174, 0.16540461] |
AUROC: 0.53902 [0.53097366, 0.54705807] | R²: 0.00388 [0.00235764, 0.00565486] | 0 | beta = log(or)/sd_pgs |
| PPM019477 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23492 [1.07805871, 1.41460106] β: 0.211 [0.07516194, 0.34684756] |
AUROC: 0.56842 [0.52959783, 0.60723511] | R²: 0.00696 [0.000789, 0.01932319] | 0 | beta = log(or)/sd_pgs |
| PPM019478 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21483 [1.16243507, 1.26958012] β: 0.1946 [0.15051701, 0.23868624] |
AUROC: 0.55421 [0.54154316, 0.56688511] | R²: 0.00779 [0.00457599, 0.01180516] | 0 | beta = log(or)/sd_pgs |
| PPM019479 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12262 [1.08997461, 1.15624017] β: 0.11566 [0.0861544, 0.1451735] |
AUROC: 0.53342 [0.52488642, 0.54195793] | R²: 0.00277 [0.00147025, 0.00431716] | 0 | beta = log(or)/sd_pgs |
| PPM019480 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17236 [1.15771305, 1.18719934] β: 0.15902 [0.14644655, 0.17159704] |
AUROC: 0.54524 [0.54162844, 0.54884559] | R²: 0.00523 [0.00440696, 0.00610806] | 0 | beta = log(or)/sd_pgs |
| PPM019481 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09524 [0.99518242, 1.20534758] β: 0.09097 [-0.0048292, 0.18676797] |
AUROC: 0.52535 [0.49869346, 0.55200012] | R²: 0.00128 [0.00000209, 0.00487633] | 0 | beta = log(or)/sd_pgs |
| PPM019482 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14508 [1.11308982, 1.17799207] β: 0.13548 [0.10713977, 0.16381135] |
AUROC: 0.53866 [0.53061568, 0.54669435] | R²: 0.00379 [0.00230863, 0.00554488] | 0 | beta = log(or)/sd_pgs |
| PPM019483 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.24252 [1.08479041, 1.42318679] β: 0.21714 [0.08138679, 0.35289857] |
AUROC: 0.56986 [0.53098801, 0.60872389] | R²: 0.00738 [0.000997, 0.02006623] | 0 | beta = log(or)/sd_pgs |
| PPM019484 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.22477 [1.1719543, 1.27996152] β: 0.20275 [0.1586727, 0.24683001] |
AUROC: 0.55628 [0.54365516, 0.56889903] | R²: 0.00845 [0.0051498, 0.01257724] | 0 | beta = log(or)/sd_pgs |
| PPM019485 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10211 [1.07007216, 1.13510722] β: 0.09723 [0.06772609, 0.12672711] |
AUROC: 0.52781 [0.51930204, 0.53632099] | R²: 0.00196 [0.00095, 0.00333554] | 0 | beta = log(or)/sd_pgs |
| PPM019486 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15335 [1.13893748, 1.16794189] β: 0.14267 [0.1300958, 0.15524313] |
AUROC: 0.54022 [0.53659848, 0.54383588] | R²: 0.00421 [0.00351947, 0.00498262] | 0 | beta = log(or)/sd_pgs |
| PPM019487 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14227 [1.03770693, 1.25736482] β: 0.13302 [0.03701341, 0.22901812] |
AUROC: 0.54029 [0.51369443, 0.56688289] | R²: 0.00272 [0.000301, 0.00753558] | 0 | beta = log(or)/sd_pgs |
| PPM019488 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11617 [1.08500902, 1.14821592] β: 0.1099 [0.0815883, 0.13820937] |
AUROC: 0.53213 [0.52404907, 0.54020559] | R²: 0.0025 [0.00141635, 0.00391061] | 0 | beta = log(or)/sd_pgs |
| PPM019489 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23173 [1.07615164, 1.40980329] β: 0.20842 [0.07339138, 0.34345019] |
AUROC: 0.56612 [0.52672065, 0.60551542] | R²: 0.00686 [0.000655, 0.01792159] | 0 | beta = log(or)/sd_pgs |
| PPM019490 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.19231 [1.14094472, 1.24597857] β: 0.17589 [0.13185662, 0.21992122] |
AUROC: 0.54928 [0.53668704, 0.56187681] | R²: 0.00637 [0.00353314, 0.00992459] | 0 | beta = log(or)/sd_pgs |
| PPM019491 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10161 [1.06958778, 1.13458485] β: 0.09677 [0.06727333, 0.12626681] |
AUROC: 0.52784 [0.51933058, 0.53634845] | R²: 0.00194 [0.000893, 0.00326912] | 0 | beta = log(or)/sd_pgs |
| PPM019492 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15354 [1.13912614, 1.16813032] β: 0.14283 [0.13026142, 0.15540445] |
AUROC: 0.54048 [0.53685753, 0.54410481] | R²: 0.00422 [0.0034919, 0.00502618] | 0 | beta = log(or)/sd_pgs |
| PPM019493 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1249 [1.02197512, 1.23819444] β: 0.1177 [0.02173715, 0.21365422] |
AUROC: 0.5344 [0.5074307, 0.56137249] | R²: 0.00213 [0.000118, 0.00670413] | 0 | beta = log(or)/sd_pgs |
| PPM019494 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10581 [1.0749525, 1.13755428] β: 0.10058 [0.07227647, 0.12888059] |
AUROC: 0.52957 [0.52148152, 0.53766659] | R²: 0.00209 [0.00111885, 0.00347131] | 0 | beta = log(or)/sd_pgs |
| PPM019495 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23758 [1.08131404, 1.41642239] β: 0.21316 [0.078177, 0.34813425] |
AUROC: 0.56725 [0.52859169, 0.60591655] | R²: 0.00718 [0.000735, 0.0191671] | 0 | beta = log(or)/sd_pgs |
| PPM019496 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20497 [1.15317504, 1.25910106] β: 0.18646 [0.14251904, 0.23039802] |
AUROC: 0.55291 [0.54034145, 0.56548567] | R²: 0.00719 [0.00426528, 0.01097952] | 0 | beta = log(or)/sd_pgs |
| PPM019497 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09992 [1.06793864, 1.13285627] β: 0.09524 [0.06573028, 0.12474211] |
AUROC: 0.52666 [0.51816735, 0.53515816] | R²: 0.00188 [0.000883, 0.00325281] | 0 | beta = log(or)/sd_pgs |
| PPM019499 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.03582 [0.94136503, 1.13975765] β: 0.0352 [-0.0604243, 0.13081565] |
AUROC: 0.50962 [0.48298884, 0.53625086] | R²: 0.00019 [0.0, 0.00223248] | 0 | beta = log(or)/sd_pgs |
| PPM019500 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.11869 [0.09034983, 0.14703744] OR: 1.12602 [1.09455712, 1.15839733] |
AUROC: 0.53372 [0.52560348, 0.541837] | R²: 0.00291 [0.00175846, 0.00438719] | 0 | beta = log(or)/sd_pgs |
| PPM019501 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.05895 [0.92378141, 1.21390666] β: 0.05728 [-0.0792798, 0.1938438] |
AUROC: 0.51989 [0.48202597, 0.55775222] | R²: 0.00051 [0.0, 0.00614416] | 0 | beta = log(or)/sd_pgs |
| PPM019502 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12993 [1.08122629, 1.18082159] β: 0.12215 [0.07809585, 0.16621046] |
AUROC: 0.53743 [0.52459314, 0.55027481] | R²: 0.00307 [0.00128569, 0.00553223] | 0 | beta = log(or)/sd_pgs |
| PPM019503 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10789 [1.07566831, 1.14107726] β: 0.10246 [0.07294215, 0.13197278] |
AUROC: 0.52857 [0.52001445, 0.53712397] | R²: 0.00217 [0.00104555, 0.00351577] | 0 | beta = log(or)/sd_pgs |
| PPM019504 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14267 [1.12839302, 1.15713496] β: 0.13337 [0.12079452, 0.14594709] |
AUROC: 0.53782 [0.53420355, 0.54143959] | R²: 0.00368 [0.00303669, 0.00446067] | 0 | beta = log(or)/sd_pgs |
| PPM019505 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10577 [1.00477493, 1.21692241] β: 0.10054 [0.00476357, 0.19632506] |
AUROC: 0.53471 [0.50835875, 0.56105638] | R²: 0.00156 [0.0000331, 0.00511287] | 0 | beta = log(or)/sd_pgs |
| PPM019506 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12027 [1.08897574, 1.15246834] β: 0.11357 [0.08523757, 0.14190602] |
AUROC: 0.5326 [0.52447165, 0.54073587] | R²: 0.00266 [0.00147464, 0.00427621] | 0 | beta = log(or)/sd_pgs |
| PPM019507 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18187 [1.03090876, 1.35493138] β: 0.1671 [0.0304407, 0.30375081] |
AUROC: 0.55554 [0.51834024, 0.59273181] | R²: 0.00431 [0.000121, 0.01349001] | 0 | beta = log(or)/sd_pgs |
| PPM019508 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17792 [1.12708219, 1.2310461] β: 0.16375 [0.11963216, 0.2078643] |
AUROC: 0.5452 [0.53247659, 0.557919] | R²: 0.00551 [0.00285031, 0.0090806] | 0 | beta = log(or)/sd_pgs |
| PPM019928 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.45859 [1.35624817, 1.56865365] β: 0.37747 [0.30472219, 0.4502177] |
AUROC: 0.60532 [0.5803355, 0.63030351] | R²: 0.02833 [0.01664267, 0.04228284] | 0 | beta = log(or)/sd_pgs |
| PPM019929 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.5321 [1.50892339, 1.55564048] β: 0.42664 [0.41139641, 0.44188734] |
AUROC: 0.6237 [0.61877662, 0.62862975] | R²: 0.0349 [0.03207661, 0.03776512] | 0 | beta = log(or)/sd_pgs |
| PPM019919 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.27295 [1.16877898, 1.38640714] β: 0.24134 [0.1559596, 0.32671561] |
AUROC: 0.57002 [0.54493965, 0.59509681] | R²: 0.00829 [0.00313542, 0.01593775] | 0 | beta = log(or)/sd_pgs |
| PPM019920 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.2393 [1.21794864, 1.26102083] β: 0.21454 [0.197168, 0.23192158] |
AUROC: 0.5606 [0.55574503, 0.56545085] | R²: 0.00659 [0.00548578, 0.00774337] | 0 | beta = log(or)/sd_pgs |
| PPM019921 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.44592 [1.3726573, 1.52309192] β: 0.36875 [0.3167485, 0.42074243] |
AUROC: 0.60208 [0.58755709, 0.61660009] | R²: 0.01898 [0.01397656, 0.02489353] | 0 | beta = log(or)/sd_pgs |
| PPM019922 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.36764 [1.25914746, 1.48548255] β: 0.31309 [0.23043487, 0.39573967] |
AUROC: 0.58889 [0.56427113, 0.61350965] | R²: 0.0149 [0.00821494, 0.02493823] | 0 | beta = log(or)/sd_pgs |
| PPM019923 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.33446 [1.31203429, 1.35726497] β: 0.28853 [0.27157882, 0.30547162] |
AUROC: 0.58137 [0.57651307, 0.5862179] | R²: 0.01256 [0.01098677, 0.01400605] | 0 | beta = log(or)/sd_pgs |
| PPM019924 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.59974 [1.52182949, 1.6816393] β: 0.46984 [0.41991323, 0.51976909] |
AUROC: 0.6315 [0.61718444, 0.64582464] | R²: 0.03367 [0.02663668, 0.04154769] | 0 | beta = log(or)/sd_pgs |
| PPM019931 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.46172 [1.35265857, 1.57957283] β: 0.37961 [0.30207197, 0.45715445] |
AUROC: 0.60579 [0.58137466, 0.63020687] | R²: 0.02494 [0.01482857, 0.03780255] | 0 | beta = log(or)/sd_pgs |
| PPM019933 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.73895 [1.66108385, 1.82046629] β: 0.55328 [0.50747031, 0.59909267] |
AUROC: 0.66036 [0.64617344, 0.67454912] | R²: 0.05664 [0.04705507, 0.0684223] | 0 | beta = log(or)/sd_pgs |
| PPM019934 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.50751 [1.39408288, 1.63015587] β: 0.41046 [0.33223677, 0.48867563] |
AUROC: 0.61363 [0.58940298, 0.63785059] | R²: 0.02861 [0.0178852, 0.04157816] | 0 | beta = log(or)/sd_pgs |
| PPM019935 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.48977 [1.46572255, 1.51421327] β: 0.39862 [0.38234833, 0.41489601] |
AUROC: 0.61238 [0.60749418, 0.61727359] | R²: 0.02623 [0.02395749, 0.02862116] | 0 | beta = log(or)/sd_pgs |
| PPM019936 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.77852 [1.69732301, 1.86359553] β: 0.57578 [0.52905231, 0.6225077] |
AUROC: 0.66492 [0.65074397, 0.67909054] | R²: 0.05886 [0.04942013, 0.07017009] | 0 | beta = log(or)/sd_pgs |
| PPM019937 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.42671 [1.32526095, 1.53593273] β: 0.35537 [0.28160939, 0.42913784] |
AUROC: 0.59847 [0.57332316, 0.62362478] | R²: 0.02435 [0.01341092, 0.03701681] | 0 | beta = log(or)/sd_pgs |
| PPM019938 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.48397 [1.46157064, 1.50671708] β: 0.39472 [0.37951164, 0.40993316] |
AUROC: 0.61454 [0.60960208, 0.61948354] | R²: 0.02982 [0.02725224, 0.03259812] | 0 | beta = log(or)/sd_pgs |
| PPM019939 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.73288 [1.65911417, 1.80992965] β: 0.54979 [0.50628383, 0.59328798] |
AUROC: 0.66293 [0.64863592, 0.6772318] | R²: 0.06348 [0.05374272, 0.0761614] | 0 | beta = log(or)/sd_pgs |
| PPM020218 | PGS004227 (ad_apoe_gw_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) | β: -0.06101 [-0.108607308, -0.013407489] | — | — | — | — |
| PPM020223 | PGS004229 (ad_noapoe_0.1_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (linolenate (18:3n3 or 3n6)) | β: -0.05431 [-0.103025695, -0.005590157] | — | — | — | — |
| PPM020220 | PGS004227 (ad_apoe_gw_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (palmitoyl-myristoyl-glycerol (16:0/14:0) [1]) | β: -0.0502 [-0.098164771, -0.002232543] | — | — | — | — |
| PPM020222 | PGS004229 (ad_noapoe_0.1_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (docosapentaenoate (DPA; 22:5n3)) | β: -0.07733 [-0.125825807, -0.028839878] | — | — | — | — |
| PPM020273 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011318| African Ancestry| 18,505 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.05 [0.95, 1.17] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020274 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011319| Hispanic or Latin American Ancestry| 6,785 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.08 [0.85, 1.36] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020275 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011320| European Ancestry| 53,861 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.15 [1.08, 1.21] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020219 | PGS004227 (ad_apoe_gw_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (palmitoyl-palmitoyl-glycerol (16:0/16:0) [1]) | β: -0.0559 [-0.103719741, -0.008088708] | — | — | — | — |
| PPM020221 | PGS004228 (ad_apoe_0.1_pgs) |
PSS011307| Ancestry Not Reported| 1,638 individuals |
PGP000527 | Green RE et al. Alzheimers Res Ther (2023) |
Reported Trait: Alzheimer's disease biomarker (docosapentaenoate (DPA; 22:5n3)) | β: -0.05808 [-0.106496039, -0.009669554] | — | — | — | — |
| PPM020316 | PGS002249 (AD_PRS_0.5) |
PSS011330| European Ancestry| 196,368 individuals |
PGP000543 | Klee M et al. Am J Prev Med (2023) |Ext. |
Reported Trait: Incident dementia with area-level socioeconomic deprivation | — | — | Hazard ratio (HR, high deprivation and PRS in top quintile vs. low-moderate deprivation and PRS in bottom quintile): 2.31 [1.84, 2.91] | 20 first PCs, third-degree relatedness, number of alleles used to compute PRS, age, sex, education, marital status, healthy lifestyle, depressive symptoms in the last 2 weeks, individual-level deprivation | — |
| PPM020317 | PGS002249 (AD_PRS_0.5) |
PSS011330| European Ancestry| 196,368 individuals |
PGP000543 | Klee M et al. Am J Prev Med (2023) |Ext. |
Reported Trait: Incident dementia with individual-level socioeconomic deprivation | — | — | Hazard ratio (HR, high deprivation and PRS in top quintile vs. low-moderate deprivation and PRS in bottom quintile): 4.06 [2.63, 6.26] | 20 first PCs, third-degree relatedness, number of alleles used to compute PRS, age, sex, education, marital status, healthy lifestyle, depressive symptoms in the last 2 weeks, area-level deprivation | — |
| PPM020349 | PGS004281 (GenoBoost_all-cause_dementia_1) |
PSS011345| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: All-cause dementia | — | AUROC: 0.81897 | Covariate-adjusted pseudo-R2: 0.03418 AUPRC: 0.81897 |
age, sex, PC1-10 | — |
| PPM020350 | PGS004282 (GenoBoost_all-cause_dementia_2) |
PSS011345| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: All-cause dementia | — | AUROC: 0.81837 | Covariate-adjusted pseudo-R2: 0.03323 AUPRC: 0.81837 |
age, sex, PC1-10 | — |
| PPM020351 | PGS004283 (GenoBoost_all-cause_dementia_3) |
PSS011345| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: All-cause dementia | — | AUROC: 0.81816 | Covariate-adjusted pseudo-R2: 0.03381 AUPRC: 0.81816 |
age, sex, PC1-10 | — |
| PPM020352 | PGS004284 (GenoBoost_all-cause_dementia_4) |
PSS011345| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: All-cause dementia | — | AUROC: 0.81886 | Covariate-adjusted pseudo-R2: 0.03415 AUPRC: 0.81886 |
age, sex, PC1-10 | — |
| PPM020353 | PGS004285 (GenoBoost_alzheimer_s_disease_0) |
PSS011336| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.8336 | Covariate-adjusted pseudo-R2: 0.0421 AUPRC: 0.8336 |
age, sex, PC1-10 | — |
| PPM020354 | PGS004286 (GenoBoost_alzheimer_s_disease_1) |
PSS011336| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.8321 | Covariate-adjusted pseudo-R2: 0.04019 AUPRC: 0.8321 |
age, sex, PC1-10 | — |
| PPM020355 | PGS004287 (GenoBoost_alzheimer_s_disease_2) |
PSS011336| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.83179 | Covariate-adjusted pseudo-R2: 0.04182 AUPRC: 0.83179 |
age, sex, PC1-10 | — |
| PPM020357 | PGS004289 (GenoBoost_alzheimer_s_disease_4) |
PSS011336| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.83162 | Covariate-adjusted pseudo-R2: 0.04076 AUPRC: 0.83162 |
age, sex, PC1-10 | — |
| PPM019930 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.78882 [1.71250526, 1.86854552] β: 0.58156 [0.53795736, 0.62516033] |
AUROC: 0.67205 [0.65778828, 0.68630804] | R²: 0.07132 [0.06110042, 0.08413551] | 0 | beta = log(or)/sd_pgs |
| PPM019925 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.48544 [1.37939815, 1.59962905] β: 0.39571 [0.32164728, 0.46977176] |
AUROC: 0.60796 [0.58278903, 0.63313316] | R²: 0.03003 [0.01833361, 0.04547365] | 0 | beta = log(or)/sd_pgs |
| PPM019926 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.52213 [1.49865179, 1.54596874] β: 0.42011 [0.40456589, 0.43565073] |
AUROC: 0.62099 [0.61607908, 0.6259011] | R²: 0.03241 [0.02967044, 0.03503408] | 0 | beta = log(or)/sd_pgs |
| PPM019461 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12873 [1.09591702, 1.16253397] β: 0.1211 [0.09159147, 0.15060208] |
AUROC: 0.53509 [0.52657818, 0.54361127] | R²: 0.00303 [0.00161439, 0.00460309] | 0 | beta = log(or)/sd_pgs |
| PPM019465 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18096 [1.03046264, 1.35342652] β: 0.16632 [0.03000786, 0.30263954] |
AUROC: 0.55516 [0.51584288, 0.59448045] | R²: 0.00429 [0.000133, 0.01465822] | 0 | beta = log(or)/sd_pgs |
| PPM019498 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12015 [1.10615947, 1.134316] β: 0.11346 [0.10089408, 0.12602982] |
AUROC: 0.53218 [0.52855431, 0.53580164] | R²: 0.00266 [0.00209727, 0.00327205] | 0 | beta = log(or)/sd_pgs |
| PPM019932 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: AD | OR: 1.48022 [1.45673427, 1.50408347] β: 0.39219 [0.37619713, 0.40818372] |
AUROC: 0.61101 [0.6061323, 0.6158922] | R²: 0.02634 [0.02407498, 0.02873899] | 0 | beta = log(or)/sd_pgs |
| PPM020398 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Alzheimer's disease | — | — | Hazard ratio (HR, high vs low PRS tertile): 4.11 [3.71, 4.54] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020399 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Vascular dementia | — | — | Hazard ratio (HR, high vs low PRS tertile): 2.43 [2.15, 2.75] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020400 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Dementia with high laxatives exposure | — | — | Hazard ratio (HR, high laxative use and PRS in top tertile vs no laxative use and PRS in bottom tertile): 4.09 [3.48, 4.81] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020401 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Alzheimer's disease with high laxatives exposure | — | — | Hazard ratio (HR, high laxative use and PRS in top tertile vs no laxative use and PRS in bottom tertile): 4.62 [3.56, 6.0] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020402 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Vascular dementia with high laxatives exposure | — | — | Hazard ratio (HR, high laxative use and PRS in top tertile vs no laxative use and PRS in bottom tertile): 3.27 [2.37, 4.51] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020397 | PGS004318 (PRS29_dementia) |
PSS011350| Multi-ancestry (including European)| 57,688 individuals |
PGP000548 | Feng J et al. BMC Geriatr (2023) |
Reported Trait: Dementia | — | — | Hazard ratio (HR, high vs low PRS tertile): 2.76 [2.6, 2.93] | Sex, age, ethnicity, socioeconomic status, education attainment, current employment status, smoking status, alcohol consumption, physical activity, diet, BMI, heart disease, stroke, diabetes, hypertension, depression, cholesterol levels, and constipation | — |
| PPM020429 | PGS004322 (GRS30_IS) |
PSS011358| European Ancestry| 454,493 individuals |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Reported Trait: Incident ischaemic stroke | HR: 1.26 [1.17, 1.35] | — | — | age, gender, 10-yr ASCVD Risk by PCE, genetic background, and sepsis | — |
| PPM020430 | PGS004322 (GRS30_IS) |
PSS011358| European Ancestry| 454,493 individuals |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Reported Trait: Any incident myocardial infarction, ischaemic stroke, or venous thromboembolism | HR: 1.05 [1.01, 1.1] | — | — | age, gender, 10-yr ASCVD Risk by PCE, genetic background, and sepsis | — |
| PPM020431 | PGS002249 (AD_PRS_0.5) |
PSS011359| European Ancestry| 60,298 individuals |
PGP000556 | Shannon OM et al. BMC Med (2023) |Ext. |
Reported Trait: Dementia | — | — | Hazard ratio (HR, top vs bottom PRS quintile): 1.224 [1.102, 1.36] | — | — |
| PPM020432 | PGS002249 (AD_PRS_0.5) |
PSS011359| European Ancestry| 60,298 individuals |
PGP000556 | Shannon OM et al. BMC Med (2023) |Ext. |
Reported Trait: Dementia x MedDiet adherence (MEDAS score) interaction | HR: 1.042 [1.003, 1.082] | — | — | — | — |
| PPM020564 | PGS004449 (disease.F10.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F10 (Mental and behavioural disorders due to use of alcohol) | OR: 1.17947 | — | — | — | — |
| PPM020565 | PGS004450 (disease.F17.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F17 (Mental and behavioural disorders due to use of tobacco) | OR: 1.24282 | — | — | — | — |
| PPM020566 | PGS004451 (disease.F41.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F41 (Other anxiety disorders) | OR: 1.18672 | — | — | — | — |
| PPM020568 | PGS004453 (disease.G56.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: G56 (Mononeuropathies of upper limb) | OR: 1.2757 | — | — | — | — |
| PPM020634 | PGS004519 (meta.F10.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F10 (Mental and behavioural disorders due to use of alcohol) | OR: 1.30179 | — | — | — | — |
| PPM020635 | PGS004520 (meta.F17.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F17 (Mental and behavioural disorders due to use of tobacco) | OR: 1.29767 | — | — | — | — |
| PPM020636 | PGS004521 (meta.F41.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: F41 (Other anxiety disorders) | OR: 1.29571 | — | — | — | — |
| PPM020638 | PGS004523 (meta.G56.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: G56 (Mononeuropathies of upper limb) | OR: 1.41928 | — | — | — | — |
| PPM020719 | PGS004590 (PRS363_rand_eff) |
PSS011381| Multi-ancestry (including European)| 368 individuals |
PGP000569 | Lake J et al. Mol Psychiatry (2023) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.68 | R²: 0.0044 | Age, sex, 5 PCs | — |
| PPM020721 | PGS004591 (PRS17_MDD) |
PSS011382| Multi-ancestry (including European)| 354,897 individuals |
PGP000570 | Li D et al. BMC Med (2023) |
Reported Trait: Major depressive disorder with PM2.5 air pollution | — | — | Hazard ratio (HR, PRS in top tertile and high PM2.5 exposure vs PRS in bottom tertile and low PM2.5 exposure): 1.34 [1.23, 1.46] | Age, gender, ethnicity, education level, employment status, household income, and Townsend deprivation index | — |
| PPM020711 | PGS004588 (PRS39_Eur) |
PSS011377| East Asian Ancestry| 379 individuals |
PGP000567 | Jung SH et al. JAMA Netw Open (2022) |
Reported Trait: Alzheimer's disease dementia | OR: 1.85 [1.05, 3.32] | — | — | Sex, age, education year, 4 PCs, APOE ε4 status | — |
| PPM020712 | PGS004589 (PRS80_trans) |
PSS011377| East Asian Ancestry| 379 individuals |
PGP000567 | Jung SH et al. JAMA Netw Open (2022) |
Reported Trait: Alzheimer's disease dementia | OR: 2.09 [1.09, 4.04] | — | — | Sex, age, education year, 4 PCs, APOE ε4 status | — |
| PPM020720 | PGS004591 (PRS17_MDD) |
PSS011382| Multi-ancestry (including European)| 354,897 individuals |
PGP000570 | Li D et al. BMC Med (2023) |
Reported Trait: Major depressive disorder | — | — | Hazard ratio (HR, per IQR change in PRS): 1.1 [1.07, 1.12] | Age, gender, ethnicity, education level, employment status, household income, Townsend deprivation index, genotyping batch, and first 10 PCs | — |
| PPM020749 | PGS004597 (PRS32_IS) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident ischaemic stroke in breast cancer survivors | — | — | Hazard ratio (HR, top 50% vs bottom 50% of PRS): 1.25 [0.91, 1.72] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020752 | PGS004597 (PRS32_IS) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident ischaemic stroke in breast cancer survivors with lifestyle | — | — | Hazard ratio (HR, unhealthy lifestyle and PRS in top 50% vs healthy lifestyle and PRS in bottom 50%): 0.37 [0.15, 0.93] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020755 | PGS004600 (PRS_AD83) |
PSS011392| European Ancestry| 276 individuals |
PGP000578 | Tomassen J et al. BMC Neurol (2022) |
Reported Trait: Memory function over time | β: -0.04 (0.01) | — | — | age, sex, center, education | — |
| PPM020756 | PGS004600 (PRS_AD83) |
PSS011392| European Ancestry| 276 individuals |
PGP000578 | Tomassen J et al. BMC Neurol (2022) |
Reported Trait: Positive amyloid-beta status | OR: 1.43 [1.02, 2.0] | — | — | age, sex, center, education | — |
| PPM020767 | PGS004606 (AMD-IAMDGC-EUR) |
PSS011398| European Ancestry| 163,011 individuals |
PGP000582 | Gorman BR et al. Nat Genet (2024) |
Reported Trait: Age-related macular degeneration | OR: 1.76 [1.73, 1.78] | AUROC: 0.71 | — | age, sex, principal components 1-10 | — |
| PPM020768 | PGS004607 (AMD-MVP-AFR) |
PSS011398| European Ancestry| 163,011 individuals |
PGP000582 | Gorman BR et al. Nat Genet (2024) |
Reported Trait: Age-related macular degeneration | OR: 1.48 [1.34, 1.63] | AUROC: 0.65 | — | age, sex, principal components 1-10 | — |
| PPM020918 | PGS004699 (Non-HLA-GRS) |
PSS011453| Multi-ancestry (including European)| 483,480 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.752 [0.75, 0.755] | — | Age at recruitment, sex, Townsend Deprivation Index, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020919 | PGS004699 (Non-HLA-GRS) |
PSS011452| Multi-ancestry (including European)| 116,767 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.744 | — | Index age, reported sex, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020920 | PGS004699 (Non-HLA-GRS) |
PSS011451| Ancestry Not Reported| 372,416 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.764 | — | Age at DNA sample collection, sex, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020921 | PGS004699 (Non-HLA-GRS) |
PSS011454| Multi-ancestry (including European)| 545 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis in individuals with undifferentiated optic neuritis | HR: 1.29 [1.07, 1.55] | — | — | Age, sex | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020922 | PGS004700 (HLA-GRS) |
PSS011453| Multi-ancestry (including European)| 483,480 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.752 [0.75, 0.755] | — | Age at recruitment, sex, Townsend Deprivation Index, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020923 | PGS004700 (HLA-GRS) |
PSS011452| Multi-ancestry (including European)| 116,767 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.744 | — | Index age, reported sex, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020924 | PGS004700 (HLA-GRS) |
PSS011451| Ancestry Not Reported| 372,416 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.764 | — | Age at DNA sample collection, sex, 4 PCs | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020925 | PGS004700 (HLA-GRS) |
PSS011454| Multi-ancestry (including European)| 545 individuals |
PGP000603 | Loginovic P et al. Nat Commun (2024) |
Reported Trait: Multiple sclerosis in individuals with undifferentiated optic neuritis | HR: 1.29 [1.07, 1.55] | — | — | Age, sex | NOTE: Performance is based on an unweighted sum of Non-HLA-GRS and HLA-GRS |
| PPM020984 | PGS004759 (depression_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Depression | — | — | Incremental R2 (Full model versus model with only covariates): 0.016 [0.011, 0.021] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020985 | PGS004760 (depression_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Depression | — | — | Incremental R2 (Full model versus model with only covariates): 0.024 [0.018, 0.03] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021022 | PGS004797 (migraine_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.003 [0.001, 0.005] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021023 | PGS004798 (migraine_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.004 [0.001, 0.006] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021024 | PGS004799 (migraine_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.019 [0.013, 0.024] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021060 | PGS004835 (stroke_PRSmix_eur) |
PSS011506| European Ancestry| 7,889 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Stroke | — | — | Incremental R2 (Full model versus model with only covariates): 0.007 [0.003, 0.01] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021061 | PGS004836 (stroke_PRSmixPlus_eur) |
PSS011506| European Ancestry| 7,889 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Stroke | — | — | Incremental R2 (Full model versus model with only covariates): 0.017 [0.011, 0.022] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021025 | PGS004800 (migraine_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.011 [0.007, 0.016] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021094 | PGS004863 (PRS74_AD) |
PSS011524| East Asian Ancestry| 528 individuals |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Reported Trait: Cortical amyloid positivity | OR: 1.186 [0.992, 1.418] | AUROC: 0.751 [0.705, 0.796] | — | APOE haplotype, age, sex, 3 PCs | — |
| PPM021095 | PGS004863 (PRS74_AD) |
PSS011525| East Asian Ancestry| 696 individuals |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Reported Trait: Clinical Dementia Rating global score ≥ 1 | OR: 1.04 [0.871, 1.243] | AUROC: 0.637 [0.586, 0.689] | — | APOE haplotype, age, sex, 3 PCs | — |
| PPM021096 | PGS004863 (PRS74_AD) |
PSS011522| South Asian Ancestry| 718 individuals |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Reported Trait: All-cause dementia | OR: 1.11 [0.94, 1.33] | AUROC: 0.69 [0.62, 0.76] | — | APOE haplotype, age, sex, 3 PCs | — |
| PPM021097 | PGS004863 (PRS74_AD) |
PSS011523| East Asian Ancestry| 2,000 individuals |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Reported Trait: Alzheimer's disease or mild cognitive impairment | OR: 1.12 | AUROC: 0.625 [0.601, 0.65] | — | APOE haplotype, age, sex, 3 PCs | — |
| PPM021098 | PGS004863 (PRS74_AD) |
PSS011526| European Ancestry| 229,265 individuals |
PGP000609 | Sleiman PM et al. Alzheimers Dement (2023) |
Reported Trait: Alzheimer's disease or dementia | OR: 1.003 [0.99, 1.007] | AUROC: 0.746 [0.738, 0.754] | — | APOE haplotype, age, sex, 3 PCs | — |
| PPM021223 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011665| European Ancestry| 447,332 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.12 [1.09, 1.14] | — | — | PCs 1-10 | — |
| PPM021224 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011580| European Ancestry| 20,188 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.07 [1.02, 1.11] | C-index: 0.54 [0.53, 0.55] | — | PCs 1-10 | — |
| PPM021225 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011579| European Ancestry| 69,715 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.1 [1.05, 1.16] | C-index: 0.55 [0.54, 0.57] | — | PCs 1-10 | — |
| PPM021226 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011578| European Ancestry| 29,427 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.1 [1.02, 1.19] | C-index: 0.54 [0.52, 0.56] | — | PCs 1-10 | — |
| PPM021227 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011576| European Ancestry| 44,188 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.17 [1.04, 1.32] | — | — | PCs 1-10 | — |
| PPM021228 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011577| European Ancestry| 7,018 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 0.98 [0.86, 1.13] | C-index: 0.59 [0.55, 0.63] | — | PCs 1-10 | — |
| PPM021230 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011574| European Ancestry| 199,868 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.11 [1.08, 1.14] | C-index: 0.55 [0.54, 0.56] | — | PCs 1-10 | — |
| PPM021252 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011614| European Ancestry| 37,136 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.18 [1.16, 1.2] | C-index: 0.56 [0.55, 0.56] | — | PCs 1-10 | — |
| PPM021253 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011613| European Ancestry| 69,715 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.27 [1.23, 1.31] | C-index: 0.57 [0.56, 0.58] | — | PCs 1-10 | — |
| PPM021254 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011612| European Ancestry| 29,427 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.27 [1.23, 1.32] | C-index: 0.58 [0.57, 0.59] | — | PCs 1-10 | — |
| PPM021255 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011610| European Ancestry| 44,188 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.17 [1.12, 1.22] | — | — | PCs 1-10 | — |
| PPM021256 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011611| European Ancestry| 7,018 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.36 [1.21, 1.53] | C-index: 0.62 [0.58, 0.65] | — | PCs 1-10 | — |
| PPM021257 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011609| European Ancestry| 412,090 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.24 [1.23, 1.25] | C-index: 0.58 [0.58, 0.58] | — | PCs 1-10 | — |
| PPM021258 | PGS004885 (INTERVENE_MegaPRS_MDD) |
PSS011608| European Ancestry| 199,868 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident MDD | HR: 1.15 [1.14, 1.16] | C-index: 0.55 [0.55, 0.55] | — | PCs 1-10 | — |
| PPM021281 | PGS004898 (PRS_AD) |
PSS011676| European Ancestry| 1,135 individuals |
PGP000624 | Vasiljevic E et al. Alzheimers Dement (2023) |
Reported Trait: Immediate learning | β: -0.07 [-0.12, -0.02] | — | — | Sex, years of education, testing practice effects | — |
| PPM021282 | PGS004898 (PRS_AD) |
PSS011676| European Ancestry| 1,135 individuals |
PGP000624 | Vasiljevic E et al. Alzheimers Dement (2023) |
Reported Trait: Delayed recall | β: -0.07 [-0.12, -0.02] | — | — | Sex, years of education, testing practice effects | — |
| PPM021283 | PGS004898 (PRS_AD) |
PSS011676| European Ancestry| 1,135 individuals |
PGP000624 | Vasiljevic E et al. Alzheimers Dement (2023) |
Reported Trait: Executive function | β: -0.06 [-0.11, -0.01] | — | — | Sex, years of education, testing practice effects | — |
| PPM021284 | PGS004898 (PRS_AD) |
PSS011676| European Ancestry| 1,135 individuals |
PGP000624 | Vasiljevic E et al. Alzheimers Dement (2023) |
Reported Trait: Preclinical Alzheimer Cognitive Composite (PACC3) | β: -0.08 [-0.13, -0.04] | — | — | Sex, years of education, testing practice effects | — |
| PPM021351 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident heart failure | HR: 1.08 [1.06, 1.1] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021311 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident cardiovascular disease outcome | HR: 1.18 [1.15, 1.21] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021312 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.2 [1.16, 1.24] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021313 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident stroke | HR: 1.19 [1.14, 1.24] | — | — | Age at baseline, stratified by study centre, sex | — |
| PPM021314 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident stroke | HR: 1.16 [1.11, 1.21] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021315 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Combination of incident coronary heart disease, stroke and cardiac revascularisation procedures | HR: 1.19 [1.16, 1.22] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021348 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Cardiovascular death, stroke, hospitalization for worsening of HF, or acute coronary syndrome | HR: 1.13 [1.0, 1.27] | — | — | Treatment group | — |
| PPM021349 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Stroke | HR: 1.0 [0.75, 1.34] | — | — | Treatment group | — |
| PPM021350 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Worsening of heart failure | HR: 1.23 [1.05, 1.43] | — | — | Treatment group | — |
| PPM021352 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident stroke | HR: 1.08 [1.06, 1.11] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021353 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.11 [1.08, 1.14] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021354 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident atrial fibrillation or atrial flutter | HR: 1.15 [1.14, 1.67] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021384 | PGS004918 (PRS8_Synapse) |
PSS011719| European Ancestry| 136 individuals |
PGP000649 | Lawingco T et al. Neurobiol Aging (2020) |
Reported Trait: Late-onset Alzheimer's disease | — | AUROC: 0.731 | — | — | — |
| PPM020348 | PGS004280 (GenoBoost_all-cause_dementia_0) |
PSS011345| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: All-cause dementia | — | AUROC: 0.81926 | Covariate-adjusted pseudo-R2: 0.03533 AUPRC: 0.07827 |
age, sex, PC1-10 | — |
| PPM020356 | PGS004288 (GenoBoost_alzheimer_s_disease_3) |
PSS011336| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Alzheimer's disease | — | AUROC: 0.83004 | Covariate-adjusted pseudo-R2: 0.03836 AUPRC: 0.83004 |
age, sex, PC1-10 | — |
| PPM021229 | PGS004881 (INTERVENE_MegaPRS_Epilepsy) |
PSS011575| European Ancestry| 412,090 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident Epilepsy | HR: 1.11 [1.09, 1.13] | C-index: 0.55 [0.55, 0.56] | — | PCs 1-10 | — |
| PPM021702 | PGS004924 (PRS90_PD) |
PSS011750| Multi-ancestry (including European)| 3,482 individuals |
PGP000657 | Cao Z et al. Parkinsonism Relat Disord (2023) |
Reported Trait: Parkinson's disease | — | — | Odds ratio (OR, top vs bottom PGS quartile): 3.79 [1.64, 8.73] | Age, race, 5 PCs, self-reported sense of smell, education, smoking status, self-reported health status, and PM2.5 and NO2 in 2006 | — |
| PPM021703 | PGS004924 (PRS90_PD) |
PSS011751| Multi-ancestry (including European)| 3,482 individuals |
PGP000657 | Cao Z et al. Parkinsonism Relat Disord (2023) |
Reported Trait: Olfactory impairment (B-SIT score ≤6) | — | — | Odds ratio (OR, top vs bottom PGS quartile): 1.42 [1.04, 1.92] | Age, race, 5 PCs, self-reported sense of smell, education, smoking status, self-reported health status, and PM2.5 and NO2 in 2006 | — |
| PPM021765 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011789| European Ancestry| 332 individuals |
PGP000674 | Lin F et al. Front Stroke (2023) |Ext. |
Reported Trait: Ischemic stroke | OR: 3.0 [0.3, 26.4] | — | — | Age, smoking status | — |
| PPM021741 | PGS004943 (ICH_MetaPRS) |
PSS011773| East Asian Ancestry| 72,149 individuals |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Reported Trait: Incident intracerebral hemorrhage | HR: 1.31 [1.24, 1.39] | C-index: 0.748 [0.734, 0.761] | — | age, sex | — |
| PPM021759 | PGS004952 (PRS52_AMD) |
PSS011783| European Ancestry| 1,575 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Early age-related macular degeneration (Clinical Classification) | OR: 1.13 [1.09, 1.16] | AUROC: 64.2 | — | Age, sex, survey membership, 10 PCs | — |
| PPM021760 | PGS004952 (PRS52_AMD) |
PSS011784| European Ancestry| 1,511 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Intermediate age-related macular degeneration (Clinical Classification) | OR: 1.25 [1.2, 1.29] | AUROC: 73.3 | — | Age, sex, survey membership, 10 PCs | — |
| PPM021761 | PGS004952 (PRS52_AMD) |
PSS011785| European Ancestry| 1,232 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Late age-related macular degeneration (Clinical Classification) | OR: 1.41 [1.32, 1.5] | AUROC: 84.2 | — | Age, sex, survey membership, 10 PCs | — |
| PPM021762 | PGS004952 (PRS52_AMD) |
PSS011786| European Ancestry| 1,780 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Mild early age-related macular degeneration (3CACSS) | OR: 1.08 [1.04, 1.13] | AUROC: 59.9 | — | Age, sex, survey membership, 10 PCs | — |
| PPM021763 | PGS004952 (PRS52_AMD) |
PSS011787| European Ancestry| 1,696 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Moderate early age-related macular degeneration (3CACSS) | OR: 1.29 [1.22, 1.37] | AUROC: 76.3 | — | Age, sex, survey membership, 10 PCs | — |
| PPM021764 | PGS004952 (PRS52_AMD) |
PSS011788| European Ancestry| 1,699 individuals |
PGP000673 | Herold JM et al. Invest Ophthalmol Vis Sci (2023) |
Reported Trait: Severe early age-related macular degeneration (3CACSS) | OR: 1.38 [1.29, 1.47] | AUROC: 80.95 | — | Age, sex, survey membership, 10 PCs | — |
| PPM022295 | PGS002280 (GRS83_AD) |
PSS011907| European Ancestry| 3,285 individuals |
PGP000698 | Gorijala P et al. Alzheimers Dement (2023) |Ext. |
Reported Trait: Sporadic early-onset Alzheimer's disease | — | — | Odds ratio (OR, high vs low PGS tertile): 2.56 [1.95, 3.39] | Sex | — |
| PPM022296 | PGS002280 (GRS83_AD) |
PSS011906| European Ancestry| 4,303 individuals |
PGP000698 | Gorijala P et al. Alzheimers Dement (2023) |Ext. |
Reported Trait: Familial late-onset Alzheimer's disease | — | — | Odds ratio (OR, high vs low PGS tertile): 2.31 [1.97, 2.72] | Sex | — |
| PPM022297 | PGS002280 (GRS83_AD) |
PSS011908| European Ancestry| 5,149 individuals |
PGP000698 | Gorijala P et al. Alzheimers Dement (2023) |Ext. |
Reported Trait: Sporadic late-onset Alzheimer's disease | — | — | Odds ratio (OR, high vs low PGS tertile): 1.67 [1.46, 1.91] | Sex | — |
| PPM022376 | PGS005156 (Stroke (PRS-CSx; EAS+EUR)) |
PSS011929| East Asian Ancestry| 58,633 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Stroke | β: 1.17852 | — | — | age, sex | — |
| PPM022476 | PGS005170 (iPRS_DEM) |
PSS011959| European Ancestry| 1,414 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.04 [0.88, 1.23] | — | — | age at baseline, age^2, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022477 | PGS005170 (iPRS_DEM) |
PSS011960| European Ancestry| 2,288 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.23 [1.07, 1.41] | — | — | age at baseline, age^2, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022478 | PGS005170 (iPRS_DEM) |
PSS011957| European Ancestry| 2,165 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (>80 years) | HR: 1.16 [1.01, 1.32] | — | — | age at baseline, age^2, sex,10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022479 | PGS005170 (iPRS_DEM) |
PSS011956| European Ancestry| 3,201 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (<80 years) | HR: 1.17 [0.96, 1.43] | — | — | age at baseline, age^2, sex, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022480 | PGS005170 (iPRS_DEM) |
PSS011958| European Ancestry| 704 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (APOE E4 carriers) | HR: 1.194 [0.98, 1.46] | — | — | age at baseline, age^2, sex,10 genetic PCs | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022481 | PGS005170 (iPRS_DEM) |
PSS011961| European Ancestry| 2,928 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (APOE E4 non-carriers) | HR: 1.13 [0.99, 1.28] | — | — | age at baseline, age^2, sex, 10 genetic PCs | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022482 | PGS005170 (iPRS_DEM) |
PSS011966| European Ancestry| 2,032 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.25 [1.11, 1.42] | AUROC: 0.761 | — | age at baseline, age^2, sex, the first 10 genetic principal components (PCs) of population stratification, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. Prediction was assessed at 5-year follow-up using time-dependent AUC over 2,000 bootstrap replications. |
| PPM022483 | PGS005170 (iPRS_DEM) |
PSS011969| European Ancestry| 782 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.17 [0.97, 1.4] | — | — | age at baseline, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022484 | PGS005170 (iPRS_DEM) |
PSS011970| European Ancestry| 1,250 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.3 [1.1, 1.54] | — | — | age at baseline, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022486 | PGS005170 (iPRS_DEM) |
PSS011967| European Ancestry| 1,758 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (<80 years) | HR: 1.3 [1.11, 1.52] | — | — | age at baseline, sex, 10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022487 | PGS005170 (iPRS_DEM) |
PSS011971| European Ancestry| 605 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (APOE E4 carriers) | HR: 1.33 [1.12, 1.58] | — | — | age at baseline, sex,10 genetic PCs | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022488 | PGS005170 (iPRS_DEM) |
PSS011972| European Ancestry| 1,427 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (APOE E4 non-carriers) | HR: 1.15 [0.96, 1.37] | — | — | age at baseline, sex, 10 genetic PCs | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022489 | PGS005170 (iPRS_DEM) |
PSS011964| European Ancestry| 130,797 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.28 [1.09, 1.51] | — | — | age, sex, five genetic principal components, and APOE dosage | — |
| PPM022490 | PGS005170 (iPRS_DEM) |
PSS011962| African Ancestry| 55,498 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.06 [0.75, 1.45] | — | — | age, sex, five genetic principal components, and APOE dosage | — |
| PPM022491 | PGS005170 (iPRS_DEM) |
PSS011963| East Asian Ancestry| 5,640 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 5.29 [1.43, 34.36] | — | — | age, sex, five genetic principal components, and APOE dosage | — |
| PPM022492 | PGS005170 (iPRS_DEM) |
PSS011965| Hispanic or Latin American Ancestry| 44,266 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.09 [0.78, 1.68] | — | — | age, sex, five genetic principal components, and APOE dosage | — |
| PPM022475 | PGS005170 (iPRS_DEM) |
PSS011955| European Ancestry| 3,702 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia | HR: 1.15 [1.03, 1.28] | AUROC: 0.756 | — | age at baseline, age^2, sex, the first 10 genetic principal components (PCs) of population stratification, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. Prediction was assessed at 10-year follow-up using time-dependent AUC over 2,000 bootstrap replications. |
| PPM022485 | PGS005170 (iPRS_DEM) |
PSS011968| European Ancestry| 638 individuals |
PGP000718 | D'Aoust T et al. Alzheimers Dement (2025) |
Reported Trait: Incident all-cause dementia (>80 years) | HR: 1.13 [0.92, 1.38] | — | — | age at baseline, sex,10 genetic PCs, and dosage of APOE ε4 and APOE ε2 alleles | Fine-Gray Regression models were used, sub-distribution hazard ratios are reported. |
| PPM022528 | PGS001775 (PRS39_AD) |
PSS011985| European Ancestry| 458,181 individuals |
PGP000722 | Yuan S et al. Am J Prev Med (2023) |Ext. |
Reported Trait: Incident dementia | — | — | Hazard ratio (HR, high vs low quintile): 1.51 [1.42, 1.67] | age, sex, Townsend deprivation index, educational attainment, BMI, physical activity, diet, smoking status, alcohol consumption, baseline hypertension, baseline stroke, history of dementia, depression | — |
| PPM022648 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident stroke | HR: 1.09 [1.07, 1.11] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022649 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident Ischemic stroke | HR: 1.12 [1.09, 1.15] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022652 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution PM10 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.48 [1.33, 1.65] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022653 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution NO2 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.51 [1.35, 1.69] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022654 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution NOx exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.39 [1.25, 1.55] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022650 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident Hemorrhagic stroke | HR: 1.05 [1.0, 1.1] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022651 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution PM2.5 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.45 [1.31, 1.61] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022981 | PGS000334 (GRSfull_22) |
PSS012082| European Ancestry| 5,347 individuals |
PGP000754 | Liu Y et al. Nat Aging (2024) |Ext. |
Reported Trait: Incident Alzheimer's disease | HR: 1.93 [1.73, 2.15] β: 0.65554 |
— | — | Baseline age, BMI, systolic BP, total cholesterol, HDL, smoking, exercise, prevelant diabetes, family history, gut microbiome score | — |
| PPM023054 | PGS000902 (PRS90_PD) |
PSS012105| Ancestry Not Reported| 3,453 individuals |
PGP000765 | Gandhi SE et al. Mov Disord Clin Pract (2024) |Ext. |
Reported Trait: dyskinesia (2-4 years after diagnosis) | OR: 1.34 [1.036, 1.737] | — | — | Age at diagnosis, Female gender, Interpolated BMI, Education > 12 years, MDS-UPDRS part 1, Depression (score > 0), Anxiety (score > 0), MDS-UPDRS part 2, MDS-UPDRS part 3, MDS-UPDRS part 3 tremor subscore, HY3 plus, MDS-UPDRS part 3 progression, Total LEDD | — |
| PPM023055 | PGS000902 (PRS90_PD) |
PSS012105| Ancestry Not Reported| 3,453 individuals |
PGP000765 | Gandhi SE et al. Mov Disord Clin Pract (2024) |Ext. |
Reported Trait: dyskinesia (8=10 years after diagnosis) | OR: 1.401 [1.024, 1.93] | — | — | Age at diagnosis, Female gender, Interpolated BMI, Education > 12 years, MDS-UPDRS part 1, Depression (score > 0), Anxiety (score > 0), MDS-UPDRS part 2, MDS-UPDRS part 3, MDS-UPDRS part 3 tremor subscore, HY3 plus, MDS-UPDRS part 3 progression, Total LEDD | — |
| PPM023429 | PGS005390 (ADRD_consensus_no_proxy_score) |
PSS012178| European Ancestry| 5,793 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: Braak NFT Stage at death | OR: 1.11 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM023430 | PGS005391 (ADRD_consensus_no_biobank_score) |
PSS012178| European Ancestry| 5,793 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: Braak NFT Stage at death | OR: 1.13 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM023435 | PGS005393 (PGS_SEXUAL_ASSAULT_PTSD) |
PSS012181| Hispanic or Latin American Ancestry| 117 individuals |
PGP000778 | Bugiga AVG et al. Braz J Psychiatry (2024) |
Reported Trait: PTSD diagnosis | — | — | R²: 0.087 | PC1-PC10 | best p-value threshold of 0.333 |
| PPM023436 | PGS005393 (PGS_SEXUAL_ASSAULT_PTSD) |
PSS012181| Hispanic or Latin American Ancestry| 117 individuals |
PGP000778 | Bugiga AVG et al. Braz J Psychiatry (2024) |
Reported Trait: PTSD diagnosis | OR: 0.035 | — | — | Trauma history, genetic ancestry (10 PCs), age, education, income. | best p-value threshold of 0.333 |
| PPM023431 | PGS005389 (ADRD_consensus_main_score) |
PSS012179| European Ancestry| 5,800 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: CERAD score at death | OR: 1.12 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM023432 | PGS005390 (ADRD_consensus_no_proxy_score) |
PSS012179| European Ancestry| 5,800 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: CERAD score at death | OR: 1.12 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM023433 | PGS005391 (ADRD_consensus_no_biobank_score) |
PSS012179| European Ancestry| 5,800 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: CERAD score at death | OR: 1.14 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM030660 | PGS012551 (PRS_stroke) |
PSS012229| European Ancestry| 21,092 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Reported Trait: Stroke | — | AUROC: 0.542 [0.499, 0.585] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for stroke: 0.523 [0.48, 0.566] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030666 | PGS001829 (portability-PLR_296.2) |
PSS012230| Greater Middle Eastern Ancestry| 1,359 individuals |
PGP000795 | Smeeth D et al. Dev Psychopathol (2023) |Ext. |
Reported Trait: Resilience (late-mid puberty) | OR: 0.01 [0.0002, 0.32] | — | — | age, gender,10 genetic principal components | — |
| PPM030668 | PGS001829 (portability-PLR_296.2) |
PSS012230| Greater Middle Eastern Ancestry| 1,359 individuals |
PGP000795 | Smeeth D et al. Dev Psychopathol (2023) |Ext. |
Reported Trait: Resilience x hair cortisol interaction | OR: 0.04 [0.003, 0.47] | — | — | age, gender,10 genetic principal components | — |
| PPM030654 | PGS012548 (PRS94_AD) |
PSS012224| European Ancestry| 345,439 individuals |
PGP000791 | Li Y et al. J Gerontol A Biol Sci Med Sci (2024) |
Reported Trait: All-cause dementia | — | — | Hazard ratio (HR, high vs low tertile): 2.94 [2.68, 3.23] | age (5 years categories), sex, recruitment assessment center, genotyping array, first 10 principal components of ancestry, polysocial risk score | — |
| PPM030655 | PGS012548 (PRS94_AD) |
PSS012224| European Ancestry| 345,439 individuals |
PGP000791 | Li Y et al. J Gerontol A Biol Sci Med Sci (2024) |
Reported Trait: Alzheimer's disease | — | — | Hazard ratio (HR, high vs low tertile): 4.71 [4.03, 5.5] | age (5 years categories), sex, recruitment assessment center, genotyping array, first 10 principal components of ancestry, polysocial risk score | — |
| PPM030656 | PGS012548 (PRS94_AD) |
PSS012224| European Ancestry| 345,439 individuals |
PGP000791 | Li Y et al. J Gerontol A Biol Sci Med Sci (2024) |
Reported Trait: Vascular dementia | — | — | Hazard ratio (HR, high vs low tertile): 2.93 [2.4, 3.58] | age (5 years categories), sex, recruitment assessment center, genotyping array, first 10 principal components of ancestry, polysocial risk score | — |
| PPM030743 | PGS012584 (PRS44_PD) |
PSS012275| Multi-ancestry (including European)| 192,340 individuals |
PGP000818 | Geng T et al. NPJ Parkinsons Dis (2024) |
Reported Trait: Parkinson's disease | HR: 1.07 [1.05, 1.08] | — | — | age at recruitment (continuous, years), and sex (men, women) | — |
| PPM023428 | PGS005389 (ADRD_consensus_main_score) |
PSS012178| European Ancestry| 5,793 individuals |
PGP000776 | EADB et al. Nat Genet (2026) |
Reported Trait: Braak NFT Stage at death | OR: 1.11 | — | — | age at death, sex, the number of APOE ε4 and ε2 alleles, 10 PCs and centers | — |
| PPM030733 | PGS012579 (PRS11_stroke) |
PSS012270| Multi-ancestry (including European)| 453,102 individuals |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Reported Trait: Stroke | — | — | Hazard ratio (HR, high vs low tertile): 1.61 [1.41, 1.82] | major cardiovascular risk factors: Age, sex, ethnicity, the TDI, level of education, annual household income, BMI, smoking status, alcohol intake, physical activity (weekly metabolic equivalent minutes ≥600), vitamin supplementation, and comorbidities that may increase the risk of infections (i.e., hypertension, diabetes, high cholesterol, liver disease, kidney disease, and digestive disease) | — |
| PPM030762 | PGS012589 (PRS29_dementia) |
PSS012285| European Ancestry| 220,963 individuals |
PGP000823 | Zhang S et al. Int J Public Health (2024) |
Reported Trait: Incident dementia | HR: 1.25 [1.21, 1.28] | — | — | age, sex | — |
| PPM030763 | PGS012589 (PRS29_dementia) |
PSS012285| European Ancestry| 220,963 individuals |
PGP000823 | Zhang S et al. Int J Public Health (2024) |
Reported Trait: Incident dementia (in APOE E4 homozygotes) | HR: 8.64 [7.73, 9.67] | — | — | age, sex | APOE E4 dosage = 2 |
| PPM030764 | PGS012589 (PRS29_dementia) |
PSS012285| European Ancestry| 220,963 individuals |
PGP000823 | Zhang S et al. Int J Public Health (2024) |
Reported Trait: Incident dementia x air pollution score interaction | — | — | Hazard ratio (HR, high air pollution score and high PRS vs. low air pollution score and low PRS): 1.93 [1.6, 2.32] | age, sex | — |
| PPM036645 | PGS018463 (TPMI_145.2_PRS-CS) |
PSS012360| East Asian Ancestry| 19,060 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cancer of tongue | — | AUROC: 0.68622 | R²: 0.0117 | sex, age, array, PCs 1-10 | — |
| PPM036758 | PGS018576 (TPMI_191_LDpred2) |
PSS012477| East Asian Ancestry| 19,669 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Manlignant and unknown neoplasms of brain and nervous system | — | AUROC: 0.69446 | R²: 0.01254 | sex, age, array, PCs 1-10 | — |
| PPM036760 | PGS018578 (TPMI_191_PRS-CS) |
PSS012480| East Asian Ancestry| 19,669 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Manlignant and unknown neoplasms of brain and nervous system | — | AUROC: 0.69562 | R²: 0.01269 | sex, age, array, PCs 1-10 | — |
| PPM037153 | PGS018971 (TPMI_327.7_Lassosum2) |
PSS012879| East Asian Ancestry| 16,204 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sleep related movement disorders | — | AUROC: 0.59938 | R²: 0.00228 | sex, age, array, PCs 1-10 | — |
| PPM036815 | PGS018633 (TPMI_225_PRS-CS) |
PSS012535| East Asian Ancestry| 19,663 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Benign neoplasm of brain and other parts of nervous system | — | AUROC: 0.65907 | R²: 0.00795 | sex, age, array, PCs 1-10 | — |
| PPM036591 | PGS018414 (pgshl) |
PSS012317| Multi-ancestry (including European)| 390 individuals |
PGP000832 | Miao DNR et al. Hum Genomics (2024) |
Reported Trait: cisplatin-induced ototoxicity | — | — | R²: 0.023 p-value: 0.00293 |
— | — |
| PPM036593 | PGS018414 (pgshl) |
PSS012318| Ancestry Not Reported| 238 individuals |
PGP000832 | Miao DNR et al. Hum Genomics (2024) |
Reported Trait: cisplatin-induced ototoxicity | — | — | R²: 0.006 p-value: 0.52 |
age at diagnosis , protocol (SJMB96 or SJMB03) , 10 principal components , craniospinal irradiation dose (CSI dose)*score | — |
| PPM036917 | PGS018735 (TPMI_250.6_LDpred2) |
PSS012665| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.66143 | R²: 0.02491 | sex, age, array, PCs 1-10 | — |
| PPM036920 | PGS018738 (TPMI_250.6_PRSmix+) |
PSS012669| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.72686 | R²: 0.05052 | sex, age, array, PCs 1-10 | — |
| PPM036921 | PGS018739 (TPMI_250.6_SBayesR) |
PSS012670| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.65242 | R²: 0.02202 | sex, age, array, PCs 1-10 | — |
| PPM037159 | PGS018977 (TPMI_327.41_LDpred2) |
PSS012868| East Asian Ancestry| 17,271 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Organic or persistent insomnia | — | AUROC: 0.63767 | R²: 0.03603 | sex, age, array, PCs 1-10 | — |
| PPM037160 | PGS018978 (TPMI_327.41_MegaPRS) |
PSS012870| East Asian Ancestry| 17,271 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Organic or persistent insomnia | — | AUROC: 0.63887 | R²: 0.03647 | sex, age, array, PCs 1-10 | — |
| PPM037161 | PGS018979 (TPMI_327.41_PRS-CS) |
PSS012871| East Asian Ancestry| 17,271 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Organic or persistent insomnia | — | AUROC: 0.63737 | R²: 0.03579 | sex, age, array, PCs 1-10 | — |
| PPM037073 | PGS018891 (TPMI_290_Lassosum2) |
PSS012814| East Asian Ancestry| 19,541 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Delirium dementia and amnestic and other cognitive disorders | — | AUROC: 0.62251 | R²: 0.01449 | sex, age, array, PCs 1-10 | — |
| PPM037074 | PGS018892 (TPMI_290_LDpred2) |
PSS012813| East Asian Ancestry| 19,541 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Delirium dementia and amnestic and other cognitive disorders | — | AUROC: 0.62437 | R²: 0.01734 | sex, age, array, PCs 1-10 | — |
| PPM037075 | PGS018893 (TPMI_290_MegaPRS) |
PSS012815| East Asian Ancestry| 19,541 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Delirium dementia and amnestic and other cognitive disorders | — | AUROC: 0.62298 | R²: 0.01479 | sex, age, array, PCs 1-10 | — |
| PPM037076 | PGS018894 (TPMI_290_PRS-CS) |
PSS012816| East Asian Ancestry| 19,541 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Delirium dementia and amnestic and other cognitive disorders | — | AUROC: 0.62532 | R²: 0.01572 | sex, age, array, PCs 1-10 | — |
| PPM037077 | PGS018895 (TPMI_290_SBayesR) |
PSS012817| East Asian Ancestry| 19,541 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Delirium dementia and amnestic and other cognitive disorders | — | AUROC: 0.62077 | R²: 0.0167 | sex, age, array, PCs 1-10 | — |
| PPM037078 | PGS018896 (TPMI_290.1_Lassosum2) |
PSS012804| East Asian Ancestry| 19,405 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Dementias | — | AUROC: 0.64809 | R²: 0.01422 | sex, age, array, PCs 1-10 | — |
| PPM037079 | PGS018897 (TPMI_290.1_LDpred2) |
PSS012803| East Asian Ancestry| 19,405 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Dementias | — | AUROC: 0.65154 | R²: 0.01619 | sex, age, array, PCs 1-10 | — |
| PPM037080 | PGS018898 (TPMI_290.1_MegaPRS) |
PSS012805| East Asian Ancestry| 19,405 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Dementias | — | AUROC: 0.65054 | R²: 0.01474 | sex, age, array, PCs 1-10 | — |
| PPM037081 | PGS018899 (TPMI_290.1_PRS-CS) |
PSS012806| East Asian Ancestry| 19,405 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Dementias | — | AUROC: 0.65026 | R²: 0.01497 | sex, age, array, PCs 1-10 | — |
| PPM037082 | PGS018900 (TPMI_290.1_SBayesR) |
PSS012807| East Asian Ancestry| 19,405 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Dementias | — | AUROC: 0.65078 | R²: 0.01653 | sex, age, array, PCs 1-10 | — |
| PPM037084 | PGS018902 (TPMI_290.3_LDpred2) |
PSS012808| East Asian Ancestry| 19,293 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other persistent mental disorders due to conditions classified elsewhere | — | AUROC: 0.61641 | R²: 0.00539 | sex, age, array, PCs 1-10 | — |
| PPM037085 | PGS018903 (TPMI_290.3_MegaPRS) |
PSS012810| East Asian Ancestry| 19,293 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other persistent mental disorders due to conditions classified elsewhere | — | AUROC: 0.61476 | R²: 0.00495 | sex, age, array, PCs 1-10 | — |
| PPM037086 | PGS018904 (TPMI_290.3_PRS-CS) |
PSS012811| East Asian Ancestry| 19,293 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other persistent mental disorders due to conditions classified elsewhere | — | AUROC: 0.6178 | R²: 0.00583 | sex, age, array, PCs 1-10 | — |
| PPM037087 | PGS018905 (TPMI_290.3_SBayesR) |
PSS012812| East Asian Ancestry| 19,293 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other persistent mental disorders due to conditions classified elsewhere | — | AUROC: 0.6147 | R²: 0.00547 | sex, age, array, PCs 1-10 | — |
| PPM037088 | PGS018906 (TPMI_290.11_Lassosum2) |
PSS012794| East Asian Ancestry| 19,090 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Alzheimers disease | — | AUROC: 0.76144 | R²: 0.00843 | sex, age, array, PCs 1-10 | — |
| PPM037089 | PGS018907 (TPMI_290.11_LDpred2) |
PSS012793| East Asian Ancestry| 19,090 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Alzheimers disease | — | AUROC: 0.75585 | R²: 0.00809 | sex, age, array, PCs 1-10 | — |
| PPM037090 | PGS018908 (TPMI_290.11_MegaPRS) |
PSS012795| East Asian Ancestry| 19,090 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Alzheimers disease | — | AUROC: 0.7642 | R²: 0.00721 | sex, age, array, PCs 1-10 | — |
| PPM037091 | PGS018909 (TPMI_290.11_PRS-CS) |
PSS012796| East Asian Ancestry| 19,090 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Alzheimers disease | — | AUROC: 0.7599 | R²: 0.00843 | sex, age, array, PCs 1-10 | — |
| PPM037092 | PGS018910 (TPMI_290.11_SBayesR) |
PSS012797| East Asian Ancestry| 19,090 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Alzheimers disease | — | AUROC: 0.76174 | R²: 0.00834 | sex, age, array, PCs 1-10 | — |
| PPM037093 | PGS018911 (TPMI_290.13_Lassosum2) |
PSS012799| East Asian Ancestry| 19,255 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Senile dementia | — | AUROC: 0.65832 | R²: 0.01011 | sex, age, array, PCs 1-10 | — |
| PPM037094 | PGS018912 (TPMI_290.13_LDpred2) |
PSS012798| East Asian Ancestry| 19,255 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Senile dementia | — | AUROC: 0.65264 | R²: 0.00966 | sex, age, array, PCs 1-10 | — |
| PPM037095 | PGS018913 (TPMI_290.13_MegaPRS) |
PSS012800| East Asian Ancestry| 19,255 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Senile dementia | — | AUROC: 0.65171 | R²: 0.00896 | sex, age, array, PCs 1-10 | — |
| PPM037097 | PGS018915 (TPMI_290.13_SBayesR) |
PSS012802| East Asian Ancestry| 19,255 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Senile dementia | — | AUROC: 0.6513 | R²: 0.01019 | sex, age, array, PCs 1-10 | — |
| PPM037098 | PGS018916 (TPMI_291_Lassosum2) |
PSS012824| East Asian Ancestry| 19,413 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other specified nonpsychotic and or transient mental disorders | — | AUROC: 0.58453 | R²: 0.00427 | sex, age, array, PCs 1-10 | — |
| PPM037099 | PGS018917 (TPMI_291_LDpred2) |
PSS012823| East Asian Ancestry| 19,413 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other specified nonpsychotic and or transient mental disorders | — | AUROC: 0.58602 | R²: 0.00442 | sex, age, array, PCs 1-10 | — |
| PPM037100 | PGS018918 (TPMI_291_MegaPRS) |
PSS012825| East Asian Ancestry| 19,413 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other specified nonpsychotic and or transient mental disorders | — | AUROC: 0.58533 | R²: 0.00436 | sex, age, array, PCs 1-10 | — |
| PPM037102 | PGS018920 (TPMI_291_SBayesR) |
PSS012827| East Asian Ancestry| 19,413 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other specified nonpsychotic and or transient mental disorders | — | AUROC: 0.58508 | R²: 0.00441 | sex, age, array, PCs 1-10 | — |
| PPM037103 | PGS018921 (TPMI_291.4_Lassosum2) |
PSS012819| East Asian Ancestry| 19,296 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Specific nonpsychotic mental disorders due to brain damage | — | AUROC: 0.63227 | R²: 0.00552 | sex, age, array, PCs 1-10 | — |
| PPM037104 | PGS018922 (TPMI_291.4_LDpred2) |
PSS012818| East Asian Ancestry| 19,296 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Specific nonpsychotic mental disorders due to brain damage | — | AUROC: 0.63193 | R²: 0.00549 | sex, age, array, PCs 1-10 | — |
| PPM037105 | PGS018923 (TPMI_291.4_MegaPRS) |
PSS012820| East Asian Ancestry| 19,296 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Specific nonpsychotic mental disorders due to brain damage | — | AUROC: 0.63179 | R²: 0.0052 | sex, age, array, PCs 1-10 | — |
| PPM037106 | PGS018924 (TPMI_291.4_PRS-CS) |
PSS012821| East Asian Ancestry| 19,296 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Specific nonpsychotic mental disorders due to brain damage | — | AUROC: 0.632 | R²: 0.00549 | sex, age, array, PCs 1-10 | — |
| PPM037107 | PGS018925 (TPMI_291.4_SBayesR) |
PSS012822| East Asian Ancestry| 19,296 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Specific nonpsychotic mental disorders due to brain damage | — | AUROC: 0.63184 | R²: 0.00549 | sex, age, array, PCs 1-10 | — |
| PPM037108 | PGS018926 (TPMI_292_Lassosum2) |
PSS012834| East Asian Ancestry| 19,249 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Neurological disorders | — | AUROC: 0.61137 | R²: 0.00434 | sex, age, array, PCs 1-10 | — |
| PPM037109 | PGS018927 (TPMI_292_LDpred2) |
PSS012833| East Asian Ancestry| 19,249 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Neurological disorders | — | AUROC: 0.61151 | R²: 0.00436 | sex, age, array, PCs 1-10 | — |
| PPM037110 | PGS018928 (TPMI_292_MegaPRS) |
PSS012835| East Asian Ancestry| 19,249 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Neurological disorders | — | AUROC: 0.61409 | R²: 0.00451 | sex, age, array, PCs 1-10 | — |
| PPM037111 | PGS018929 (TPMI_292_PRS-CS) |
PSS012836| East Asian Ancestry| 19,249 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Neurological disorders | — | AUROC: 0.61139 | R²: 0.00435 | sex, age, array, PCs 1-10 | — |
| PPM037112 | PGS018930 (TPMI_292_SBayesR) |
PSS012837| East Asian Ancestry| 19,249 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Neurological disorders | — | AUROC: 0.61126 | R²: 0.00439 | sex, age, array, PCs 1-10 | — |
| PPM037118 | PGS018936 (TPMI_296.2_Lassosum2) |
PSS012839| East Asian Ancestry| 14,694 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Depression | — | AUROC: 0.67117 | R²: 0.05472 | sex, age, array, PCs 1-10 | — |
| PPM037119 | PGS018937 (TPMI_296.2_LDpred2) |
PSS012838| East Asian Ancestry| 14,694 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Depression | — | AUROC: 0.66911 | R²: 0.05437 | sex, age, array, PCs 1-10 | — |
| PPM037121 | PGS018939 (TPMI_296.2_PRS-CS) |
PSS012841| East Asian Ancestry| 14,694 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Depression | — | AUROC: 0.67254 | R²: 0.05586 | sex, age, array, PCs 1-10 | — |
| PPM037122 | PGS018940 (TPMI_296.2_SBayesR) |
PSS012842| East Asian Ancestry| 14,694 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Depression | — | AUROC: 0.66833 | R²: 0.05398 | sex, age, array, PCs 1-10 | — |
| PPM037123 | PGS018941 (TPMI_300.11_Lassosum2) |
PSS012844| East Asian Ancestry| 14,642 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Generalized anxiety disorder | — | AUROC: 0.59145 | R²: 0.01052 | sex, age, array, PCs 1-10 | — |
| PPM037124 | PGS018942 (TPMI_300.11_LDpred2) |
PSS012843| East Asian Ancestry| 14,642 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Generalized anxiety disorder | — | AUROC: 0.5935 | R²: 0.01111 | sex, age, array, PCs 1-10 | — |
| PPM037125 | PGS018943 (TPMI_300.11_MegaPRS) |
PSS012845| East Asian Ancestry| 14,642 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Generalized anxiety disorder | — | AUROC: 0.59612 | R²: 0.01112 | sex, age, array, PCs 1-10 | — |
| PPM037126 | PGS018944 (TPMI_300.11_PRS-CS) |
PSS012846| East Asian Ancestry| 14,642 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Generalized anxiety disorder | — | AUROC: 0.59422 | R²: 0.01116 | sex, age, array, PCs 1-10 | — |
| PPM037127 | PGS018945 (TPMI_300.11_SBayesR) |
PSS012847| East Asian Ancestry| 14,642 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Generalized anxiety disorder | — | AUROC: 0.59236 | R²: 0.01101 | sex, age, array, PCs 1-10 | — |
| PPM037128 | PGS018946 (TPMI_306_Lassosum2) |
PSS012849| East Asian Ancestry| 16,706 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other mental disorder | — | AUROC: 0.63543 | R²: 0.04391 | sex, age, array, PCs 1-10 | — |
| PPM037129 | PGS018947 (TPMI_306_LDpred2) |
PSS012848| East Asian Ancestry| 16,706 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other mental disorder | — | AUROC: 0.63546 | R²: 0.04397 | sex, age, array, PCs 1-10 | — |
| PPM037130 | PGS018948 (TPMI_306_MegaPRS) |
PSS012850| East Asian Ancestry| 16,706 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other mental disorder | — | AUROC: 0.63533 | R²: 0.04383 | sex, age, array, PCs 1-10 | — |
| PPM037132 | PGS018950 (TPMI_306_SBayesR) |
PSS012852| East Asian Ancestry| 16,706 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other mental disorder | — | AUROC: 0.63613 | R²: 0.04434 | sex, age, array, PCs 1-10 | — |
| PPM037133 | PGS018951 (TPMI_315_Lassosum2) |
PSS012854| East Asian Ancestry| 19,934 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Develomental delays and disorders | — | AUROC: 0.66544 | R²: 0.00499 | sex, age, array, PCs 1-10 | — |
| PPM037134 | PGS018952 (TPMI_315_LDpred2) |
PSS012853| East Asian Ancestry| 19,934 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Develomental delays and disorders | — | AUROC: 0.66519 | R²: 0.00497 | sex, age, array, PCs 1-10 | — |
| PPM037135 | PGS018953 (TPMI_315_MegaPRS) |
PSS012855| East Asian Ancestry| 19,934 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Develomental delays and disorders | — | AUROC: 0.66353 | R²: 0.00494 | sex, age, array, PCs 1-10 | — |
| PPM037136 | PGS018954 (TPMI_315_PRS-CS) |
PSS012856| East Asian Ancestry| 19,934 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Develomental delays and disorders | — | AUROC: 0.66181 | R²: 0.00498 | sex, age, array, PCs 1-10 | — |
| PPM037137 | PGS018955 (TPMI_315_SBayesR) |
PSS012857| East Asian Ancestry| 19,934 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Develomental delays and disorders | — | AUROC: 0.66238 | R²: 0.00511 | sex, age, array, PCs 1-10 | — |
| PPM037168 | PGS018986 (TPMI_340_Lassosum2) |
PSS012889| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76375 | R²: 0.11662 | sex, age, array, PCs 1-10 | — |
| PPM037169 | PGS018987 (TPMI_340_LDpred2) |
PSS012888| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76372 | R²: 0.11649 | sex, age, array, PCs 1-10 | — |
| PPM037170 | PGS018988 (TPMI_340_MegaPRS) |
PSS012890| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76013 | R²: 0.11377 | sex, age, array, PCs 1-10 | — |
| PPM037171 | PGS018989 (TPMI_340_PRS-CS) |
PSS012891| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76286 | R²: 0.11567 | sex, age, array, PCs 1-10 | — |
| PPM037172 | PGS018990 (TPMI_340_SBayesR) |
PSS012892| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76335 | R²: 0.11547 | sex, age, array, PCs 1-10 | — |
| PPM037173 | PGS018991 (TPMI_345.1_Lassosum2) |
PSS012894| East Asian Ancestry| 18,476 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Epilepsy | — | AUROC: 0.70084 | R²: 0.01046 | sex, age, array, PCs 1-10 | — |
| PPM037174 | PGS018992 (TPMI_345.1_LDpred2) |
PSS012893| East Asian Ancestry| 18,476 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Epilepsy | — | AUROC: 0.70066 | R²: 0.01046 | sex, age, array, PCs 1-10 | — |
| PPM037175 | PGS018993 (TPMI_345.1_MegaPRS) |
PSS012895| East Asian Ancestry| 18,476 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Epilepsy | — | AUROC: 0.70152 | R²: 0.01049 | sex, age, array, PCs 1-10 | — |
| PPM037176 | PGS018994 (TPMI_345.1_PRS-CS) |
PSS012896| East Asian Ancestry| 18,476 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Epilepsy | — | AUROC: 0.70027 | R²: 0.01057 | sex, age, array, PCs 1-10 | — |
| PPM037177 | PGS018995 (TPMI_345.1_SBayesR) |
PSS012897| East Asian Ancestry| 18,476 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Epilepsy | — | AUROC: 0.7006 | R²: 0.01046 | sex, age, array, PCs 1-10 | — |
| PPM037179 | PGS018997 (TPMI_352.2_LDpred2) |
PSS012898| East Asian Ancestry| 18,297 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Facial nerve disorders CN7 | — | AUROC: 0.67176 | R²: 0.01121 | sex, age, array, PCs 1-10 | — |
| PPM037180 | PGS018998 (TPMI_352.2_MegaPRS) |
PSS012900| East Asian Ancestry| 18,297 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Facial nerve disorders CN7 | — | AUROC: 0.67501 | R²: 0.01142 | sex, age, array, PCs 1-10 | — |
| PPM037181 | PGS018999 (TPMI_352.2_PRS-CS) |
PSS012901| East Asian Ancestry| 18,297 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Facial nerve disorders CN7 | — | AUROC: 0.67303 | R²: 0.01128 | sex, age, array, PCs 1-10 | — |
| PPM037182 | PGS019000 (TPMI_352.2_SBayesR) |
PSS012902| East Asian Ancestry| 18,297 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Facial nerve disorders CN7 | — | AUROC: 0.67171 | R²: 0.0112 | sex, age, array, PCs 1-10 | — |
| PPM037183 | PGS019001 (TPMI_357_Lassosum2) |
PSS012904| East Asian Ancestry| 19,044 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Inflammatory and toxic neuropathy | — | AUROC: 0.60542 | R²: 0.01438 | sex, age, array, PCs 1-10 | — |
| PPM037184 | PGS019002 (TPMI_357_LDpred2) |
PSS012903| East Asian Ancestry| 19,044 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Inflammatory and toxic neuropathy | — | AUROC: 0.60618 | R²: 0.0144 | sex, age, array, PCs 1-10 | — |
| PPM037185 | PGS019003 (TPMI_357_MegaPRS) |
PSS012905| East Asian Ancestry| 19,044 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Inflammatory and toxic neuropathy | — | AUROC: 0.60195 | R²: 0.01347 | sex, age, array, PCs 1-10 | — |
| PPM037186 | PGS019004 (TPMI_357_PRS-CS) |
PSS012906| East Asian Ancestry| 19,044 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Inflammatory and toxic neuropathy | — | AUROC: 0.6048 | R²: 0.01407 | sex, age, array, PCs 1-10 | — |
| PPM037188 | PGS019006 (TPMI_361_Lassosum2) |
PSS012909| East Asian Ancestry| 17,638 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Retinal detachments and defects | — | AUROC: 0.64518 | R²: 0.01185 | sex, age, array, PCs 1-10 | — |
| PPM037189 | PGS019007 (TPMI_361_LDpred2) |
PSS012908| East Asian Ancestry| 17,638 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Retinal detachments and defects | — | AUROC: 0.64405 | R²: 0.01162 | sex, age, array, PCs 1-10 | — |
| PPM037190 | PGS019008 (TPMI_361_MegaPRS) |
PSS012910| East Asian Ancestry| 17,638 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Retinal detachments and defects | — | AUROC: 0.64402 | R²: 0.01161 | sex, age, array, PCs 1-10 | — |
| PPM037191 | PGS019009 (TPMI_361_PRS-CS) |
PSS012911| East Asian Ancestry| 17,638 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Retinal detachments and defects | — | AUROC: 0.64418 | R²: 0.01161 | sex, age, array, PCs 1-10 | — |
| PPM037192 | PGS019010 (TPMI_361_SBayesR) |
PSS012912| East Asian Ancestry| 17,638 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Retinal detachments and defects | — | AUROC: 0.64456 | R²: 0.01164 | sex, age, array, PCs 1-10 | — |
| PPM037193 | PGS019011 (TPMI_362_Lassosum2) |
PSS012934| East Asian Ancestry| 18,643 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other retinal disorders | — | AUROC: 0.56005 | R²: 0.01551 | sex, age, array, PCs 1-10 | — |
| PPM037194 | PGS019012 (TPMI_362_LDpred2) |
PSS012933| East Asian Ancestry| 18,643 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other retinal disorders | — | AUROC: 0.56621 | R²: 0.01747 | sex, age, array, PCs 1-10 | — |
| PPM037195 | PGS019013 (TPMI_362_MegaPRS) |
PSS012935| East Asian Ancestry| 18,643 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other retinal disorders | — | AUROC: 0.56323 | R²: 0.01687 | sex, age, array, PCs 1-10 | — |
| PPM037196 | PGS019014 (TPMI_362_PRS-CS) |
PSS012936| East Asian Ancestry| 18,643 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other retinal disorders | — | AUROC: 0.56337 | R²: 0.01671 | sex, age, array, PCs 1-10 | — |
| PPM037197 | PGS019015 (TPMI_362_SBayesR) |
PSS012937| East Asian Ancestry| 18,643 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other retinal disorders | — | AUROC: 0.56231 | R²: 0.01628 | sex, age, array, PCs 1-10 | — |
| PPM037199 | PGS019017 (TPMI_362.2_LDpred2) |
PSS012923| East Asian Ancestry| 17,925 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Degeneration of macula and posterior pole of retina | — | AUROC: 0.58598 | R²: 0.00867 | sex, age, array, PCs 1-10 | — |
| PPM037200 | PGS019018 (TPMI_362.2_MegaPRS) |
PSS012925| East Asian Ancestry| 17,925 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Degeneration of macula and posterior pole of retina | — | AUROC: 0.58426 | R²: 0.00872 | sex, age, array, PCs 1-10 | — |
| PPM037201 | PGS019019 (TPMI_362.2_PRS-CS) |
PSS012926| East Asian Ancestry| 17,925 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Degeneration of macula and posterior pole of retina | — | AUROC: 0.58662 | R²: 0.00887 | sex, age, array, PCs 1-10 | — |
| PPM037202 | PGS019020 (TPMI_362.2_SBayesR) |
PSS012927| East Asian Ancestry| 17,925 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Degeneration of macula and posterior pole of retina | — | AUROC: 0.58547 | R²: 0.00857 | sex, age, array, PCs 1-10 | — |
| PPM037203 | PGS019021 (TPMI_362.6_Lassosum2) |
PSS012929| East Asian Ancestry| 17,530 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Peripheral retinal degenerations | — | AUROC: 0.66601 | R²: 0.00976 | sex, age, array, PCs 1-10 | — |
| PPM037204 | PGS019022 (TPMI_362.6_LDpred2) |
PSS012928| East Asian Ancestry| 17,530 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Peripheral retinal degenerations | — | AUROC: 0.66588 | R²: 0.00975 | sex, age, array, PCs 1-10 | — |
| PPM037205 | PGS019023 (TPMI_362.6_MegaPRS) |
PSS012930| East Asian Ancestry| 17,530 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Peripheral retinal degenerations | — | AUROC: 0.66599 | R²: 0.00976 | sex, age, array, PCs 1-10 | — |
| PPM037206 | PGS019024 (TPMI_362.6_PRS-CS) |
PSS012931| East Asian Ancestry| 17,530 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Peripheral retinal degenerations | — | AUROC: 0.66592 | R²: 0.00976 | sex, age, array, PCs 1-10 | — |
| PPM037207 | PGS019025 (TPMI_362.6_SBayesR) |
PSS012932| East Asian Ancestry| 17,530 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Peripheral retinal degenerations | — | AUROC: 0.66718 | R²: 0.00993 | sex, age, array, PCs 1-10 | — |
| PPM037208 | PGS019026 (TPMI_362.26_Lassosum2) |
PSS012914| East Asian Ancestry| 17,554 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular puckering of retina | — | AUROC: 0.65845 | R²: 0.00658 | sex, age, array, PCs 1-10 | — |
| PPM037209 | PGS019027 (TPMI_362.26_LDpred2) |
PSS012913| East Asian Ancestry| 17,554 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular puckering of retina | — | AUROC: 0.66467 | R²: 0.00729 | sex, age, array, PCs 1-10 | — |
| PPM037210 | PGS019028 (TPMI_362.26_MegaPRS) |
PSS012915| East Asian Ancestry| 17,554 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular puckering of retina | — | AUROC: 0.65624 | R²: 0.00642 | sex, age, array, PCs 1-10 | — |
| PPM037211 | PGS019029 (TPMI_362.26_PRS-CS) |
PSS012916| East Asian Ancestry| 17,554 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular puckering of retina | — | AUROC: 0.66164 | R²: 0.00691 | sex, age, array, PCs 1-10 | — |
| PPM037212 | PGS019030 (TPMI_362.26_SBayesR) |
PSS012917| East Asian Ancestry| 17,554 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular puckering of retina | — | AUROC: 0.65794 | R²: 0.00674 | sex, age, array, PCs 1-10 | — |
| PPM037213 | PGS019031 (TPMI_362.29_Lassosum2) |
PSS012919| East Asian Ancestry| 17,901 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular degeneration senile of retina NOS | — | AUROC: 0.59018 | R²: 0.00782 | sex, age, array, PCs 1-10 | — |
| PPM037214 | PGS019032 (TPMI_362.29_LDpred2) |
PSS012918| East Asian Ancestry| 17,901 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular degeneration senile of retina NOS | — | AUROC: 0.59322 | R²: 0.00832 | sex, age, array, PCs 1-10 | — |
| PPM037215 | PGS019033 (TPMI_362.29_MegaPRS) |
PSS012920| East Asian Ancestry| 17,901 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular degeneration senile of retina NOS | — | AUROC: 0.58856 | R²: 0.00791 | sex, age, array, PCs 1-10 | — |
| PPM037217 | PGS019035 (TPMI_362.29_SBayesR) |
PSS012922| East Asian Ancestry| 17,901 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular degeneration senile of retina NOS | — | AUROC: 0.59257 | R²: 0.00812 | sex, age, array, PCs 1-10 | — |
| PPM037263 | PGS019081 (TPMI_386_Lassosum2) |
PSS013009| East Asian Ancestry| 19,232 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Vertiginous syndromes and other disorders of vestibular system | — | AUROC: 0.59319 | R²: 0.03898 | sex, age, array, PCs 1-10 | — |
| PPM037264 | PGS019082 (TPMI_386_LDpred2) |
PSS013008| East Asian Ancestry| 19,232 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Vertiginous syndromes and other disorders of vestibular system | — | AUROC: 0.59425 | R²: 0.04012 | sex, age, array, PCs 1-10 | — |
| PPM037265 | PGS019083 (TPMI_386_MegaPRS) |
PSS013010| East Asian Ancestry| 19,232 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Vertiginous syndromes and other disorders of vestibular system | — | AUROC: 0.59217 | R²: 0.03816 | sex, age, array, PCs 1-10 | — |
| PPM037266 | PGS019084 (TPMI_386_PRS-CS) |
PSS013011| East Asian Ancestry| 19,232 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Vertiginous syndromes and other disorders of vestibular system | — | AUROC: 0.5934 | R²: 0.0392 | sex, age, array, PCs 1-10 | — |
| PPM037267 | PGS019085 (TPMI_386_SBayesR) |
PSS013012| East Asian Ancestry| 19,232 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Vertiginous syndromes and other disorders of vestibular system | — | AUROC: 0.59204 | R²: 0.03809 | sex, age, array, PCs 1-10 | — |
| PPM037268 | PGS019086 (TPMI_386.1_Lassosum2) |
PSS012984| East Asian Ancestry| 17,579 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Menieres disease | — | AUROC: 0.61707 | R²: 0.01248 | sex, age, array, PCs 1-10 | — |
| PPM037269 | PGS019087 (TPMI_386.1_LDpred2) |
PSS012983| East Asian Ancestry| 17,579 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Menieres disease | — | AUROC: 0.61731 | R²: 0.01262 | sex, age, array, PCs 1-10 | — |
| PPM037270 | PGS019088 (TPMI_386.1_MegaPRS) |
PSS012985| East Asian Ancestry| 17,579 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Menieres disease | — | AUROC: 0.61749 | R²: 0.01255 | sex, age, array, PCs 1-10 | — |
| PPM037271 | PGS019089 (TPMI_386.1_PRS-CS) |
PSS012986| East Asian Ancestry| 17,579 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Menieres disease | — | AUROC: 0.61682 | R²: 0.01254 | sex, age, array, PCs 1-10 | — |
| PPM037272 | PGS019090 (TPMI_386.1_SBayesR) |
PSS012987| East Asian Ancestry| 17,579 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Menieres disease | — | AUROC: 0.61747 | R²: 0.01243 | sex, age, array, PCs 1-10 | — |
| PPM037293 | PGS019111 (TPMI_389_Lassosum2) |
PSS013024| East Asian Ancestry| 19,259 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hearing loss | — | AUROC: 0.5933 | R²: 0.02351 | sex, age, array, PCs 1-10 | — |
| PPM037294 | PGS019112 (TPMI_389_LDpred2) |
PSS013023| East Asian Ancestry| 19,259 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hearing loss | — | AUROC: 0.59236 | R²: 0.02335 | sex, age, array, PCs 1-10 | — |
| PPM037295 | PGS019113 (TPMI_389_MegaPRS) |
PSS013025| East Asian Ancestry| 19,259 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hearing loss | — | AUROC: 0.58885 | R²: 0.0216 | sex, age, array, PCs 1-10 | — |
| PPM037296 | PGS019114 (TPMI_389_PRS-CS) |
PSS013026| East Asian Ancestry| 19,259 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hearing loss | — | AUROC: 0.59015 | R²: 0.02245 | sex, age, array, PCs 1-10 | — |
| PPM037297 | PGS019115 (TPMI_389_SBayesR) |
PSS013027| East Asian Ancestry| 19,259 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hearing loss | — | AUROC: 0.58585 | R²: 0.02066 | sex, age, array, PCs 1-10 | — |
| PPM037298 | PGS019116 (TPMI_389.1_Lassosum2) |
PSS013014| East Asian Ancestry| 18,218 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sensorineural hearing loss | — | AUROC: 0.60128 | R²: 0.00481 | sex, age, array, PCs 1-10 | — |
| PPM037299 | PGS019117 (TPMI_389.1_LDpred2) |
PSS013013| East Asian Ancestry| 18,218 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sensorineural hearing loss | — | AUROC: 0.60384 | R²: 0.00487 | sex, age, array, PCs 1-10 | — |
| PPM037301 | PGS019119 (TPMI_389.1_PRS-CS) |
PSS013016| East Asian Ancestry| 18,218 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sensorineural hearing loss | — | AUROC: 0.59978 | R²: 0.0048 | sex, age, array, PCs 1-10 | — |
| PPM037302 | PGS019120 (TPMI_389.1_SBayesR) |
PSS013017| East Asian Ancestry| 18,218 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sensorineural hearing loss | — | AUROC: 0.59804 | R²: 0.00448 | sex, age, array, PCs 1-10 | — |
| PPM037397 | PGS019215 (TPMI_430_Lassosum2) |
PSS013123| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66064 | R²: 0.01278 | sex, age, array, PCs 1-10 | — |
| PPM037398 | PGS019216 (TPMI_430_LDpred2) |
PSS013122| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66428 | R²: 0.01316 | sex, age, array, PCs 1-10 | — |
| PPM037399 | PGS019217 (TPMI_430_MegaPRS) |
PSS013124| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.65946 | R²: 0.01257 | sex, age, array, PCs 1-10 | — |
| PPM037401 | PGS019219 (TPMI_430_SBayesR) |
PSS013126| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.65968 | R²: 0.01263 | sex, age, array, PCs 1-10 | — |
| PPM037402 | PGS019220 (TPMI_430.2_Lassosum2) |
PSS013118| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66204 | R²: 0.00902 | sex, age, array, PCs 1-10 | — |
| PPM037403 | PGS019221 (TPMI_430.2_LDpred2) |
PSS013117| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66451 | R²: 0.00928 | sex, age, array, PCs 1-10 | — |
| PPM037404 | PGS019222 (TPMI_430.2_MegaPRS) |
PSS013119| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66942 | R²: 0.01012 | sex, age, array, PCs 1-10 | — |
| PPM037405 | PGS019223 (TPMI_430.2_PRS-CS) |
PSS013120| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66267 | R²: 0.00903 | sex, age, array, PCs 1-10 | — |
| PPM037406 | PGS019224 (TPMI_430.2_SBayesR) |
PSS013121| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66098 | R²: 0.00882 | sex, age, array, PCs 1-10 | — |
| PPM037407 | PGS019225 (TPMI_433_Lassosum2) |
PSS013153| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58403 | R²: 0.0205 | sex, age, array, PCs 1-10 | — |
| PPM037408 | PGS019226 (TPMI_433_LDpred2) |
PSS013152| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58583 | R²: 0.0211 | sex, age, array, PCs 1-10 | — |
| PPM037409 | PGS019227 (TPMI_433_MegaPRS) |
PSS013154| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58307 | R²: 0.02029 | sex, age, array, PCs 1-10 | — |
| PPM037411 | PGS019229 (TPMI_433_SBayesR) |
PSS013156| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58559 | R²: 0.02111 | sex, age, array, PCs 1-10 | — |
| PPM037412 | PGS019230 (TPMI_433.2_Lassosum2) |
PSS013133| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64904 | R²: 0.05282 | sex, age, array, PCs 1-10 | — |
| PPM037413 | PGS019231 (TPMI_433.2_LDpred2) |
PSS013132| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64962 | R²: 0.0533 | sex, age, array, PCs 1-10 | — |
| PPM037414 | PGS019232 (TPMI_433.2_MegaPRS) |
PSS013134| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64321 | R²: 0.04993 | sex, age, array, PCs 1-10 | — |
| PPM037415 | PGS019233 (TPMI_433.2_PRS-CS) |
PSS013135| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.65154 | R²: 0.05411 | sex, age, array, PCs 1-10 | — |
| PPM037416 | PGS019234 (TPMI_433.2_SBayesR) |
PSS013136| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64638 | R²: 0.05144 | sex, age, array, PCs 1-10 | — |
| PPM037422 | PGS019240 (TPMI_433.6_Lassosum2) |
PSS013143| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67118 | R²: 0.01491 | sex, age, array, PCs 1-10 | — |
| PPM037423 | PGS019241 (TPMI_433.6_LDpred2) |
PSS013142| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67222 | R²: 0.01499 | sex, age, array, PCs 1-10 | — |
| PPM037424 | PGS019242 (TPMI_433.6_MegaPRS) |
PSS013144| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.6716 | R²: 0.01494 | sex, age, array, PCs 1-10 | — |
| PPM037425 | PGS019243 (TPMI_433.6_PRS-CS) |
PSS013145| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67259 | R²: 0.01516 | sex, age, array, PCs 1-10 | — |
| PPM037426 | PGS019244 (TPMI_433.6_SBayesR) |
PSS013146| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.672 | R²: 0.01494 | sex, age, array, PCs 1-10 | — |
| PPM037427 | PGS019245 (TPMI_433.8_Lassosum2) |
PSS013148| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63759 | R²: 0.01205 | sex, age, array, PCs 1-10 | — |
| PPM037428 | PGS019246 (TPMI_433.8_LDpred2) |
PSS013147| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63716 | R²: 0.01173 | sex, age, array, PCs 1-10 | — |
| PPM037430 | PGS019248 (TPMI_433.8_PRS-CS) |
PSS013150| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63925 | R²: 0.01237 | sex, age, array, PCs 1-10 | — |
| PPM037431 | PGS019249 (TPMI_433.8_SBayesR) |
PSS013151| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63585 | R²: 0.01168 | sex, age, array, PCs 1-10 | — |
| PPM037432 | PGS019250 (TPMI_433.21_Lassosum2) |
PSS013128| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66398 | R²: 0.03769 | sex, age, array, PCs 1-10 | — |
| PPM037433 | PGS019251 (TPMI_433.21_LDpred2) |
PSS013127| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66506 | R²: 0.03875 | sex, age, array, PCs 1-10 | — |
| PPM037434 | PGS019252 (TPMI_433.21_MegaPRS) |
PSS013129| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66288 | R²: 0.03706 | sex, age, array, PCs 1-10 | — |
| PPM037435 | PGS019253 (TPMI_433.21_PRS-CS) |
PSS013130| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.67066 | R²: 0.04063 | sex, age, array, PCs 1-10 | — |
| PPM038108 | PGS019928 (Insomnia UKB) |
PSS013823| Multi-ancestry (including European)| 16,637 individuals |
PGP000836 | Wyss AB et al. Sleep (2026) |
Reported Trait: Insomnia (WHIIRS >=10, or modified 3-question WHIIRS >=6 in ARIC) | OR: 1.17 [1.111, 1.22] | — | Incremental variance explained by the PRS for WHIIRS>=10: 0.27 [0.11, 0.48] | Age, sex, study center, ancestry principal components; race additionally included in BHS. | Incremental variance explained was reported as a percentage and estimated in unrelated HCHS/SOL participants. The score was constructed from UKB GWAS summary statistics using PRS-CS and evaluated across ARIC, HCHS/SOL, MESA and BHS. Fixed-effect meta-analysis p for heterogeneity = 0.69. HCHS/SOL analyses incorporated sampling weights. |
| PPM038109 | PGS019929 (Insomnia MVP EUR) |
PSS013823| Multi-ancestry (including European)| 16,637 individuals |
PGP000836 | Wyss AB et al. Sleep (2026) |
Reported Trait: Insomnia (WHIIRS >=10, or modified 3-question WHIIRS >=6 in ARIC) | OR: 1.19 | — | — | Age, sex, study center, ancestry principal components; race additionally included in BHS. | European-ancestry score constructed from MVP GWAS summary statistics using PRS-CSx and evaluated as a stand-alone score across ARIC, HCHS/SOL, MESA and BHS. Fixed-effect meta-analysis p for heterogeneity = 0.49. HCHS/SOL analyses incorporated sampling weights. |
| PPM038110 | PGS019933 (Insomnia UKB+MVP EUR (meta-analyzed)) |
PSS013823| Multi-ancestry (including European)| 16,637 individuals |
PGP000836 | Wyss AB et al. Sleep (2026) |
Reported Trait: Insomnia (WHIIRS >=10, or modified 3-question WHIIRS >=6 in ARIC) | OR: 1.27 | — | — | Age, sex, study center, ancestry principal components; race additionally included in BHS. | The score was constructed from meta-analysed UKB and MVP European-ancestry GWAS summary statistics using PRS-CS and evaluated across ARIC, HCHS/SOL, MESA and BHS. Significant between-study heterogeneity was observed (p for heterogeneity = 0.006); the manuscript also reports random-effects results. HCHS/SOL analyses incorporated sampling weights. |
| PPM036642 | PGS018460 (TPMI_145.2_Lassosum2) |
PSS012358| East Asian Ancestry| 19,060 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cancer of tongue | — | AUROC: 0.68616 | R²: 0.01171 | sex, age, array, PCs 1-10 | — |
| PPM036643 | PGS018461 (TPMI_145.2_LDpred2) |
PSS012357| East Asian Ancestry| 19,060 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cancer of tongue | — | AUROC: 0.68599 | R²: 0.01168 | sex, age, array, PCs 1-10 | — |
| PPM036644 | PGS018462 (TPMI_145.2_MegaPRS) |
PSS012359| East Asian Ancestry| 19,060 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cancer of tongue | — | AUROC: 0.68604 | R²: 0.0117 | sex, age, array, PCs 1-10 | — |
| PPM036646 | PGS018464 (TPMI_145.2_SBayesR) |
PSS012361| East Asian Ancestry| 19,060 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cancer of tongue | — | AUROC: 0.68563 | R²: 0.01173 | sex, age, array, PCs 1-10 | — |
| PPM036757 | PGS018575 (TPMI_191_Lassosum2) |
PSS012478| East Asian Ancestry| 19,669 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Manlignant and unknown neoplasms of brain and nervous system | — | AUROC: 0.69472 | R²: 0.01255 | sex, age, array, PCs 1-10 | — |
| PPM036759 | PGS018577 (TPMI_191_MegaPRS) |
PSS012479| East Asian Ancestry| 19,669 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Manlignant and unknown neoplasms of brain and nervous system | — | AUROC: 0.69455 | R²: 0.0126 | sex, age, array, PCs 1-10 | — |
| PPM036761 | PGS018579 (TPMI_191_SBayesR) |
PSS012481| East Asian Ancestry| 19,669 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Manlignant and unknown neoplasms of brain and nervous system | — | AUROC: 0.69618 | R²: 0.01269 | sex, age, array, PCs 1-10 | — |
| PPM036812 | PGS018630 (TPMI_225_Lassosum2) |
PSS012533| East Asian Ancestry| 19,663 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Benign neoplasm of brain and other parts of nervous system | — | AUROC: 0.66017 | R²: 0.00803 | sex, age, array, PCs 1-10 | — |
| PPM036813 | PGS018631 (TPMI_225_LDpred2) |
PSS012532| East Asian Ancestry| 19,663 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Benign neoplasm of brain and other parts of nervous system | — | AUROC: 0.66156 | R²: 0.00841 | sex, age, array, PCs 1-10 | — |
| PPM037154 | PGS018972 (TPMI_327.7_LDpred2) |
PSS012878| East Asian Ancestry| 16,204 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sleep related movement disorders | — | AUROC: 0.59366 | R²: 0.00218 | sex, age, array, PCs 1-10 | — |
| PPM036814 | PGS018632 (TPMI_225_MegaPRS) |
PSS012534| East Asian Ancestry| 19,663 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Benign neoplasm of brain and other parts of nervous system | — | AUROC: 0.66091 | R²: 0.00806 | sex, age, array, PCs 1-10 | — |
| PPM037155 | PGS018973 (TPMI_327.7_MegaPRS) |
PSS012880| East Asian Ancestry| 16,204 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sleep related movement disorders | — | AUROC: 0.59286 | R²: 0.00226 | sex, age, array, PCs 1-10 | — |
| PPM036816 | PGS018634 (TPMI_225_SBayesR) |
PSS012536| East Asian Ancestry| 19,663 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Benign neoplasm of brain and other parts of nervous system | — | AUROC: 0.65916 | R²: 0.00802 | sex, age, array, PCs 1-10 | — |
| PPM036916 | PGS018734 (TPMI_250.6_Lassosum2) |
PSS012666| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.64672 | R²: 0.02095 | sex, age, array, PCs 1-10 | — |
| PPM036918 | PGS018736 (TPMI_250.6_MegaPRS) |
PSS012667| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.63648 | R²: 0.017 | sex, age, array, PCs 1-10 | — |
| PPM036919 | PGS018737 (TPMI_250.6_PRS-CS) |
PSS012668| East Asian Ancestry| 14,427 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Polyneuropathy in diabetes | — | AUROC: 0.6604 | R²: 0.02481 | sex, age, array, PCs 1-10 | — |
| PPM036922 | PGS018740 (TPMI_250.7_Lassosum2) |
PSS012672| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.62187 | R²: 0.01769 | sex, age, array, PCs 1-10 | — |
| PPM036923 | PGS018741 (TPMI_250.7_LDpred2) |
PSS012671| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.63759 | R²: 0.02299 | sex, age, array, PCs 1-10 | — |
| PPM036924 | PGS018742 (TPMI_250.7_MegaPRS) |
PSS012673| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.6363 | R²: 0.02173 | sex, age, array, PCs 1-10 | — |
| PPM036925 | PGS018743 (TPMI_250.7_PRS-CS) |
PSS012674| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.64129 | R²: 0.02379 | sex, age, array, PCs 1-10 | — |
| PPM036926 | PGS018744 (TPMI_250.7_PRSmix+) |
PSS012675| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.69783 | R²: 0.04794 | sex, age, array, PCs 1-10 | — |
| PPM036927 | PGS018745 (TPMI_250.7_SBayesR) |
PSS012676| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.63067 | R²: 0.0204 | sex, age, array, PCs 1-10 | — |
| PPM037156 | PGS018974 (TPMI_327.7_PRS-CS) |
PSS012881| East Asian Ancestry| 16,204 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sleep related movement disorders | — | AUROC: 0.59362 | R²: 0.00215 | sex, age, array, PCs 1-10 | — |
| PPM037157 | PGS018975 (TPMI_327.7_SBayesR) |
PSS012882| East Asian Ancestry| 16,204 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sleep related movement disorders | — | AUROC: 0.5943 | R²: 0.00216 | sex, age, array, PCs 1-10 | — |
| PPM037158 | PGS018976 (TPMI_327.41_Lassosum2) |
PSS012869| East Asian Ancestry| 17,271 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Organic or persistent insomnia | — | AUROC: 0.63693 | R²: 0.03544 | sex, age, array, PCs 1-10 | — |
| PPM037083 | PGS018901 (TPMI_290.3_Lassosum2) |
PSS012809| East Asian Ancestry| 19,293 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other persistent mental disorders due to conditions classified elsewhere | — | AUROC: 0.61692 | R²: 0.00516 | sex, age, array, PCs 1-10 | — |
| PPM037096 | PGS018914 (TPMI_290.13_PRS-CS) |
PSS012801| East Asian Ancestry| 19,255 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Senile dementia | — | AUROC: 0.65473 | R²: 0.0099 | sex, age, array, PCs 1-10 | — |
| PPM037101 | PGS018919 (TPMI_291_PRS-CS) |
PSS012826| East Asian Ancestry| 19,413 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other specified nonpsychotic and or transient mental disorders | — | AUROC: 0.58595 | R²: 0.00447 | sex, age, array, PCs 1-10 | — |
| PPM037120 | PGS018938 (TPMI_296.2_MegaPRS) |
PSS012840| East Asian Ancestry| 14,694 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Depression | — | AUROC: 0.66585 | R²: 0.05261 | sex, age, array, PCs 1-10 | — |
| PPM037131 | PGS018949 (TPMI_306_PRS-CS) |
PSS012851| East Asian Ancestry| 16,706 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other mental disorder | — | AUROC: 0.63575 | R²: 0.04417 | sex, age, array, PCs 1-10 | — |
| PPM037162 | PGS018980 (TPMI_327.41_SBayesR) |
PSS012872| East Asian Ancestry| 17,271 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Organic or persistent insomnia | — | AUROC: 0.63665 | R²: 0.03558 | sex, age, array, PCs 1-10 | — |
| PPM037178 | PGS018996 (TPMI_352.2_Lassosum2) |
PSS012899| East Asian Ancestry| 18,297 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Facial nerve disorders CN7 | — | AUROC: 0.67307 | R²: 0.01135 | sex, age, array, PCs 1-10 | — |
| PPM037187 | PGS019005 (TPMI_357_SBayesR) |
PSS012907| East Asian Ancestry| 19,044 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Inflammatory and toxic neuropathy | — | AUROC: 0.60676 | R²: 0.01426 | sex, age, array, PCs 1-10 | — |
| PPM037198 | PGS019016 (TPMI_362.2_Lassosum2) |
PSS012924| East Asian Ancestry| 17,925 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Degeneration of macula and posterior pole of retina | — | AUROC: 0.58428 | R²: 0.00842 | sex, age, array, PCs 1-10 | — |
| PPM037216 | PGS019034 (TPMI_362.29_PRS-CS) |
PSS012921| East Asian Ancestry| 17,901 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Macular degeneration senile of retina NOS | — | AUROC: 0.5911 | R²: 0.00806 | sex, age, array, PCs 1-10 | — |
| PPM037300 | PGS019118 (TPMI_389.1_MegaPRS) |
PSS013015| East Asian Ancestry| 18,218 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Sensorineural hearing loss | — | AUROC: 0.60145 | R²: 0.00461 | sex, age, array, PCs 1-10 | — |
| PPM037400 | PGS019218 (TPMI_430_PRS-CS) |
PSS013125| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66105 | R²: 0.01285 | sex, age, array, PCs 1-10 | — |
| PPM037410 | PGS019228 (TPMI_433_PRS-CS) |
PSS013155| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58466 | R²: 0.02084 | sex, age, array, PCs 1-10 | — |
| PPM037429 | PGS019247 (TPMI_433.8_MegaPRS) |
PSS013149| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63781 | R²: 0.012 | sex, age, array, PCs 1-10 | — |
| PPM037436 | PGS019254 (TPMI_433.21_SBayesR) |
PSS013131| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66335 | R²: 0.03789 | sex, age, array, PCs 1-10 | — |
|
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
|---|---|---|---|---|---|---|---|---|
| PSS009161 | — | — | 3,907 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009189 | — | — | 1,095 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009193 | — | — | 4,116 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011451 | — | — | [
|
— | Not reported | — | FinnGen | — |
| PSS011452 | — | — | [
|
— | European | — | MyCode | — |
| PSS011452 | — | — | [
|
— | Not reported | — | MyCode | — |
| PSS011453 | — | — | [
|
— | European | — | UKB | — |
| PSS011453 | — | — | [
|
— | Not reported | — | UKB | — |
| PSS011454 | — | — | 462 individuals | — | European | — | UKB | — |
| PSS011454 | — | — | 83 individuals | — | Not reported | — | UKB | — |
| PSS012983 | 386.0,H81.0, H81.31, H81.39 | — | [ ,
47.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012985 | 386.0,H81.0, H81.31, H81.39 | — | [ ,
47.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012986 | 386.0,H81.0, H81.31, H81.39 | — | [ ,
47.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000033 | Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria. | — | [
|
— | European | — | 8 cohorts
|
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered |
| PSS000034 | Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria. | — | 4,353 individuals | — | European | — | 8 cohorts
|
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered |
| PSS000035 | Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria. | — | 15,334 individuals | — | European | — | 8 cohorts
|
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered |
| PSS000036 | Cases are patients with clinically diagnosed AD and compared to cognitively normal older individuals | — | [ ,
40.51 % Male samples |
— | European | — | ADGC | ADGC Phase 2 |
| PSS009278 | — | — | 19,895 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012224 | — | Median = 12.5 years | 345,439 individuals, 47.6 % Male samples |
Mean = 56.4 years Sd = 8.0 years |
European | — | UKB | — |
| PSS009289 | — | — | 19,330 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012229 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS009297 | — | — | 19,618 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009298 | — | — | 19,563 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009299 | — | — | 17,764 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012230 | — | — | 1,359 individuals, 47.24 % Male samples |
Mean = 11.23 years Sd = 2.39 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) (Syrian) |
— | BIOPATH | — |
| PSS009301 | — | — | 19,299 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009302 | — | — | 19,840 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009303 | — | — | 19,445 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009304 | — | — | 19,413 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS009315 | — | — | 19,915 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009316 | — | — | 19,445 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011474 | — | — | 8,837 individuals | — | South Asian | — | G&H | — |
| PSS000057 | Incident stroke in was defined based on the UK Biobank (UKB) algorithm, based on medical history and linkage to data on hospital admissions and mortality. The authors also subtyped ischaemic stroke, intracerebral haemorrhage, or subarachnoid haemorrhage. UKB Participants with genetic data were excluded from the analysis based on the following criteria: failing genetic quality control (missingness > 5%, sex mismatch, excessive heterozygosity), having a history of stroke or myocardial infarction (MI), self-report of stroke or MI, missing lifestyle information. | Median = 7.1 years | [ ,
44.59 % Male samples |
Mean = 56.7 years Sd = 7.9 years |
European | Unrelated White British subset of UKB participants | UKB | — |
| PSS011506 | — | — | 7,889 individuals | — | European | — | AllofUs | — |
| PSS000058 | Prevalent and incident Ischaemic stroke; defined in http://biobank.ndph.ox.ac.uk/showcase/docs/alg_outcome_stroke.pdf | Mean = 6.3 years Sd = 1.9 years |
[ ,
45.7 % Male samples |
Mean = 54.3 years | European | — | UKB | Validation set |
| PSS011522 | — | — | [
|
— | South Asian (Pakistani, Bangladeshi) |
— | G&H | — |
| PSS011523 | — | — | [
|
— | East Asian (Japanese) |
— | NCGG | — |
| PSS011524 | — | — | [
|
— | East Asian (Korean) |
— | BICWALZS | — |
| PSS011525 | — | — | [
|
— | East Asian (Korean) |
— | BICWALZS | — |
| PSS011526 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS009387 | — | — | 19,161 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000556 | PheCode:190; ICD9CM:190.0, 190.1, 190.2, 190.3, 190.4, 190.5, 190.6, 190.7, 190.8, 190.9, 234.0, V10.84; ICD10CM:C69, C69.0, C69.00, C69.01, C69.02, C69.1, C69.10, C69.11, C69.12, C69.2, C69.20, C69.21, C69.22, C69.3, C69.30, C69.31, C69.32, C69.4, C69.40, C69.41, C69.42, C69.5, C69.50, C69.51, C69.52, C69.6, C69.60, C69.61, C69.62, C69.8, C69.80, C69.81, C69.82, C69.9, C69.90, C69.91, C69.92, D09.2, D09.20, D09.21, D09.22 | — | [
|
— | European | — | MGI | — |
| PSS000557 | PheCode:191.11; ICD9CM:191.0, 191.1, 191.2, 191.3, 191.4, 191.5, 191.6, 191.7, 191.8, 191.9, V10.85; ICD10CM:C71, C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9 | — | [
|
— | European | — | MGI | — |
| PSS009415 | — | — | 3,905 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012270 | — | — | 425,676 individuals | — | European | — | UKB | — |
| PSS009419 | — | — | 19,978 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012270 | — | — | 8,639 individuals | — | South Asian | — | UKB | — |
| PSS012270 | — | — | 7,345 individuals | — | African American or Afro-Caribbean | — | UKB | — |
| PSS012270 | — | — | 1,462 individuals | — | East Asian (Chinese) |
— | UKB | — |
| PSS012270 | — | — | 9,980 individuals | — | Not reported | — | UKB | — |
| PSS000084 | EFIGA recruited patients from families multiply affected by LOAD, but of Caribbean Hispanic ancestry from the Dominican Republic and New York. Families were recruited after confirming diagnoses in the probands. Family members with dementia were also interviewed and neurologically evaluated. Clinical diagnoses were made in a consensus diagnostic conference by a panel of neurologists, neuropsychologists, and psychiatrists. Detailed description is available elsewhere.14 For these family-based studies, we included data from families for which their members (1) were 60 years or older at the time of enrollment; (2) had a diagnosis of probable or possible LOAD according to National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association (NINDS-ADRDA) criteria; (3) had available pedigree information and covariates. | — | [ ,
34.0 % Male samples |
— | Hispanic or Latin American | Samples are described as "Carribbean Hispanic" | EFIGA | — |
| PSS000085 | Selection criteria included (1) a proband who received a dianosis of definite or probable late onset Alzheimer's Disease (LOAD) with age at onset of at least 60 years; (2) a full sibling with definite, probable, or possible LOAD with age at onset after 60 years; (3) a related family member (first-,second-,or third-degree relative) of theaffected sibling pair and 60 years or older if unaffected, or 50 years or older if dianosed with LOAD or mild cognitive impairment (MCI) | — | [ ,
38.0 % Male samples |
— | European | — | NIA-LOAD | — |
| PSS000577 | PheCode:191.11; ICD9:191, 191.0, 191.1, 191.2, 191.3, 191.4, 191.5, 191.6, 191.7, 191.8, 191.9; ICD10:C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9 | — | [
|
— | European | — | UKB | — |
| PSS000088 | Parkinson Disease symptom progression was assessed during 1 to 3 follow-up examinations by a movement disorder team (June 1, 2007, to August 31, 2013; mean [SD] time from disease onset, 7.3 [2.8] years) using the following methods: - Cognitive decline was determined with the Mini-Mental State Examination (MMSE; range, 0-30, with lower scores indicating worse cognitive function). Cognitive decline was defined as a 4-point decrease from baseline MMSE score and time to event as the time from the baseline to follow-up examinations in which a 4-point decrease was first measured - Motor decline was defined as a 20-point increase in Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) score, and time to event as the time from the baseline to follow-up examinations in which a 20-point increase was first measured. - Motor decline was also measured by assessing conversion to stage 3 or higher of the Hoehn & Yahr (H&Y) scale. Time to conversion to H&Y stage 3 was defined as the time from the baseline to first follow-up examinations in which the patient scored at least stage 3. | Mean = 5.3 years Sd = 2.1 years |
[ ,
56.14 % Male samples |
Mean = 69.1 years Sd = 10.4 years |
European | — | PEG | Patients with idiopathic PD diagnosed less than 3 years previously were recruited from June 1, 2001, through November 31, 2007. Patients were confirmed as having clinically probable or possible Parkinson Disease by a team of movement disorder specialists |
| PSS000578 | PheCode:191.1; ICD9:192, 192.0, 192.1, 192.2, 192.3, 192.8, 192.9; ICD10:C70.0, C70.1, C70.9, C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9, C72.0, C72.1, C72.2, C72.3, C72.4, C72.5, C72.8, C72.9 | — | [
|
— | European | — | UKB | — |
| PSS012275 | — | — | 186,624 individuals, 46.3 % Male samples |
Mean = 64.2 years Sd = 2.9 years |
European | — | UKB | — |
| PSS012275 | — | — | 5,716 individuals, 46.3 % Male samples |
Mean = 64.2 years Sd = 2.9 years |
Not reported | — | UKB | — |
| PSS012899 | 351,G51 | — | [ ,
46.77 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012285 | — | — | [ ,
44.1 % Male samples |
Mean = 59.9 years Sd = 5.4 years |
European | — | UKB | — |
| PSS011574 | — | — | [
|
— | European | — | EB | — |
| PSS011575 | — | — | [
|
— | European | — | FinnGen | — |
| PSS011576 | — | — | [
|
— | European | — | G&H | — |
| PSS011577 | — | — | [
|
— | European | — | GS:SFHS | — |
| PSS011578 | — | — | [
|
— | European | — | GEL | — |
| PSS011579 | — | — | [
|
— | European | — | HUNT | — |
| PSS000601 | All patients with atrial fibrillation and CHADS2 score of 2 or higher who were treated with anticoagulation. The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment. | Median = 2.8 years | [ ,
60.78 % Male samples |
Mean = 70.8 years Sd = 9.1 years |
European | — | ENGAGE_AF-TIMI_48 | — |
| PSS000602 | The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment. | Median = 2.5 years | [ ,
71.7 % Male samples |
Mean = 65.9 years Sd = 9.2 years |
European | — | ENGAGE_AF-TIMI_48, FOURIER, PEGASUS-TIMI_54, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS011580 | — | — | [
|
— | European | — | MGBB | — |
| PSS001209 | — | — | [
|
— | European | — | AGDS | — |
| PSS011608 | — | — | [
|
— | European | — | EB | — |
| PSS011609 | — | — | [
|
— | European | — | FinnGen | — |
| PSS011610 | — | — | [
|
— | European | — | G&H | — |
| PSS011611 | — | — | [
|
— | European | — | GS:SFHS | — |
| PSS011612 | — | — | [
|
— | European | — | GEL | — |
| PSS001213 | — | — | [
|
— | European | — | AGDS | — |
| PSS011614 | — | — | [
|
— | European | — | MGBB | — |
| PSS011613 | — | — | [
|
— | European | — | HUNT | — |
| PSS001214 | — | — | [
|
— | European | — | AGDS | — |
| PSS003601 | Cases were individuals with Parkinson's disease (PD). PD cases were identified from three different sources: (1) participants were asked in a follow-up interview if they had ever been informed by a physician to have PD and, if yes, the age at which the diagnosis was ascertained, (2) all diagnoses containing the International Classification of Diseases, Ninth Revision code 332 (PD) from 1990 to 2018 in public and private hospitals were identified via a computer-assisted record linkage analysis of the cohort database with the nationwide hospital discharge database, (3) record linkage of the cohort database with three public hospital–based PD registries in Singapore through July 31, 2018, was carried out via database linkage. All identified cases were reviewed to confirm that the diagnosis was primary PD according to the criteria defined by the Advisory Council of the USA National Institute of Neurological Disorders and Stroke. | — | [ ,
45.32 % Male samples |
— | Asian unspecified | — | SCHS | — |
| PSS011665 | — | — | [
|
— | European | — | UKB | — |
| PSS007662 | Cases were individuals with Parkinson's disease (PD). All cases were recruited in the study after a clinical diagnosis of PD. | — | [ ,
51.36 % Male samples |
— | European | — | NR | — |
| PSS007663 | Cases were individuals with dementia. Of the 82 cases with dementia, 41 had all-type dementia, 25 had Alzheimer's disease (AD) dementia and 16 had other types of dementia. | — | [
|
— | European | — | AmDem, SCIENCe | — |
| PSS009559 | AD: F00, F00.0, F00.1, F00.2, F00.9, G30, G30.0, G30.1, G30.8, G30.9 VaD: F01, F01.0, F01.1, F01.2, F01.3, F01.8, F01.9, I67.3 FTD: F02.0, G31.0, Other codes for all-cause dementia: A81.0, F02, F02.1, F02.2, F02.3, F02.4, F02.8, F03, F05.1, F10.6, G31.1, G31.8 | Median = 8.0 years | [ ,
47.3 % Male samples |
Mean = 64.1 years | European | — | UKB | — |
| PSS013149 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012357 | 141, V10.01,C01, C02, Z85.810 | — | [ ,
45.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012358 | 141, V10.01,C01, C02, Z85.810 | — | [ ,
45.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012359 | 141, V10.01,C01, C02, Z85.810 | — | [ ,
45.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012360 | 141, V10.01,C01, C02, Z85.810 | — | [ ,
45.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012361 | 141, V10.01,C01, C02, Z85.810 | — | [ ,
45.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009572 | — | — | [ ,
54.0 % Male samples |
— | European | — | DeNoPa, EPIPARK, KIEL, Other | — |
| PSS011676 | — | — | 1,135 individuals, 30.0 % Male samples |
Mean = 59.0 years Sd = 6.0 years |
European | — | WRAP | — |
| PSS011681 | The primary outcome was a first-onset cardiovascular disease event, defined as the composite of CHD (i.e., myocardial infarction or fatal CHD) or any stroke. Secondary outcomes included each of CHD and stroke separately, and a combination of CHD, stroke, and cardiac revascularisation procedures (i.e., percutaneous transluminal cor- onary angioplasty [PTCA] and coronary artery bypass grafting [CABG]). 3333 Cases are CHD events and 2347 are stroke events | Median = 8.1 years | [ ,
43.01 % Male samples |
Mean = 56.0 years Sd = 8.0 years |
European | — | UKB | — |
| PSS012907 | 357,A52.15, G13.0, G13.1, G61, G62.2, G62.8, G62.9, G63, G64, G65, M05.50, M05.51, M05.52, M05.53, M05.54, M05.55, M05.56, M05.57, M05.59, M34.83 | — | [ ,
46.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011358 | ICD-10 codes (I21, I22, I23, I24.1, and I25.2), ICD-9 codes (410, 411, 412, and 429.79) for MI, ICD-10 (I63, I64), ICD-9 (434 and 436) for IS | — | 454,493 individuals | — | European | — | UKB | Mean age of full combined ancestry cohort = 56.9 years |
| PSS011698 | — | — | 1,567 individuals | — | European | — | EAST-AFNET4 | — |
| PSS011699 | — | — | 407,311 individuals | — | European | — | UKB | — |
| PSS009585 | Incident stroke as a confirmed diagnosis of first-ever fatal or nonfatal stroke event during follow-up (I60-I69) | — | 41,006 individuals, 43.1 % Male samples |
Mean = 51.9 years | East Asian | — | NR | — |
| PSS009587 | — | — | [
|
— | African American or Afro-Caribbean (African American) |
— | COG | — |
| PSS011359 | Alzheimer's (ICD10: F00, F00.0, F00.1, F00.2, F00.9, G30, G30.0, G30.1, G30.8, G30.9), Vascular dementia (ICD10: F01, F01.0, F01.1, F01.2, F01.3, F01.8, F01.9, I67.3), Frontotemporal dementia (ICD10: F02.0, G31.0), all-cause dementia (ICD10: A81.0, F02, F02.1, F02.2, F02.3, F02.4, F02.8, F03, F05.1, F10.6, G31.1, G31.8) | Mean = 9.1 years Sd = 1.7 years |
60,298 individuals, 51.5 % Male samples |
Mean = 63.8 years Sd = 2.7 years |
European | — | UKB | — |
| PSS010050 | Participants without history of stroke, coronary heart disease, peripheral vascular disease, or congestive heart failure at recruitment | — | 454,756 individuals | — | Not reported | — | UKB | — |
| PSS007696 | — | — | [
|
— | European | — | CanPath | — |
| PSS010051 | Adults aged 37-73 free of dementia at baseline. International Classification of Diseases (ICD-10) codes was used to define all-cause dementia (ICD-10 codes: F00, F01, F02, F03, F05.1, G30, G31.1, G31.8), Alzheimer’s dementia (AD) (ICD-10 codes: F00, G30), and vascular dementia (VaD) (ICD-10 codes: F01). | — | [ ,
46.9 % Male samples |
Mean = 64.1 years | European | — | UKB | 5,750 (2.8%) all-cause dementia, 2,432 (1.2%) AD, and 936 (0.5%) VaD |
| PSS012477 | 191, 192, 237.5, 237.6, 239.6, V10.85, V10.86,C70, C71, C72, D42, D43.0, D43.1, D43.2, D43.4, D49.6, Z85.841, Z85.848 | — | [ ,
46.09 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012478 | 191, 192, 237.5, 237.6, 239.6, V10.85, V10.86,C70, C71, C72, D42, D43.0, D43.1, D43.2, D43.4, D49.6, Z85.841, Z85.848 | — | [ ,
46.09 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012479 | 191, 192, 237.5, 237.6, 239.6, V10.85, V10.86,C70, C71, C72, D42, D43.0, D43.1, D43.2, D43.4, D49.6, Z85.841, Z85.848 | — | [ ,
46.09 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007705 | — | — | [
|
— | Asian unspecified | Central and South Asian | UKB | — |
| PSS012480 | 191, 192, 237.5, 237.6, 239.6, V10.85, V10.86,C70, C71, C72, D42, D43.0, D43.1, D43.2, D43.4, D49.6, Z85.841, Z85.848 | — | [ ,
46.09 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012481 | 191, 192, 237.5, 237.6, 239.6, V10.85, V10.86,C70, C71, C72, D42, D43.0, D43.1, D43.2, D43.4, D49.6, Z85.841, Z85.848 | — | [ ,
46.09 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007716 | — | — | [
|
— | European | — | UKB | — |
| PSS011719 | Samples used in this study were extracted from autopsied brain tissue. Samples were taken from cognitively normal individuals witth a dementia rating of 0 (controls) and from late-onset Alzheimer's disease (LOAD) patients who had a clinical diagnosis of dementia due to AD and neuropathological confirmation of AD. | — | [ ,
39.0 % Male samples |
— | European | — | BfDR | — |
| PSS009618 | AMD phenotype was defined using a combination of main and secondary ICD-10 (Field IDs 41202, 41204: Code H35.3) and ICD-9 (Field IDs 41203, 41205: Code 3625) diagnoses for macular degeneration, self-reported macular degeneration (Field ID 20002: Code 1528), and macular degeneration from the available general practice data. Prevalent AMD cases were defined as individuals who had AMD first diagnosed at or before enrollment. Incident AMD cases were defined as individuals who had AMD first diagnosed after enrollment | — | 44,253 individuals | — | European | — | UKB | — |
| PSS009618 | AMD phenotype was defined using a combination of main and secondary ICD-10 (Field IDs 41202, 41204: Code H35.3) and ICD-9 (Field IDs 41203, 41205: Code 3625) diagnoses for macular degeneration, self-reported macular degeneration (Field ID 20002: Code 1528), and macular degeneration from the available general practice data. Prevalent AMD cases were defined as individuals who had AMD first diagnosed at or before enrollment. Incident AMD cases were defined as individuals who had AMD first diagnosed after enrollment | — | 40 individuals | — | South Asian | — | UKB | — |
| PSS007729 | — | — | 2,477 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009618 | AMD phenotype was defined using a combination of main and secondary ICD-10 (Field IDs 41202, 41204: Code H35.3) and ICD-9 (Field IDs 41203, 41205: Code 3625) diagnoses for macular degeneration, self-reported macular degeneration (Field ID 20002: Code 1528), and macular degeneration from the available general practice data. Prevalent AMD cases were defined as individuals who had AMD first diagnosed at or before enrollment. Incident AMD cases were defined as individuals who had AMD first diagnosed after enrollment | — | 530 individuals | — | Not reported | — | UKB | — |
| PSS003755 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003756 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003757 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003758 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003759 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS010155 | — | — | 117 individuals, 50.0 % Male samples |
Mean = 9.96 years | Not reported | — | NR | ABCD |
| PSS007739 | — | — | 2,385 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS012533 | 225, V12.41,D32.0, D32.1, D32.9, D33.0, D33.1, D33.2, D33.3, D33.4, D33.7, D33.9, Z86.011 | — | [ ,
46.15 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012532 | 225, V12.41,D32.0, D32.1, D32.9, D33.0, D33.1, D33.2, D33.3, D33.4, D33.7, D33.9, Z86.011 | — | [ ,
46.15 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012535 | 225, V12.41,D32.0, D32.1, D32.9, D33.0, D33.1, D33.2, D33.3, D33.4, D33.7, D33.9, Z86.011 | — | [ ,
46.15 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012534 | 225, V12.41,D32.0, D32.1, D32.9, D33.0, D33.1, D33.2, D33.3, D33.4, D33.7, D33.9, Z86.011 | — | [ ,
46.15 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012536 | 225, V12.41,D32.0, D32.1, D32.9, D33.0, D33.1, D33.2, D33.3, D33.4, D33.7, D33.9, Z86.011 | — | [ ,
46.15 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007745 | — | — | 2,441 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007746 | — | — | 2,429 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007747 | — | — | 2,272 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007749 | — | — | 2,390 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007750 | — | — | 2,471 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007751 | — | — | 2,384 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007752 | — | — | 2,374 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011263 | — | — | [
|
— | European | — | HUNT | — |
| PSS007762 | — | — | 2,470 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007763 | — | — | 2,407 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS010156 | — | — | 4,382 individuals, 50.0 % Male samples |
Mean = 9.94 years | Not reported | — | NR | ABCD |
| PSS009634 | — | — | 4,114 individuals | — | European | — | ADC | DCN, FACE, HAN, UAN, UHA, AMC, ZIM |
| PSS009635 | — | — | 17,545 individuals | — | European | — | 3C, FHS, MAS, RS | AgeCoDe, VITA |
| PSS009641 | A stroke event was defined as hospitalization due to stroke which was self-reported in a structured and standardized inter- view performed by certified and supervised personnel. | — | 3,071 individuals, 49.0 % Male samples |
Mean = 57.4 years Sd = 12.9 years |
European | — | KORA | — |
| PSS011750 | — | — | [ ,
0.0 % Male samples |
— | European, African unspecified, Not reported | — | SISTER | — |
| PSS009642 | G30.1 Alzheimer’s disease with late onset | — | 497,087 individuals, 45.9 % Male samples |
Mean = 57.1 years Sd = 7.9 years |
European | — | UKB | — |
| PSS011751 | — | — | [ ,
0.0 % Male samples |
— | European, African unspecified, Not reported | — | SISTER | — |
| PSS000225 | — | — | [ ,
55.22 % Male samples |
— | European | — | PPMI | Both the PPMI and WUSTL datasets are available by request from the PPMI website (www.ppmi-info.org) |
| PSS000226 | — | — | [ ,
58.27 % Male samples |
— | European | — | WUSTL | Both the PPMI and WUSTL datasets are available by request from the PPMI website (www.ppmi-info.org) |
| PSS011276 | — | — | [
|
— | European | — | UKB | — |
| PSS007831 | — | — | 2,325 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000237 | Schizophrenia case subjects had two or more ICD codes included in phecode 295.1 | — | [ ,
46.0 % Male samples |
Mean = 57.9 years Sd = 20.0 years |
European | — | BioVU | Vanderbilt University Medical Center (VUMC) biobank (BioVU) |
| PSS000238 | Psychosis case subjects were identified with phecode 295 | — | [ ,
46.0 % Male samples |
Mean = 57.9 years Sd = 20.0 years |
European | — | BioVU | Vanderbilt University Medical Center (VUMC) biobank (BioVU) |
| PSS000239 | Schizophrenia case subjects had two or more ICD codes included in phecode 295.1 | — | [ ,
41.0 % Male samples |
Mean = 60.2 years Sd = 16.9 years |
European | — | MyCode | Geisinger Health System (GHS) |
| PSS000240 | Psychosis case subjects were identified with phecode 295 | — | [ ,
41.0 % Male samples |
Mean = 60.2 years Sd = 16.9 years |
European | — | MyCode | Geisinger Health System (GHS) |
| PSS000241 | Schizophrenia case subjects had two or more ICD codes included in phecode 295.1 | — | [ ,
48.0 % Male samples |
Mean = 57.2 years Sd = 19.8 years |
European | — | BioMe | BioMe Biobank at the Mount Sinai School of Medicine (MSSM) |
| PSS009663 | glioma (ICD-9 = 191 or ICD-10 = C71; ICD-O: 9380-9480) | — | 312 individuals | — | European | — | UKB | — |
| PSS000243 | Schizophrenia case subjects had two or more ICD codes included in phecode 295.1 | — | [ ,
46.0 % Male samples |
Mean = 58.5 years Sd = 16.4 years |
European | — | PHB | Partners HealthCare System (PHS) biobank |
| PSS000244 | Psychosis case subjects were identified with phecode 295 | — | [ ,
46.0 % Male samples |
Mean = 58.5 years Sd = 16.4 years |
European | — | PHB | Partners HealthCare System (PHS) biobank |
| PSS007859 | — | — | 570 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007863 | — | — | 2,460 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000250 | — | — | [
|
— | European | — | 15 cohorts
|
Part of PGC29 (PMID: 29700475) |
| PSS012665 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012666 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012667 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS003899 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003900 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003901 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003902 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003903 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012669 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012670 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012668 | 357.2,E08.42, E09.42, E10.42 | — | [ ,
42.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012672 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011773 | ICD10: I61 | Median = 12.2 years | 72,149 individuals, 40.2 % Male samples |
Mean = 51.7 years Sd = 10.5 years |
East Asian (Chinese) |
— | CKB | — |
| PSS012671 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012918 | 362.50,H35.3 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012673 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012674 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012675 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012676 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011290 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS010943 | — | — | [
|
— | Not reported | — | NR | Luxembourg Parkinson's Study |
| PSS010944 | ICD10 codes, including F00, F01, F02, F03 and G30 subcategories. | — | [ ,
46.2 % Male samples |
Mean = 56.8 years | European (white British) |
— | UKB | — |
| PSS010944 | ICD10 codes, including F00, F01, F02, F03 and G30 subcategories. | — | [ ,
54.2 % Male samples |
Mean = 53.4 years | South Asian | — | UKB | — |
| PSS010944 | ICD10 codes, including F00, F01, F02, F03 and G30 subcategories. | — | [ ,
43.6 % Male samples |
Mean = 51.9 years | African unspecified (Black) |
— | UKB | — |
| PSS011783 | — | — | [
|
— | European | — | AugUR | — |
| PSS011784 | — | — | [
|
— | European | — | AugUR | — |
| PSS011785 | — | — | [
|
— | European | — | AugUR | — |
| PSS011786 | — | — | [
|
— | European | — | AugUR | — |
| PSS011787 | — | — | [
|
— | European | — | AugUR | — |
| PSS011788 | — | — | [
|
— | European | — | AugUR | — |
| PSS011789 | — | — | [ ,
0.0 % Male samples |
— | European | — | GEOS | — |
| PSS010946 | — | — | [
|
Range = [18.0, 86.0] years | African unspecified (Black) |
— | UCLA | — |
| PSS010947 | — | — | [
|
Range = [18.0, 86.0] years | Asian unspecified (Asian) |
— | UCLA | — |
| PSS010948 | — | — | [
|
Range = [18.0, 86.0] years | European | — | UCLA | — |
| PSS010949 | — | — | [
|
Range = [18.0, 86.0] years | Hispanic or Latin American (Latino) |
— | UCLA | — |
| PSS010950 | — | — | [
|
Range = [30.0, 60.0] years | East Asian (Han Chinese) |
— | CONVERGE | — |
| PSS010951 | — | — | [
|
Range = [37.0, 74.0] years | African unspecified (African) |
— | UKB | — |
| PSS010952 | — | — | [
|
Range = [37.0, 74.0] years | Asian unspecified (Asian) |
— | UKB | — |
| PSS010953 | — | — | [
|
Range = [37.0, 74.0] years | European | — | UKB | — |
| PSS010954 | — | — | [
|
Range = [8.0, 32.0] years | European (Danish) |
— | iPSYCH | — |
| PSS010955 | — | — | [
|
Range = [8.0, 35.0] years | European (Danish) |
— | iPSYCH | — |
| PSS012920 | 362.50,H35.3 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013133 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013134 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013135 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013136 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007947 | — | — | 1,801 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS003974 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003975 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003976 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003977 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003978 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS007958 | — | — | 1,764 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS012921 | 362.50,H35.3 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007964 | — | — | 1,802 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007965 | — | — | 1,802 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007966 | — | — | 1,742 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007968 | — | — | 1,801 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007969 | — | — | 1,773 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007970 | — | — | 1,775 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS008832 | — | — | 3,913 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS013142 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007979 | — | — | 1,804 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007980 | — | — | 1,789 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS013143 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012922 | 362.50,H35.3 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013144 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013145 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012793 | 331.0,G30 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012794 | 331.0,G30 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012795 | 331.0,G30 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012796 | 331.0,G30 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012797 | 331.0,G30 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012798 | 290.0, 290.2, 290.3,F03 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012799 | 290.0, 290.2, 290.3,F03 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012800 | 290.0, 290.2, 290.3,F03 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013147 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012802 | 290.0, 290.2, 290.3,F03 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012803 | 290.0, 290.1, 290.2, 290.3, 290.4, 294.1, 294.2, 331.0, 331.1, 331.2, 331.82,F01, F02, F03, G30, G31.0, G31.1, G31.83 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012804 | 290.0, 290.1, 290.2, 290.3, 290.4, 294.1, 294.2, 331.0, 331.1, 331.2, 331.82,F01, F02, F03, G30, G31.0, G31.1, G31.83 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012805 | 290.0, 290.1, 290.2, 290.3, 290.4, 294.1, 294.2, 331.0, 331.1, 331.2, 331.82,F01, F02, F03, G30, G31.0, G31.1, G31.83 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012806 | 290.0, 290.1, 290.2, 290.3, 290.4, 294.1, 294.2, 331.0, 331.1, 331.2, 331.82,F01, F02, F03, G30, G31.0, G31.1, G31.83 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012807 | 290.0, 290.1, 290.2, 290.3, 290.4, 294.1, 294.2, 331.0, 331.1, 331.2, 331.82,F01, F02, F03, G30, G31.0, G31.1, G31.83 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012808 | 294.8, 294.9, 310.1,F06.1, F06.8 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012809 | 294.8, 294.9, 310.1,F06.1, F06.8 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000952 | Cases are individuals with sporadic Parkinson's disease. | — | [
|
— | European, NR | European, Not reported | PPMI | — |
| PSS012810 | 294.8, 294.9, 310.1,F06.1, F06.8 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS010987 | — | — | 890 individuals | Mean = 50.88 years | European | — | TCGA | — |
| PSS012813 | 290, 291.0, 292.81, 293.0, 293.1, 294, 310.1, 331.0, 331.1, 331.2, 331.82, 797,F01, F02, F03, F04, F05, F06.1, F06.8, F10.121, F10.221, F10.231, F10.921, F11.121, F11.221, F11.921, F12.121, F12.221, F12.921, F13.121, F13.221, F13.921, F14.121, F14.221, F14.921, F15.121, F15.221, F15.921, F16.121, F16.221, F16.921, F18.121, F18.221, F18.921, F19.121, F19.221, F19.921, G30, G31.0, G31.1, G31.83, R41.81, R54 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012814 | 290, 291.0, 292.81, 293.0, 293.1, 294, 310.1, 331.0, 331.1, 331.2, 331.82, 797,F01, F02, F03, F04, F05, F06.1, F06.8, F10.121, F10.221, F10.231, F10.921, F11.121, F11.221, F11.921, F12.121, F12.221, F12.921, F13.121, F13.221, F13.921, F14.121, F14.221, F14.921, F15.121, F15.221, F15.921, F16.121, F16.221, F16.921, F18.121, F18.221, F18.921, F19.121, F19.221, F19.921, G30, G31.0, G31.1, G31.83, R41.81, R54 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012815 | 290, 291.0, 292.81, 293.0, 293.1, 294, 310.1, 331.0, 331.1, 331.2, 331.82, 797,F01, F02, F03, F04, F05, F06.1, F06.8, F10.121, F10.221, F10.231, F10.921, F11.121, F11.221, F11.921, F12.121, F12.221, F12.921, F13.121, F13.221, F13.921, F14.121, F14.221, F14.921, F15.121, F15.221, F15.921, F16.121, F16.221, F16.921, F18.121, F18.221, F18.921, F19.121, F19.221, F19.921, G30, G31.0, G31.1, G31.83, R41.81, R54 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012816 | 290, 291.0, 292.81, 293.0, 293.1, 294, 310.1, 331.0, 331.1, 331.2, 331.82, 797,F01, F02, F03, F04, F05, F06.1, F06.8, F10.121, F10.221, F10.231, F10.921, F11.121, F11.221, F11.921, F12.121, F12.221, F12.921, F13.121, F13.221, F13.921, F14.121, F14.221, F14.921, F15.121, F15.221, F15.921, F16.121, F16.221, F16.921, F18.121, F18.221, F18.921, F19.121, F19.221, F19.921, G30, G31.0, G31.1, G31.83, R41.81, R54 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012817 | 290, 291.0, 292.81, 293.0, 293.1, 294, 310.1, 331.0, 331.1, 331.2, 331.82, 797,F01, F02, F03, F04, F05, F06.1, F06.8, F10.121, F10.221, F10.231, F10.921, F11.121, F11.221, F11.921, F12.121, F12.221, F12.921, F13.121, F13.221, F13.921, F14.121, F14.221, F14.921, F15.121, F15.221, F15.921, F16.121, F16.221, F16.921, F18.121, F18.221, F18.921, F19.121, F19.221, F19.921, G30, G31.0, G31.1, G31.83, R41.81, R54 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008842 | — | — | 3,732 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS012811 | 294.8, 294.9, 310.1,F06.1, F06.8 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012812 | 294.8, 294.9, 310.1,F06.1, F06.8 | — | [ ,
45.99 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012819 | 310,F07, F09, F48.2 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012818 | 310,F07, F09, F48.2 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012823 | 293, 310, 780.0,F07, F09, F48.2, F53, R40.0, R40.1 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012824 | 293, 310, 780.0,F07, F09, F48.2, F53, R40.0, R40.1 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012825 | 293, 310, 780.0,F07, F09, F48.2, F53, R40.0, R40.1 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012820 | 310,F07, F09, F48.2 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012827 | 293, 310, 780.0,F07, F09, F48.2, F53, R40.0, R40.1 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012821 | 310,F07, F09, F48.2 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012822 | 310,F07, F09, F48.2 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012826 | 293, 310, 780.0,F07, F09, F48.2, F53, R40.0, R40.1 | — | [ ,
45.95 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012924 | 362.5,H35.3 | — | [ ,
45.8 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012833 | 331.83, 780.02, 780.1, 780.93, 780.97, 781.8, 784.3, 784.5, 784.6, 799.50, 799.51, 799.52, 799.53, 799.54, 799.55, 799.59,G31.84, R40.4, R41.0, R41.1, R41.2, R41.3, R41.4, R41.82, R41.840, R41.841, R41.842, R41.843, R41.844, R41.89, R44.0, R44.2, R44.3, R47.01, R47.02, R47.1, R47.8, R47.9, R48.0, R48.1, R48.2, R48.8, R48.9 | — | [ ,
46.02 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012834 | 331.83, 780.02, 780.1, 780.93, 780.97, 781.8, 784.3, 784.5, 784.6, 799.50, 799.51, 799.52, 799.53, 799.54, 799.55, 799.59,G31.84, R40.4, R41.0, R41.1, R41.2, R41.3, R41.4, R41.82, R41.840, R41.841, R41.842, R41.843, R41.844, R41.89, R44.0, R44.2, R44.3, R47.01, R47.02, R47.1, R47.8, R47.9, R48.0, R48.1, R48.2, R48.8, R48.9 | — | [ ,
46.02 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012835 | 331.83, 780.02, 780.1, 780.93, 780.97, 781.8, 784.3, 784.5, 784.6, 799.50, 799.51, 799.52, 799.53, 799.54, 799.55, 799.59,G31.84, R40.4, R41.0, R41.1, R41.2, R41.3, R41.4, R41.82, R41.840, R41.841, R41.842, R41.843, R41.844, R41.89, R44.0, R44.2, R44.3, R47.01, R47.02, R47.1, R47.8, R47.9, R48.0, R48.1, R48.2, R48.8, R48.9 | — | [ ,
46.02 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012836 | 331.83, 780.02, 780.1, 780.93, 780.97, 781.8, 784.3, 784.5, 784.6, 799.50, 799.51, 799.52, 799.53, 799.54, 799.55, 799.59,G31.84, R40.4, R41.0, R41.1, R41.2, R41.3, R41.4, R41.82, R41.840, R41.841, R41.842, R41.843, R41.844, R41.89, R44.0, R44.2, R44.3, R47.01, R47.02, R47.1, R47.8, R47.9, R48.0, R48.1, R48.2, R48.8, R48.9 | — | [ ,
46.02 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012837 | 331.83, 780.02, 780.1, 780.93, 780.97, 781.8, 784.3, 784.5, 784.6, 799.50, 799.51, 799.52, 799.53, 799.54, 799.55, 799.59,G31.84, R40.4, R41.0, R41.1, R41.2, R41.3, R41.4, R41.82, R41.840, R41.841, R41.842, R41.843, R41.844, R41.89, R44.0, R44.2, R44.3, R47.01, R47.02, R47.1, R47.8, R47.9, R48.0, R48.1, R48.2, R48.8, R48.9 | — | [ ,
46.02 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008045 | — | — | 1,684 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS011004 | — | — | 237 individuals, 51.0 % Male samples |
— | Hispanic or Latin American (Brazilian) |
— | NR | BHRCS |
| PSS012839 | 296.2, 296.3, 311,F32, F33 | — | [ ,
46.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012838 | 296.2, 296.3, 311,F32, F33 | — | [ ,
46.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012841 | 296.2, 296.3, 311,F32, F33 | — | [ ,
46.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012842 | 296.2, 296.3, 311,F32, F33 | — | [ ,
46.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012844 | 300.02,F41.1 | — | [ ,
46.82 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012843 | 300.02,F41.1 | — | [ ,
46.82 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012845 | 300.02,F41.1 | — | [ ,
46.82 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012846 | 300.02,F41.1 | — | [ ,
46.82 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012847 | 300.02,F41.1 | — | [ ,
46.82 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012849 | 307, 316, 333.92, 648.4, V11.2, V11.8, V11.9, V15.4, V40.2, V40.3, V40.9, V62.85, V66.3, V67.3, V70.1, V70.2, V71.0,F54, G21.0, G44.2, O90.6, O99.31, O99.34, R45.850, Z86.59 | — | [ ,
46.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012848 | 307, 316, 333.92, 648.4, V11.2, V11.8, V11.9, V15.4, V40.2, V40.3, V40.9, V62.85, V66.3, V67.3, V70.1, V70.2, V71.0,F54, G21.0, G44.2, O90.6, O99.31, O99.34, R45.850, Z86.59 | — | [ ,
46.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012850 | 307, 316, 333.92, 648.4, V11.2, V11.8, V11.9, V15.4, V40.2, V40.3, V40.9, V62.85, V66.3, V67.3, V70.1, V70.2, V71.0,F54, G21.0, G44.2, O90.6, O99.31, O99.34, R45.850, Z86.59 | — | [ ,
46.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012852 | 307, 316, 333.92, 648.4, V11.2, V11.8, V11.9, V15.4, V40.2, V40.3, V40.9, V62.85, V66.3, V67.3, V70.1, V70.2, V71.0,F54, G21.0, G44.2, O90.6, O99.31, O99.34, R45.850, Z86.59 | — | [ ,
46.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008849 | — | — | 3,852 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS012854 | 307.9, 315, 317, 318, 319, V40,F63.3, F70, F71, F72, F73, F78, F79, F80, F81.0, F81.2, F81.8, F81.9, F82, F88, F89, H93.25, R45.1, R45.81, R45.82 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000966 | The narcolepsy patients had either hypocretin deficiency (CSF hypocretin-1 ≤110 pg/mL) or clear-cut cataplexy and HLA-DQB1*06:02. | — | [ ,
44.94 % Male samples |
— | East Asian (Han Chinese, Chinese) |
— | NR | — |
| PSS012853 | 307.9, 315, 317, 318, 319, V40,F63.3, F70, F71, F72, F73, F78, F79, F80, F81.0, F81.2, F81.8, F81.9, F82, F88, F89, H93.25, R45.1, R45.81, R45.82 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012855 | 307.9, 315, 317, 318, 319, V40,F63.3, F70, F71, F72, F73, F78, F79, F80, F81.0, F81.2, F81.8, F81.9, F82, F88, F89, H93.25, R45.1, R45.81, R45.82 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008850 | — | — | 3,836 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS012856 | 307.9, 315, 317, 318, 319, V40,F63.3, F70, F71, F72, F73, F78, F79, F80, F81.0, F81.2, F81.8, F81.9, F82, F88, F89, H93.25, R45.1, R45.81, R45.82 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012857 | 307.9, 315, 317, 318, 319, V40,F63.3, F70, F71, F72, F73, F78, F79, F80, F81.0, F81.2, F81.8, F81.9, F82, F88, F89, H93.25, R45.1, R45.81, R45.82 | — | [ ,
45.98 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008851 | — | — | 3,678 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008072 | — | — | 390 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS000971 | Hearing aid use cases responded ‘Yes’ to either ‘Do you wear a hearing aid?’ or ‘Wearing a hearing aid’ while controls responded ‘No’. | — | [ ,
8.0 % Male samples |
Mean = 59.32 years Sd = 9.69 years |
European (British) |
— | TwinsUK | — |
| PSS000972 | Hearing difficulty cases were defined as responding either ‘Yes, diagnosed by doctor or health professional’ or ‘Yes, not diagnosed by health professional’ to ‘Do you suffer from hearing loss?’ while participants that responded ‘No’ were assigned as controls. | — | [ ,
8.5 % Male samples |
Mean = 60.34 years Sd = 10.18 years |
European (British) |
— | TwinsUK | — |
| PSS008076 | — | — | 1,788 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS012868 | 307.42, 327.0,F51.01, F51.03, F51.09 | — | [ ,
46.44 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012870 | 307.42, 327.0,F51.01, F51.03, F51.09 | — | [ ,
46.44 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008853 | — | — | 3,790 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS012871 | 307.42, 327.0,F51.01, F51.03, F51.09 | — | [ ,
46.44 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012869 | 307.42, 327.0,F51.01, F51.03, F51.09 | — | [ ,
46.44 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012872 | 307.42, 327.0,F51.01, F51.03, F51.09 | — | [ ,
46.44 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008854 | — | — | 3,898 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011016 | — | — | [
|
— | Other (Ashkenazi Jewish) |
— | NR | — |
| PSS011016 | — | — | [
|
— | European | — | NR | — |
| PSS011017 | — | — | [
|
— | Other (Ashkenazi Jewish) |
— | NR | — |
| PSS000275 | Primary tumor samples from TCGA | — | [
|
Mean = 52.0 years Sd = 16.0 years |
European | — | TCGA | — |
| PSS000275 | — | — | [
|
— | European | — | eMERGE | — |
| PSS008855 | — | — | 3,743 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011017 | — | — | [
|
— | European | — | NR | — |
| PSS012879 | 327.5, 333.94, 780.58,G25.81, G47.6 | — | [ ,
47.11 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012878 | 327.5, 333.94, 780.58,G25.81, G47.6 | — | [ ,
47.11 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008856 | — | — | 3,723 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011021 | — | Mean = 9.0 years | 41,006 individuals, 43.1 % Male samples |
Mean = 51.9 years Sd = 10.6 years |
East Asian (Chinese) |
— | InterASIA | China MUCA 1998, CIMIC |
| PSS012889 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012888 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012890 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012891 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012892 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012894 | 345.0, 345.1, 345.2, 345.3, 345.4, 345.5, 345.6, 345.7, 345.8, 345.91,G40.0, G40.1, G40.2, G40.3, G40.4, G40.5, G40.801, G40.802, G40.803, G40.804, G40.811, G40.812, G40.813, G40.814, G40.82, G40.89, G40.911, G40.919, G40.A, G40.A0, G40.A01, G40.A09, G40.A1, G40.A11, G40.A19, G40.B, G40.B0, G40.B01, G40.B09, G40.B1, G40.B11, G40.B19 | — | [ ,
45.92 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012893 | 345.0, 345.1, 345.2, 345.3, 345.4, 345.5, 345.6, 345.7, 345.8, 345.91,G40.0, G40.1, G40.2, G40.3, G40.4, G40.5, G40.801, G40.802, G40.803, G40.804, G40.811, G40.812, G40.813, G40.814, G40.82, G40.89, G40.911, G40.919, G40.A, G40.A0, G40.A01, G40.A09, G40.A1, G40.A11, G40.A19, G40.B, G40.B0, G40.B01, G40.B09, G40.B1, G40.B11, G40.B19 | — | [ ,
45.92 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012895 | 345.0, 345.1, 345.2, 345.3, 345.4, 345.5, 345.6, 345.7, 345.8, 345.91,G40.0, G40.1, G40.2, G40.3, G40.4, G40.5, G40.801, G40.802, G40.803, G40.804, G40.811, G40.812, G40.813, G40.814, G40.82, G40.89, G40.911, G40.919, G40.A, G40.A0, G40.A01, G40.A09, G40.A1, G40.A11, G40.A19, G40.B, G40.B0, G40.B01, G40.B09, G40.B1, G40.B11, G40.B19 | — | [ ,
45.92 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011026 | — | — | 314,998 individuals, 49.1 % Male samples |
Mean = 56.1 years | European | — | UKB | — |
| PSS000984 | — | — | 62 individuals, 0.0 % Male samples |
— | European, Hispanic or Latin American, African unspecified, Asian unspecified, NR | — | NR | — |
| PSS000985 | — | — | 63 individuals, 0.0 % Male samples |
— | European, Hispanic or Latin American, African unspecified, Asian unspecified, NR | — | NR | — |
| PSS000986 | — | — | 73 individuals, 0.0 % Male samples |
— | European, Hispanic or Latin American, African unspecified, Asian unspecified, NR | — | NR | — |
| PSS012896 | 345.0, 345.1, 345.2, 345.3, 345.4, 345.5, 345.6, 345.7, 345.8, 345.91,G40.0, G40.1, G40.2, G40.3, G40.4, G40.5, G40.801, G40.802, G40.803, G40.804, G40.811, G40.812, G40.813, G40.814, G40.82, G40.89, G40.911, G40.919, G40.A, G40.A0, G40.A01, G40.A09, G40.A1, G40.A11, G40.A19, G40.B, G40.B0, G40.B01, G40.B09, G40.B1, G40.B11, G40.B19 | — | [ ,
45.92 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012897 | 345.0, 345.1, 345.2, 345.3, 345.4, 345.5, 345.6, 345.7, 345.8, 345.91,G40.0, G40.1, G40.2, G40.3, G40.4, G40.5, G40.801, G40.802, G40.803, G40.804, G40.811, G40.812, G40.813, G40.814, G40.82, G40.89, G40.911, G40.919, G40.A, G40.A0, G40.A01, G40.A09, G40.A1, G40.A11, G40.A19, G40.B, G40.B0, G40.B01, G40.B09, G40.B1, G40.B11, G40.B19 | — | [ ,
45.92 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012898 | 351,G51 | — | [ ,
46.77 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012900 | 351,G51 | — | [ ,
46.77 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012901 | 351,G51 | — | [ ,
46.77 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012902 | 351,G51 | — | [ ,
46.77 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012904 | 357,A52.15, G13.0, G13.1, G61, G62.2, G62.8, G62.9, G63, G64, G65, M05.50, M05.51, M05.52, M05.53, M05.54, M05.55, M05.56, M05.57, M05.59, M34.83 | — | [ ,
46.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012903 | 357,A52.15, G13.0, G13.1, G61, G62.2, G62.8, G62.9, G63, G64, G65, M05.50, M05.51, M05.52, M05.53, M05.54, M05.55, M05.56, M05.57, M05.59, M34.83 | — | [ ,
46.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012905 | 357,A52.15, G13.0, G13.1, G61, G62.2, G62.8, G62.9, G63, G64, G65, M05.50, M05.51, M05.52, M05.53, M05.54, M05.55, M05.56, M05.57, M05.59, M34.83 | — | [ ,
46.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012906 | 357,A52.15, G13.0, G13.1, G61, G62.2, G62.8, G62.9, G63, G64, G65, M05.50, M05.51, M05.52, M05.53, M05.54, M05.55, M05.56, M05.57, M05.59, M34.83 | — | [ ,
46.19 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012909 | 361,H33.0, H33.1, H33.2, H33.3, H33.4, H33.8 | — | [ ,
45.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012908 | 361,H33.0, H33.1, H33.2, H33.3, H33.4, H33.8 | — | [ ,
45.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012910 | 361,H33.0, H33.1, H33.2, H33.3, H33.4, H33.8 | — | [ ,
45.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012911 | 361,H33.0, H33.1, H33.2, H33.3, H33.4, H33.8 | — | [ ,
45.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012912 | 361,H33.0, H33.1, H33.2, H33.3, H33.4, H33.8 | — | [ ,
45.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012914 | 362.56,H35.37 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012913 | 362.56,H35.37 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012915 | 362.56,H35.37 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012916 | 362.56,H35.37 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012917 | 362.56,H35.37 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS010078 | C71, histology was either Giant cell glioblastoma or Glioblastoma (NOS) | — | [
|
— | European (British) |
— | UKB | Controls were samples without any cancer diagnosis or self-reported cancer |
| PSS012923 | 362.5,H35.3 | — | [ ,
45.8 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012919 | 362.50,H35.3 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012925 | 362.5,H35.3 | — | [ ,
45.8 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012926 | 362.5,H35.3 | — | [ ,
45.8 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012927 | 362.5,H35.3 | — | [ ,
45.8 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012928 | 362.6,H35.4 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012929 | 362.6,H35.4 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012930 | 362.6,H35.4 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012931 | 362.6,H35.4 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012932 | 362.6,H35.4 | — | [ ,
45.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012933 | 362,G45.3, H31.11, H33.2, H34, H35, H36 | — | [ ,
46.03 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012934 | 362,G45.3, H31.11, H33.2, H34, H35, H36 | — | [ ,
46.03 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012935 | 362,G45.3, H31.11, H33.2, H34, H35, H36 | — | [ ,
46.03 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012936 | 362,G45.3, H31.11, H33.2, H34, H35, H36 | — | [ ,
46.03 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012937 | 362,G45.3, H31.11, H33.2, H34, H35, H36 | — | [ ,
46.03 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008866 | — | — | 3,912 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008867 | — | — | 3,806 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008160 | — | — | 6,310 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008171 | — | — | 6,081 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008179 | — | — | 6,222 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008180 | — | — | 6,205 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008181 | — | — | 5,870 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008183 | — | — | 6,094 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008184 | — | — | 6,277 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS000294 | Participants completed an online follow-up questionnaire assessing common mental health disorders, including MDD symptoms. Phenotypes were derived from this questionnaire. Individuals with probable MDD met lifetime criteria based on their responses to questions derived from the Composite International Diagnostic Interview. We excluded cases if they self-reported diagnoses of schizophrenia, other psychoses, or bipolar disorder. Controls were excluded if they self-reported any mental illness, taking any drug with an antidepressant indication, or had been hospitalised with a mood disorder or met previously-defined criteria for a mood disorder. | — | [ ,
45.0 % Male samples |
Range = [46.0, 80.0] years | European | — | UKB | — |
| PSS008185 | — | — | 6,095 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008186 | — | — | 6,037 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011907 | — | — | [
|
— | European | — | ADNI, Knight-ADRC | — |
| PSS011906 | — | — | [
|
— | European | — | NIA-LOAD | — |
| PSS011908 | — | — | [
|
— | European | — | ADNI, Knight-ADRC | — |
| PSS012984 | 386.0,H81.0, H81.31, H81.39 | — | [ ,
47.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009875 | Ischemic stroke | — | [
|
— | East Asian (Japanese) |
— | BBJ | % Male: 70.0% for cases and 53.1% for controls. Age information: Mean (cases) = 69.2 years, sd (cases) = 10.8; Mean (controls) = 66.5 years, sd (controls) = 12.5 |
| PSS009876 | Ischemic stroke | — | [
|
— | European | — | NR | ClinicalTrials_EUR |
| PSS009877 | Ischemic stroke | Mean = 4.6 years Sd = 4.8 years |
[ ,
37.8 % Male samples |
Mean = 44.0 years Sd = 15.7 years |
European (Estonian) |
— | EB | — |
| PSS009878 | Ischemic stroke | — | [
|
— | African American or Afro-Caribbean (African American) |
— | MVP | — |
| PSS009879 | Ischemic stroke | — | [
|
— | European (European) |
— | MVP | — |
| PSS008197 | — | — | 6,308 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008198 | — | — | 6,173 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009881 | Ischemic stroke | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009882 | — | — | [
|
— | European | — | KP | — |
| PSS009883 | — | — | [
|
— | European | — | UKB | — |
| PSS009880 | Ischemic stroke | — | [
|
— | Sub-Saharan African (Nigerian) |
— | NR | Stroke Investigative Research & Educational Network (SIREN) |
| PSS012987 | 386.0,H81.0, H81.31, H81.39 | — | [ ,
47.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011307 | — | — | 1,638 individuals, 49.6 % Male samples |
— | Not reported | — | NSHD | Outcomes tested were metabolite levels generated by Metabolon Inc, and metabolite modules generated using this data. All outcome (metabolite) data were collected at the 60-64 wave of the NSHD. |
| PSS013008 | 386, 780.4,H81, H82, H83.0, H83.1, H83.2, H83.9, R42 | — | [ ,
46.3 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013009 | 386, 780.4,H81, H82, H83.0, H83.1, H83.2, H83.9, R42 | — | [ ,
46.3 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013010 | 386, 780.4,H81, H82, H83.0, H83.1, H83.2, H83.9, R42 | — | [ ,
46.3 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013011 | 386, 780.4,H81, H82, H83.0, H83.1, H83.2, H83.9, R42 | — | [ ,
46.3 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013012 | 386, 780.4,H81, H82, H83.0, H83.1, H83.2, H83.9, R42 | — | [ ,
46.3 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013013 | 389.1,H90.3, H90.4, H90.5, H90.A2, H90.A21, H90.A22 | — | [ ,
46.26 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013014 | 389.1,H90.3, H90.4, H90.5, H90.A2, H90.A21, H90.A22 | — | [ ,
46.26 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013015 | 389.1,H90.3, H90.4, H90.5, H90.A2, H90.A21, H90.A22 | — | [ ,
46.26 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013016 | 389.1,H90.3, H90.4, H90.5, H90.A2, H90.A21, H90.A22 | — | [ ,
46.26 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013017 | 389.1,H90.3, H90.4, H90.5, H90.A2, H90.A21, H90.A22 | — | [ ,
46.26 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009897 | — | — | 228 individuals, 49.6 % Male samples |
Mean = 76.62 years Sd = 4.55 years |
Not reported | — | ADNI | — |
| PSS009898 | CN/MCI/AD: [573/124/83] | — | 780 individuals | — | Not reported | — | NR | AIBL |
| PSS009899 | CN/MCI/AD: [412/66/24] | — | 502 individuals | — | Not reported | — | NR | AIBL |
| PSS009900 | CN/MCI/AD: [161/58/59] | — | 278 individuals | — | Not reported | — | NR | AIBL |
| PSS013023 | 388.0, 388.1, 388.2, 388.3, 388.4, 388.5, 389, 794.15, V41.2, V49.85, V53.2,H83.3, H90, H91, H93.0, H93.1, H93.2, H93.3, H93.A, H93.A1, H93.A2, H93.A3, H93.A9, H94.0, R94.120, Z96.2, Z97.4 | — | [ ,
46.08 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013024 | 388.0, 388.1, 388.2, 388.3, 388.4, 388.5, 389, 794.15, V41.2, V49.85, V53.2,H83.3, H90, H91, H93.0, H93.1, H93.2, H93.3, H93.A, H93.A1, H93.A2, H93.A3, H93.A9, H94.0, R94.120, Z96.2, Z97.4 | — | [ ,
46.08 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000997 | All individuals had Parkinsons' disease. Dementia was defined by the following criteria for each cohort. DeNoPa: Dementia was defined using operationalized level 1 MDS dementia criteria. These criteria required 1, an MMSE< 26; 2, cognitive deficits severe enough to impact daily living (MDS-UPDRS sub-score I item 1, Cognitive impairment score ≥ 2 indicating ‘Dementia has impact on active daily living scale’); 3, impairment in at least two cognitive domains operationalized as impairment in two of the following four tasks: ≤ 3 of 5 points in the MMSE Seven backward test (attention); abnormal clock drawing test (executive dysfunction); subscore = 0 in the MMSE Pentagons (visuo-constructive ability); and ≤ 2 of 3 points in the 3-Word Recall of the MMSE (memory performance). A Geriatric Depression Scale-15 (GDS-15) score <10 was used to indicate the absence of severe depression. EPIPARK: Dementia was defined using operationalized level 1 MDS dementia criteria. These criteria required 1, a Montreal Cognitive Assessment (MoCA) score < 2127; 2, cognitive deficits severe enough to impact daily living (UPDRS sub-score I item 1, Intellectual impairment score ≥ 2 indicating ‘Dementia has impact on active daily living scale’); 3, impairment in at least two cognitive domains operationalized as impairment in two of the following four tasks: ≤ 2 of 3 points in the MoCA serial seven subtraction test; 0 points in the MoCA language fluency test item (language); ≤ 4 of 5 points in the word recall of the MoCA (delayed recall); ≤ 4 of 5 on the MoCA visuospatial/executive test. A Beck Depression Inventory (BDI) score ≤30 was used to indicate the absence of severe depression. HBS: Dementia was defined using operationalized level 1 MDS dementia criteria. These criteria required 1, an MMSE < 26; 2, cognitive deficits severe enough to impact daily living (UPDRS sub-score I item 1, Intellectual impairment score ≥ 2 indicating ‘Dementia has impact on active daily living scale’); 3, impairment in at least two cognitive domains operationalized as impairment in two of the following four tasks: ≤ 3 of 5 points in the MMSE Seven backward test (attention); abnormal clock drawing test (executive dysfunction); subscore = 0 in the MMSE Pentagons (visuo-constructive ability); and ≤ 2 of 3 points in the 3-Word Recall of the MMSE (memory performance). A Geriatric Depression Scale-15 (GDS-15) score <10 was used to indicate the absence of severe depression. | — | 404 individuals | — | European, NR | — | DeNoPa, EPIPARK, HBS | — |
| PSS013025 | 388.0, 388.1, 388.2, 388.3, 388.4, 388.5, 389, 794.15, V41.2, V49.85, V53.2,H83.3, H90, H91, H93.0, H93.1, H93.2, H93.3, H93.A, H93.A1, H93.A2, H93.A3, H93.A9, H94.0, R94.120, Z96.2, Z97.4 | — | [ ,
46.08 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013026 | 388.0, 388.1, 388.2, 388.3, 388.4, 388.5, 389, 794.15, V41.2, V49.85, V53.2,H83.3, H90, H91, H93.0, H93.1, H93.2, H93.3, H93.A, H93.A1, H93.A2, H93.A3, H93.A9, H94.0, R94.120, Z96.2, Z97.4 | — | [ ,
46.08 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013027 | 388.0, 388.1, 388.2, 388.3, 388.4, 388.5, 389, 794.15, V41.2, V49.85, V53.2,H83.3, H90, H91, H93.0, H93.1, H93.2, H93.3, H93.A, H93.A1, H93.A2, H93.A3, H93.A9, H94.0, R94.120, Z96.2, Z97.4 | — | [ ,
46.08 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS001005 | Cases include individuals with Alzheimer's disease (AD) The phenotypes of the participants were determined on the basis of the most recent diagnostic records (until December 2019). | — | [ ,
54.29 % Male samples |
— | East Asian (Chinese) |
— | NR | Participants recruited from the Specialist Outpatient Department of Prince of Wales Hospital. |
| PSS001006 | Cases include individuals with Alzheimer's disease (AD). Patients with definite AD have been diagnosed according to established neuropathological criteria (CERAD, Braak, Khachaturian, NIA-RI, or other established criteria). | — | [ ,
37.62 % Male samples |
— | European | — | LOAD | — |
| PSS004273 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004274 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004275 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS001009 | Cases include participants with the following tumors: Astrocytomas (ICCC-3 group IIIb), Other gliomas (ICCC-3 group IIId), Ependymomas (ICCC-3 group IIIa), Intracranial embryonal tumors (ICCC-3 group IIIc), other specified intracranial neoplasms (ICCC-3 group IIIe), unspecified intracranial neoplasms (ICCC-3 group IIIf) | — | [ ,
54.09 % Male samples |
— | European, NR | European = 454, NR =280 | CEFALO | — |
| PSS004276 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011929 | — | — | [
|
— | East Asian (Korean) |
— | HEXA | — |
| PSS008267 | — | — | 5,858 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS004302 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004303 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004304 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004305 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004306 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004307 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004309 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004310 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004311 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008295 | — | — | 1,716 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008299 | — | — | 6,199 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009931 | — | 4,483 individuals, 53.2 % Male samples |
Mean = 118.94 months Sd = 7.48 months |
European | — | NR | ABCD | |
| PSS012801 | 290.0, 290.2, 290.3,F03 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009933 | — | — | 90 individuals, 71.0 % Male samples |
Mean = 36.0 years | South Asian (Indian) |
— | NR | — |
| PSS013117 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013118 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013119 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013120 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013121 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013122 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013123 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013124 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013125 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013126 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013127 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013128 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013129 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013130 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013131 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013132 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011955 | — | — | [ ,
38.0 % Male samples |
Mean = 74.2 years Sd = 5.5 years |
European (French) |
— | 3C | — |
| PSS011956 | — | — | [
|
— | European (French) |
— | 3C | — |
| PSS011957 | — | — | [
|
— | European (French) |
— | 3C | — |
| PSS011958 | — | — | [
|
— | European (French) |
— | 3C | — |
| PSS011959 | — | — | [ ,
100.0 % Male samples |
— | European (French) |
— | 3C | — |
| PSS011960 | — | — | [ ,
0.0 % Male samples |
— | European (French) |
— | 3C | — |
| PSS011961 | — | — | [
|
— | European (French) |
— | 3C | — |
| PSS011962 | — | — | [ ,
42.0 % Male samples |
Mean = 49.0 years Sd = 15.0 years |
African American or Afro-Caribbean | — | AllofUs | — |
| PSS011963 | — | — | [ ,
36.0 % Male samples |
Mean = 44.0 years Sd = 17.0 years |
East Asian | — | AllofUs | — |
| PSS011964 | — | — | [ ,
40.0 % Male samples |
Mean = 56.0 years Sd = 17.0 years |
European | — | AllofUs | — |
| PSS011965 | — | — | [ ,
33.0 % Male samples |
Mean = 45.0 years Sd = 16.0 years |
Hispanic or Latin American | — | AllofUs | — |
| PSS011966 | — | — | [ ,
39.0 % Male samples |
Mean = 70.9 years Sd = 8.62 years |
European (French) |
— | MEMENTO | — |
| PSS011967 | — | — | [
|
— | European (French) |
— | MEMENTO | — |
| PSS011968 | — | — | [
|
— | European (French) |
— | MEMENTO | — |
| PSS009939 | — | — | 39,444 individuals | — | European (Finnish) |
— | FinnGen | — |
| PSS011969 | — | — | [ ,
100.0 % Male samples |
— | European (French) |
— | MEMENTO | — |
| PSS011970 | — | — | [ ,
0.0 % Male samples |
— | European (French) |
— | MEMENTO | — |
| PSS011971 | — | — | 605 individuals | — | European (French) |
— | MEMENTO | — |
| PSS011972 | — | — | 1,427 individuals | — | European (French) |
— | MEMENTO | — |
| PSS013152 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013153 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013154 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013146 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013156 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013148 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013150 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013151 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013155 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011985 | — | — | [
|
— | European | — | UKB | — |
| PSS011318 | — | — | 18,505 individuals, 81.9 % Male samples |
Mean = 55.4 years Sd = 11.8 years |
African American or Afro-Caribbean | — | MVP | — |
| PSS011319 | — | — | 6,785 individuals, 86.5 % Male samples |
Mean = 52.6 years Sd = 14.8 years |
Hispanic or Latin American | — | MVP | — |
| PSS009949 | NIH Toolbox was used to measure cognition in ABCD. Children’s problems and competencies were rated using the parent-reported Children Behavior Checklist (CBCL). Details of the ABCD MRI data acquisition and analysis have been published previously. | — | 2,198 individuals, 0.0 % Male samples |
Mean = 9.89 years Sd = 0.61 years |
European | — | ABCD | — |
| PSS009950 | NIH Toolbox was used to measure cognition in ABCD. Children’s problems and competencies were rated using the parent-reported Children Behavior Checklist (CBCL). Details of the ABCD MRI data acquisition and analysis have been published previously. | — | 2,524 individuals, 100.0 % Male samples |
Mean = 9.92 years Sd = 0.62 years |
European | — | ABCD | — |
| PSS009951 | Fluid intelligence test | — | 78,561 individuals, 0.0 % Male samples |
Mean = 57.46 years Sd = 8.08 years |
European | — | UKB | — |
| PSS009952 | imaging-derived phenotypes (IDPs) generated by an image-processing pipeline developed and ran on behalf of the UKB | — | 10,343 individuals, 0.0 % Male samples |
Mean = 63.13 years Sd = 7.3 years |
European | — | UKB | — |
| PSS009953 | Fluid intelligence test | — | 68,614 individuals, 100.0 % Male samples |
Mean = 58.39 years Sd = 8.36 years |
European | — | UKB | — |
| PSS009954 | imaging-derived phenotypes (IDPs) generated by an image-processing pipeline developed and ran on behalf of the UKB | — | 11,180 individuals, 100.0 % Male samples |
Mean = 64.6 years Sd = 7.57 years |
European | — | UKB | — |
| PSS011320 | — | — | 53,861 individuals, 88.2 % Male samples |
Mean = 59.3 years Sd = 13.8 years |
European | — | MVP | — |
| PSS008393 | — | — | 1,162 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS004418 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS000358 | UPDRS motor severity was estimated as a mean value acrosseach patient’s recordings, relative to the rest of the data | Mean = 5946.0 days Sd = 2299.0 days Range = [1574.0, 13992.0] days |
[ ,
66.0 % Male samples |
Range = [35.0, 85.0] years | European | — | NR | Testing dataset genotyped as part of a larger study of a total of 1380 patients with idiopathic PD and 1295 control subjects by 5 collaborating groups in Norway and Sweden. (https://www.sciencedirect.com/science/article/abs/pii/S0197458012005301?showall%3Dtrue%26via%3Dihub) |
| PSS004419 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004420 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004421 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004422 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008399 | — | — | 1,186 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008401 | — | — | 1,055 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008400 | — | — | 1,183 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008403 | — | — | 1,164 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008404 | — | — | 1,191 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008405 | — | — | 1,169 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008406 | — | — | 1,165 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008417 | — | — | 1,198 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008418 | — | — | 1,183 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS010105 | ICD codes I67.1 and I60 | — | [
|
— | European (Norwegian) |
— | HUNT2 | — |
| PSS011179 | — | — | 1,005 individuals | — | African unspecified | — | MGBB | — |
| PSS011179 | — | — | 306 individuals | — | Asian unspecified | — | MGBB | — |
| PSS011179 | — | — | 20,348 individuals | — | European | — | MGBB | — |
| PSS011179 | — | — | 614 individuals | — | Hispanic or Latin American | — | MGBB | — |
| PSS011179 | — | — | 884 individuals | — | Not reported | — | MGBB | — |
| PSS011180 | — | — | 4,189 individuals | Mean = 63.0 years | Hispanic or Latin American (Central American, South American, Mexican, Cuban, Dominican, Puerto-Rican) |
— | HCHS-SOL | SOL-INCA: Study of Latinos-Investigation of Neurocognitive Aging |
| PSS001049 | Cases are individuals with multiple sclerosis. | — | [
|
— | European | Mainland Scotland | GS:SFHS | — |
| PSS001050 | Cases are individuals with multiple sclerosis. | — | [
|
— | European | Orkney | ORCADES | — |
| PSS001051 | Cases are individuals with multiple sclerosis. | — | [
|
— | European | Shetlands | VIKING | — |
| PSS001052 | The diagnosis of dementia at each examination was based on Diagnostic and Statistical Manual of Mental Disorders Third Edition‐Revised (DSM‐III‐R) criteria, using information from neuropsychiatric examinations and close informant interviews. Dementia diagnoses for individuals lost to follow‐up were based on information obtained from the Swedish Inpatient Registry until 2012. Age of dementia onset was based on information provided by close informants, the examinations, and the Swedish Inpatient Register. If no information could be obtained from these sources, the age of onset was determined as the mid‐point between the last examination at which dementia criteria were not fulfilled and the first with a dementia diagnosis. Information on deaths during follow‐up was obtained from the Swedish Population Registry until December 31, 2016. Of the 605 dementia cases, 182 were carriers of an APOE ɛ4 allele. | Mean = 7.2 years Sd = 4.7 years |
[
|
European | — | NR | Gothenburg H70 Birth Cohort studies | |
| PSS008489 | — | — | 1,089 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008935 | — | — | 3,691 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS001065 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001066 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Hispanic or Latin American | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Asian unspecified, Native American, NR | — | BioMe | — |
| PSS012840 | 296.2, 296.3, 311,F32, F33 | — | [ ,
46.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS008517 | — | — | 363 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008521 | — | — | 1,153 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS001080 | Cases included incident Alzheimer's disease (AD) and other types of incident dementia. Of the 1,609 dementia cases, 1,262 were individuals with AD and 347 were individuals with other types of dementia excluding AD. A consensus panel led by a consultant neurologist established the final diagnosis according to standard criteria for dementia (Diagnostic and Statistical Manual of Mental Disorders III-revised) and Alzheimer’s disease (National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association). Of the total 12,255 individuals, APOE genotypes were available for 11,375. From those genotyped, 261 individuals were homozygous for APOE ε4 (ε4/ε4). Of the 261 ε4/ε4 individuals, 72 had AD whilst 11 had other types of dementia excluding AD. | Median = 10.9 years | [ ,
41.5 % Male samples |
European (Dutch) |
— | RS | — | |
| PSS001081 | Cases were individuals with incident-all cause dementia. Dementia was diagnosed using Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria. Diagnosis date was recorded as date of trigger. Dementia cases were sub-classified into either 'probable Alzheimer's Disease (AD)', 'possible AD' or 'non-dementia AD' using the 2011 NIA-Alzheimer's Association core clinical criteria. Of the 324 cases, 143 were classified as 'probable AD', 176 were classified as 'possible AD' and 5 were classified as 'non-AD related dementia'. | Median = 4.5 years IQR = [2.1, 5.7] years |
[ ,
45.0 % Male samples |
Mean = 75.05 years Sd = 4.2 years |
European | — | ASPREE | — |
| PSS001082 | Cases were individuals who had experienced an ischemic stroke (IS) event. IS was defined according to the World Health Organization definition and included imaging by computed tomography or magnetic resonance imaging in the majority of cases. All cases of IS were further divided into subtypes of large vessel (n=49), small vessel (n=43), cardioembolic (n=36), and undetermined. Undetermined strokes had undetermined causes, multiple causes identified, or an incomplete evaluation made. All stroke events were assessed by an adjudication committee, blinded to the identity of participants and study treatment group assignment. | Median = 4.7 years IQR = [3.6, 5.7] years |
[ ,
45.1 % Male samples |
Mean = 75.1 years Sd = 4.2 years |
European | — | ASPREE | — |
| PSS011330 | — | — | 196,368 individuals, 47.3 % Male samples |
Mean = 64.1 years Sd = 2.9 years |
European | — | UKB | — |
| PSS012047 | — | — | [ ,
45.5 % Male samples |
Mean = 56.48 years Sd = 8.1 years |
European | — | UKB | — |
| PSS012851 | 307, 316, 333.92, 648.4, V11.2, V11.8, V11.9, V15.4, V40.2, V40.3, V40.9, V62.85, V66.3, V67.3, V70.1, V70.2, V71.0,F54, G21.0, G44.2, O90.6, O99.31, O99.34, R45.850, Z86.59 | — | [ ,
46.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS001084 | Moderate Age-Related Diabetes (MARD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001085 | Moderate Obesity-related Diabetes (MOD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001086 | Severe Autoimmune Diabetes (SAID) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001087 | Severe Insulin-Deficient Diabetes (SIDD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001088 | Severe Insulin-Resistant Diabetes (SIRD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS004614 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004615 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004616 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004617 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004618 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004619 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004620 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004621 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004622 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004624 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004625 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004626 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008606 | — | — | 6,626 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS004632 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004634 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004635 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004636 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004637 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004639 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004640 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004641 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004642 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004643 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004644 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004645 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004646 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008617 | — | — | 6,465 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008625 | — | — | 6,562 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008626 | — | — | 6,544 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008627 | — | — | 5,989 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008629 | — | — | 6,463 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008630 | — | — | 6,611 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008631 | — | — | 6,514 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008632 | — | — | 6,470 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008963 | — | — | 1,043 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS001125 | Cases included individuals with Alzheimer's disease. | — | [
|
— | European | — | 11 cohorts
|
— |
| PSS001126 | All individuals were aged 55 and above. Cases include individuals with Alzheimer's disease. | — | [
|
— | European | — | 11 cohorts
|
— |
| PSS001127 | Cases included individuals with Alzheimer's disease. | — | [
|
— | European | — | 11 cohorts
|
— |
| PSS008643 | — | — | 6,641 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008644 | — | — | 6,521 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS004672 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004673 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004674 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004675 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004676 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011336 | — | — | [ ,
46.0 % Male samples |
— | European (White British) |
— | UKB | — |
| PSS008967 | — | — | 3,863 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS012082 | — | — | [
|
— | European (Finnish) |
— | FINRISK | — |
| PSS004682 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004683 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004684 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004685 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004686 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004687 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004688 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004689 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004690 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004691 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004692 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004693 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004694 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004695 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004696 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011345 | — | — | [ ,
46.0 % Male samples |
— | European (White British) |
— | UKB | — |
| PSS010009 | PheCode 327.4 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | MGI | — |
| PSS012880 | 327.5, 333.94, 780.58,G25.81, G47.6 | — | [ ,
47.11 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS001167 | Cases were individuals with pathologically or clinically diagnosed Alzheimer's disease (AD). Of the 1008 AD cases, 332 had been confirmed pathologically whilst 676 had been confirmed clinically. Pathological AD was confirmed by the Biobanc Hospital Clínic–IDIBAPS, whilst clinical diagnosis of AD was based on clinical criteria from Fundació ACE. | — | [ ,
29.2 % Male samples |
— | European (Spanish) |
— | EADB | — |
| PSS012881 | 327.5, 333.94, 780.58,G25.81, G47.6 | — | [ ,
47.11 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011213 | — | — | [
|
— | European | — | EB | — |
| PSS008715 | — | — | 6,265 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS012882 | 327.5, 333.94, 780.58,G25.81, G47.6 | — | [ ,
47.11 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011223 | — | — | [
|
— | European | — | EB | — |
| PSS011226 | G6_AD_WIDE, ICD10: G30|F00, ICD9: 3310 | — | [
|
— | European | — | FinnGen | — |
| PSS012105 | — | — | 3,453 individuals, 64.7 % Male samples |
Mean = 65.6 years Sd = 9.6 years |
Not reported | — | OD, PPMI, TP | — |
| PSS011234 | I9_STR, ICD10: I61 | I63 | I64 (exclude I636), ICD9:431|4330A|4331A|4339A|4340A|4341A|4349A|436 | — | [
|
— | European | — | FinnGen | — |
| PSS001174 | Cases were individuals with Parkinson's disease (PD). Cases were defined using the standard UK Brain Bank criteria with a modification to allow the inclusion of cases that had a family history of PD. | — | [ ,
52.75 % Male samples |
— | European, NR | — | HBS | Sample overlap between this dataset and the dataset used to source SNPs for PRS90_PD. |
| PSS000435 | Cases were selected from the iPSYCH sample as those diagnosed with ASD in 2013 or earlier by a psychiatrist according to ICD10, including diagnoses of childhood autism (ICD10 code F84.0), atypical autism (F84.1), Asperger’s syndrome (F84.5), other pervasive developmental disorders (F84.8), and pervasive developmental disorder, unspecified (F84.9). As controls we selected from the random iPSYCH control cohort children that did not have an ASD diagnosis by 2013. | — | [
|
Mean (Age At Diagnosis) = 10.0 years Range = [10.0, 14.0] years |
European | — | iPSYCH | Average case/control numbers of each fold used in cross-validation (1/5th of total iPSYCH). |
| PSS008743 | — | — | 1,537 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS011350 | — | — | 53,447 individuals | — | European | — | UKB | Mean age of full combined ancestry cohort = 58 years |
| PSS008747 | — | — | 6,626 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS011247 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS010048 | phecode 296.22 | — | [
|
— | European | — | MGI | — |
| PSS011350 | — | — | 1,118 individuals | — | African unspecified | — | UKB | Mean age of full combined ancestry cohort = 58 years |
| PSS011252 | — | — | [
|
— | European | — | HUNT | — |
| PSS011350 | — | — | 3,123 individuals | — | Asian unspecified, Not reported | — | UKB | Mean age of full combined ancestry cohort = 58 years |
| PSS001185 | — | — | [
|
— | European | — | AGDS | — |
| PSS001186 | — | — | [
|
— | European | — | AGDS | — |
| PSS001187 | — | — | [
|
— | European | — | AGDS | — |
| PSS001188 | — | — | [
|
— | European | — | AGDS | — |
| PSS001189 | — | — | [
|
— | European | — | AGDS | — |
| PSS001190 | — | — | [
|
— | European | — | AGDS | — |
| PSS001191 | — | — | [
|
— | European | — | AGDS | — |
| PSS001192 | — | — | [
|
— | European | — | AGDS | — |
| PSS001193 | — | — | [
|
— | European | — | AGDS | — |
| PSS001194 | — | — | [
|
— | European | — | AGDS | — |
| PSS000449 | — | — | [ ,
54.7 % Male samples |
Mean (Cases) = 77.6 years Sd (Cases) = 7.6 years |
European | — | ABIL | — |
| PSS000449 | — | — | [ ,
44.4 % Male samples |
Mean (Cases) = 86.8 years Sd (Cases) = 4.6 years |
European | — | MAS | — |
| PSS000449 | — | — | [ ,
47.0 % Male samples |
Mean (Cases) = 64.4 years Sd (Cases) = 4.5 years |
European | — | UKB | — |
| PSS001195 | — | — | [
|
— | European | — | AGDS | — |
| PSS001199 | — | — | [
|
— | European | — | AGDS | — |
| PSS001197 | — | — | [
|
— | European | — | AGDS | — |
| PSS001201 | — | — | [
|
— | European | — | AGDS | — |
| PSS001196 | — | — | [
|
— | European | — | AGDS | — |
| PSS001203 | — | — | [
|
— | European | — | AGDS | — |
| PSS001204 | — | — | [
|
— | European | — | AGDS | — |
| PSS001200 | — | — | [
|
— | European | — | AGDS | — |
| PSS001198 | — | — | [
|
— | European | — | AGDS | — |
| PSS001202 | — | — | [
|
— | European | — | AGDS | — |
| PSS001205 | — | — | [
|
— | European | — | AGDS | — |
| PSS001207 | — | — | [
|
— | European | — | AGDS | — |
| PSS001206 | — | — | [
|
— | European | — | AGDS | — |
| PSS001211 | — | — | [
|
— | European | — | AGDS | — |
| PSS001210 | — | — | [
|
— | European | — | AGDS | — |
| PSS001208 | — | — | [
|
— | European | — | AGDS | — |
| PSS001212 | — | — | [
|
— | European | — | AGDS | — |
| PSS001215 | — | — | [
|
— | European | — | AGDS | — |
| PSS001216 | — | — | [
|
— | European | — | AGDS | — |
| PSS001217 | — | — | [
|
— | European | — | AGDS | — |
| PSS001218 | — | — | [
|
— | European | — | AGDS | — |
| PSS001219 | — | — | [
|
— | European | — | AGDS | — |
| PSS001220 | — | — | [
|
— | European | — | AGDS | — |
| PSS001221 | — | — | [
|
— | European | — | AGDS | — |
| PSS001222 | — | — | [
|
— | European | — | AGDS | — |
| PSS001223 | — | — | [
|
— | European | — | AGDS | — |
| PSS001224 | — | — | [
|
— | European | — | AGDS | — |
| PSS001225 | — | — | [
|
— | European | — | AGDS | — |
| PSS001226 | — | — | [
|
— | European | — | AGDS | — |
| PSS001227 | — | — | [
|
— | European | — | AGDS | — |
| PSS001228 | — | — | [
|
— | European | — | AGDS | — |
| PSS001229 | — | — | [
|
— | European | — | AGDS | — |
| PSS001230 | — | — | [
|
— | European | — | AGDS | — |
| PSS001231 | — | — | [
|
— | European | — | AGDS | — |
| PSS001232 | — | — | [
|
— | European | — | AGDS | — |
| PSS001233 | — | — | [
|
— | European | — | AGDS | — |
| PSS001234 | — | — | [
|
— | European | — | AGDS | — |
| PSS001235 | — | — | [
|
— | European | — | AGDS | — |
| PSS001236 | — | — | [
|
— | European | — | AGDS | — |
| PSS001237 | — | — | [
|
— | European | — | AGDS | — |
| PSS001238 | — | — | [
|
— | European | — | AGDS | — |
| PSS001239 | — | — | [
|
— | European | — | AGDS | — |
| PSS001240 | — | — | [
|
— | European | — | AGDS | — |
| PSS001241 | — | — | [
|
— | European | — | AGDS | — |
| PSS001242 | — | — | [
|
— | European | — | AGDS | — |
| PSS001243 | — | — | [
|
— | European | — | AGDS | — |
| PSS001244 | — | — | [
|
— | European | — | AGDS | — |
| PSS001245 | — | — | [
|
— | European | — | AGDS | — |
| PSS001246 | — | — | [
|
— | European | — | AGDS | — |
| PSS001247 | — | — | [
|
— | European | — | AGDS | — |
| PSS001248 | — | — | [
|
— | European | — | AGDS | — |
| PSS001249 | — | — | [
|
— | European | — | AGDS | — |
| PSS001250 | — | — | [
|
— | European | — | AGDS | — |
| PSS001251 | — | — | [
|
— | European | — | AGDS | — |
| PSS001252 | — | — | [
|
— | European | — | AGDS | — |
| PSS001253 | — | — | [
|
— | European | — | AGDS | — |
| PSS001254 | — | — | [
|
— | European | — | AGDS | — |
| PSS001255 | — | — | [
|
— | European | — | AGDS | — |
| PSS001256 | — | — | [
|
— | European | — | AGDS | — |
| PSS001257 | — | — | [
|
— | European | — | AGDS | — |
| PSS001258 | — | — | [
|
— | European | — | AGDS | — |
| PSS001259 | — | — | [
|
— | European | — | AGDS | — |
| PSS001260 | — | — | [
|
— | European | — | AGDS | — |
| PSS001261 | — | — | [
|
— | European | — | AGDS | — |
| PSS001262 | — | — | [
|
— | European | — | AGDS | — |
| PSS001263 | — | — | [
|
— | European | — | AGDS | — |
| PSS001264 | — | — | [
|
— | European | — | AGDS | — |
| PSS001265 | — | — | [
|
— | European | — | AGDS | — |
| PSS001266 | — | — | [
|
— | European | — | AGDS | — |
| PSS001267 | — | — | [
|
— | European | — | AGDS | — |
| PSS001268 | — | — | [
|
— | European | — | AGDS | — |
| PSS001269 | — | — | [
|
— | European | — | AGDS | — |
| PSS001270 | — | — | [
|
— | European | — | AGDS | — |
| PSS001271 | — | — | [
|
— | European | — | AGDS | — |
| PSS001272 | — | — | [
|
— | European | — | AGDS | — |
| PSS001273 | — | — | [
|
— | European | — | AGDS | — |
| PSS001274 | — | — | [
|
— | European | — | AGDS | — |
| PSS001275 | — | — | [
|
— | European | — | AGDS | — |
| PSS001276 | — | — | [
|
— | European | — | AGDS | — |
| PSS001277 | — | — | [
|
— | European | — | AGDS | — |
| PSS001278 | — | — | [
|
— | European | — | AGDS | — |
| PSS001279 | — | — | [
|
— | European | — | AGDS | — |
| PSS001280 | — | — | [
|
— | European | — | AGDS | — |
| PSS001281 | — | — | [
|
— | European | — | AGDS | — |
| PSS001282 | — | — | [
|
— | European | — | AGDS | — |
| PSS001283 | — | — | [
|
— | European | — | AGDS | — |
| PSS001284 | — | — | [
|
— | European | — | AGDS | — |
| PSS001285 | — | — | [
|
— | European | — | AGDS | — |
| PSS001286 | — | — | [
|
— | European | — | AGDS | — |
| PSS001287 | — | — | [
|
— | European | — | AGDS | — |
| PSS001288 | — | — | [
|
— | European | — | AGDS | — |
| PSS001289 | — | — | [
|
— | European | — | AGDS | — |
| PSS001290 | — | — | [
|
— | European | — | AGDS | — |
| PSS001291 | — | — | [
|
— | European | — | AGDS | — |
| PSS001292 | — | — | [
|
— | European | — | AGDS | — |
| PSS001293 | — | — | [
|
— | European | — | AGDS | — |
| PSS001294 | — | — | [
|
— | European | — | AGDS | — |
| PSS001295 | — | — | [
|
— | European | — | AGDS | — |
| PSS001296 | — | — | [
|
— | European | — | AGDS | — |
| PSS001297 | — | — | [
|
— | European | — | AGDS | — |
| PSS001298 | — | — | [
|
— | European | — | AGDS | — |
| PSS001299 | — | — | [
|
— | European | — | AGDS | — |
| PSS001300 | — | — | [
|
— | European | — | AGDS | — |
| PSS001301 | — | — | [
|
— | European | — | AGDS | — |
| PSS001302 | — | — | [
|
— | European | — | AGDS | — |
| PSS001303 | — | — | [
|
— | European | — | AGDS | — |
| PSS001304 | — | — | [
|
— | European | — | AGDS | — |
| PSS001305 | — | — | [
|
— | European | — | AGDS | — |
| PSS001306 | — | — | [
|
— | European | — | AGDS | — |
| PSS001307 | — | — | [
|
— | European | — | AGDS | — |
| PSS001308 | — | — | [
|
— | European | — | AGDS | — |
| PSS001309 | — | — | [
|
— | European | — | AGDS | — |
| PSS001310 | — | — | [
|
— | European | — | AGDS | — |
| PSS001311 | — | — | [
|
— | European | — | AGDS | — |
| PSS001312 | — | — | [
|
— | European | — | AGDS | — |
| PSS001313 | — | — | [
|
— | European | — | AGDS | — |
| PSS001314 | — | — | [
|
— | European | — | AGDS | — |
| PSS001315 | — | — | [
|
— | European | — | AGDS | — |
| PSS001316 | — | — | [
|
— | European | — | AGDS | — |
| PSS001317 | — | — | [
|
— | European | — | AGDS | — |
| PSS001318 | — | — | [
|
— | European | — | AGDS | — |
| PSS001319 | — | — | [
|
— | European | — | AGDS | — |
| PSS001320 | — | — | [
|
— | European | — | AGDS | — |
| PSS001321 | — | — | [
|
— | European | — | AGDS | — |
| PSS001322 | — | — | [
|
— | European | — | AGDS | — |
| PSS001323 | — | — | [
|
— | European | — | AGDS | — |
| PSS001324 | — | — | [
|
— | European | — | AGDS | — |
| PSS001325 | — | — | [
|
— | European | — | AGDS | — |
| PSS001326 | — | — | [
|
— | European | — | AGDS | — |
| PSS001327 | — | — | [
|
— | European | — | AGDS | — |
| PSS001328 | — | — | [
|
— | European | — | AGDS | — |
| PSS001329 | — | — | [
|
— | European | — | AGDS | — |
| PSS001330 | — | — | [
|
— | European | — | AGDS | — |
| PSS001331 | — | — | [
|
— | European | — | AGDS | — |
| PSS001332 | — | — | [
|
— | European | — | AGDS | — |
| PSS001333 | — | — | [
|
— | European | — | AGDS | — |
| PSS001334 | — | — | [
|
— | European | — | AGDS | — |
| PSS001335 | — | — | [
|
— | European | — | AGDS | — |
| PSS001336 | — | — | [
|
— | European | — | AGDS | — |
| PSS001337 | — | — | [
|
— | European | — | AGDS | — |
| PSS001338 | — | — | [
|
— | European | — | AGDS | — |
| PSS001339 | — | — | [
|
— | European | — | AGDS | — |
| PSS001340 | — | — | [
|
— | European | — | AGDS | — |
| PSS001341 | — | — | [
|
— | European | — | AGDS | — |
| PSS001342 | — | — | [
|
— | European | — | AGDS | — |
| PSS001343 | — | — | [
|
— | European | — | AGDS | — |
| PSS001344 | — | — | [
|
— | European | — | AGDS | — |
| PSS001345 | — | — | [
|
— | European | — | AGDS | — |
| PSS001346 | — | — | [
|
— | European | — | AGDS | — |
| PSS001347 | — | — | [
|
— | European | — | AGDS | — |
| PSS001348 | — | — | [
|
— | European | — | AGDS | — |
| PSS001349 | — | — | [
|
— | European | — | AGDS | — |
| PSS001350 | — | — | [
|
— | European | — | AGDS | — |
| PSS001351 | — | — | [
|
— | European | — | AGDS | — |
| PSS001352 | — | — | [
|
— | European | — | AGDS | — |
| PSS001353 | — | — | [
|
— | European | — | AGDS | — |
| PSS001354 | — | — | [
|
— | European | — | AGDS | — |
| PSS001355 | — | — | [
|
— | European | — | AGDS | — |
| PSS001356 | — | — | [
|
— | European | — | AGDS | — |
| PSS001357 | — | — | [
|
— | European | — | AGDS | — |
| PSS001358 | — | — | [
|
— | European | — | AGDS | — |
| PSS001359 | — | — | [
|
— | European | — | AGDS | — |
| PSS001360 | — | — | [
|
— | European | — | AGDS | — |
| PSS001361 | — | — | [
|
— | European | — | AGDS | — |
| PSS001362 | — | — | [
|
— | European | — | AGDS | — |
| PSS001363 | — | — | [
|
— | European | — | AGDS | — |
| PSS001364 | — | — | [
|
— | European | — | AGDS | — |
| PSS001365 | — | — | [
|
— | European | — | AGDS | — |
| PSS001366 | — | — | [
|
— | European | — | AGDS | — |
| PSS001367 | — | — | [
|
— | European | — | AGDS | — |
| PSS001368 | — | — | [
|
— | European | — | AGDS | — |
| PSS001369 | — | — | [
|
— | European | — | AGDS | — |
| PSS001370 | — | — | [
|
— | European | — | AGDS | — |
| PSS001371 | — | — | [
|
— | European | — | AGDS | — |
| PSS001372 | — | — | [
|
— | European | — | AGDS | — |
| PSS001373 | — | — | [
|
— | European | — | AGDS | — |
| PSS001374 | — | — | [
|
— | European | — | AGDS | — |
| PSS001375 | — | — | [
|
— | European | — | AGDS | — |
| PSS001376 | — | — | [
|
— | European | — | AGDS | — |
| PSS001377 | — | — | [
|
— | European | — | AGDS | — |
| PSS001378 | — | — | [
|
— | European | — | AGDS | — |
| PSS001379 | — | — | [
|
— | European | — | AGDS | — |
| PSS001380 | — | — | [
|
— | European | — | AGDS | — |
| PSS001381 | — | — | [
|
— | European | — | AGDS | — |
| PSS001382 | — | — | [
|
— | European | — | AGDS | — |
| PSS001383 | — | — | [
|
— | European | — | AGDS | — |
| PSS001384 | — | — | [
|
— | European | — | AGDS | — |
| PSS001385 | — | — | [
|
— | European | — | AGDS | — |
| PSS001386 | — | — | [
|
— | European | — | AGDS | — |
| PSS001387 | — | — | [
|
— | European | — | AGDS | — |
| PSS001388 | — | — | [
|
— | European | — | AGDS | — |
| PSS001389 | — | — | [
|
— | European | — | AGDS | — |
| PSS001390 | — | — | [
|
— | European | — | AGDS | — |
| PSS001391 | — | — | [
|
— | European | — | AGDS | — |
| PSS001392 | — | — | [
|
— | European | — | AGDS | — |
| PSS001393 | — | — | [
|
— | European | — | AGDS | — |
| PSS001394 | — | — | [
|
— | European | — | AGDS | — |
| PSS001395 | — | — | [
|
— | European | — | AGDS | — |
| PSS001396 | — | — | [
|
— | European | — | AGDS | — |
| PSS001397 | — | — | [
|
— | European | — | AGDS | — |
| PSS001398 | — | — | [
|
— | European | — | AGDS | — |
| PSS001399 | — | — | [
|
— | European | — | AGDS | — |
| PSS001400 | — | — | [
|
— | European | — | AGDS | — |
| PSS001401 | — | — | [
|
— | European | — | AGDS | — |
| PSS001402 | — | — | [
|
— | European | — | AGDS | — |
| PSS001403 | — | — | [
|
— | European | — | AGDS | — |
| PSS001404 | — | — | [
|
— | European | — | AGDS | — |
| PSS001405 | — | — | [
|
— | European | — | AGDS | — |
| PSS001406 | — | — | [
|
— | European | — | AGDS | — |
| PSS001407 | — | — | [
|
— | European | — | AGDS | — |
| PSS001408 | — | — | [
|
— | European | — | AGDS | — |
| PSS001409 | — | — | [
|
— | European | — | AGDS | — |
| PSS001410 | — | — | [
|
— | European | — | AGDS | — |
| PSS001411 | — | — | [
|
— | European | — | AGDS | — |
| PSS001412 | — | — | [
|
— | European | — | AGDS | — |
| PSS001413 | — | — | [
|
— | European | — | AGDS | — |
| PSS001414 | — | — | [
|
— | European | — | AGDS | — |
| PSS001415 | — | — | [
|
— | European | — | AGDS | — |
| PSS001416 | — | — | [
|
— | European | — | AGDS | — |
| PSS001417 | — | — | [
|
— | European | — | AGDS | — |
| PSS001418 | — | — | [
|
— | European | — | AGDS | — |
| PSS001419 | — | — | [
|
— | European | — | AGDS | — |
| PSS001420 | — | — | [
|
— | European | — | AGDS | — |
| PSS001421 | — | — | [
|
— | European | — | AGDS | — |
| PSS001422 | — | — | [
|
— | European | — | AGDS | — |
| PSS001423 | — | — | [
|
— | European | — | AGDS | — |
| PSS001424 | — | — | [
|
— | European | — | AGDS | — |
| PSS001425 | — | — | [
|
— | European | — | AGDS | — |
| PSS001426 | — | — | [
|
— | European | — | AGDS | — |
| PSS001427 | — | — | [
|
— | European | — | AGDS | — |
| PSS001428 | — | — | [
|
— | European | — | AGDS | — |
| PSS001429 | — | — | [
|
— | European | — | AGDS | — |
| PSS001430 | — | — | [
|
— | European | — | AGDS | — |
| PSS001431 | — | — | [
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— | European | — | AGDS | — |
| PSS001432 | — | — | [
|
— | European | — | AGDS | — |
| PSS001433 | — | — | [
|
— | European | — | AGDS | — |
| PSS001434 | — | — | [
|
— | European | — | AGDS | — |
| PSS001435 | — | — | [
|
— | European | — | AGDS | — |
| PSS001436 | — | — | [
|
— | European | — | AGDS | — |
| PSS001437 | — | — | [
|
— | European | — | AGDS | — |
| PSS001438 | — | — | [
|
— | European | — | AGDS | — |
| PSS001439 | — | — | [
|
— | European | — | AGDS | — |
| PSS001440 | — | — | [
|
— | European | — | AGDS | — |
| PSS001441 | — | — | [
|
— | European | — | AGDS | — |
| PSS001442 | — | — | [
|
— | European | — | AGDS | — |
| PSS001443 | — | — | [
|
— | European | — | AGDS | — |
| PSS001444 | — | — | [
|
— | European | — | AGDS | — |
| PSS001445 | All individuals had a history of incident atrial fibrillation (AF) following enrollment. 2,310 individuals were taking warfarin. Cases were individuals with ischemic stroke (IS). IS was defined uisng the UKB codes: 131368, 42008. Of the 2,310 individuals taking warfarin, 93 were individuals with ischemic stroke (cases). | Median = 7.0 years | [ ,
66.7 % Male samples |
European | — | UKB | — | |
| PSS011377 | — | — | [ ,
39.3 % Male samples |
Mean = 69.8 years Sd = 9.3 years |
East Asian (Korean) |
— | BICWALZS, PREMIER | — |
| PSS011381 | — | — | [
|
— | European, Native American, African unspecified | — | TANGL | — |
| PSS012178 | Braak NFT Stage | — | [
|
— | European | — | NACC | — |
| PSS011382 | — | — | [
|
— | European | — | UKB | — |
| PSS011382 | — | — | [
|
— | Asian unspecified | — | UKB | — |
| PSS011382 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS011382 | — | — | [
|
— | East Asian (Chinese) |
— | UKB | — |
| PSS011382 | — | — | [
|
— | Not reported | — | UKB | — |
| PSS012179 | CERAD score | — | [
|
— | European | — | NACC | — |
| PSS012181 | — | — | [
|
— | Hispanic or Latin American (Brazilian) |
— | NR | — |
| PSS010179 | The test cohort consisted of individuals without a history of ICH at baseline and anticoagulant use defined by self-report in the verbal interview at inclusion. Furthermore, individuals were included if they had a diagnosis of the International Classification of Diseases, Tenth Revision code Z92.1 (personal history of long-term (current) use of anticoagulants) or D68.3 (hemorrhagic disorder due to circulating anticoagulants) at baseline or a prescription of an anticoagulant medication between baseline and 6 months thereafter in the primary care data | Mean = 11.9 years | [ ,
69.0 % Male samples |
Mean = 62.0 years | European | — | UKB | — |
| PSS010179 | The test cohort consisted of individuals without a history of ICH at baseline and anticoagulant use defined by self-report in the verbal interview at inclusion. Furthermore, individuals were included if they had a diagnosis of the International Classification of Diseases, Tenth Revision code Z92.1 (personal history of long-term (current) use of anticoagulants) or D68.3 (hemorrhagic disorder due to circulating anticoagulants) at baseline or a prescription of an anticoagulant medication between baseline and 6 months thereafter in the primary care data | Mean = 11.9 years | [ ,
69.0 % Male samples |
Mean = 62.0 years | Not reported | — | UKB | — |
| PSS013823 | WHIIRS 5-question score ≥10. | — | [
|
— | Hispanic or Latin American (Central American, Cuban, Dominican, Mexican, Puerto Rican, and South America) |
— | HCHS/SOL | Visit 1; survey-weighted analysis. |
| PSS013823 | WHIIRS 5-question score ≥10. | — | [
|
— | European, African American or Afro-Caribbean, Hispanic or Latin American, East Asian (European, Black, Hispanic/Latino, and Chinese American) |
— | MESA | Visit 5. |
| PSS013823 | Modified 3-question WHIIRS score ≥6. | — | [
|
— | European | — | ARIC | Visit 4 / Sleep Heart Health Study assessment. |
| PSS009052 | — | — | 4,114 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS013823 | WHIIRS 5-question score ≥10. | — | [
|
— | European, African American or Afro-Caribbean, Hispanic or Latin American, East Asian (European, Black, Hispanic/Latino, and Chinese American) |
— | BHS_b | BiCEPS visit. |
| PSS011390 | CVD ICD-10: I20-I25, I60-I64, G45 | — | 12,780 individuals, 0.0 % Male samples |
— | European | — | UKB | Mean age of full combined ancestry cohort = 58.8 years (sd = 7.1) |
| PSS011390 | CVD ICD-10: I20-I25, I60-I64, G45 | — | 568 individuals, 0.0 % Male samples |
— | Not reported | — | UKB | Mean age of full combined ancestry cohort = 58.8 years (sd = 7.1) |
| PSS011392 | Used the following tests to assess memory performance: the total immediate recall and delayed recall of the Rey Auditory Verbal Learning Test (RAVLT), the twenty minute recall of the Rey Complex Figure Test (RCFT), the total errors of the Cambridge Neuropsychological Test Automated Battery (CANTAB) Paired Associate Learning (PAL) test, and the total score of the Face Name Associated Memory Examination (FNAME) names and occupations delayed recall. | Mean = 2.0 years Sd = 0.4 years |
276 individuals, 37.0 % Male samples |
Mean = 74.7 years Sd = 9.7 years |
European | — | ACPRC, NTR | Cognitively unimpaired. Includes 97 complete twin pairs. |
| PSS009063 | — | — | 4,032 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009071 | — | — | 4,070 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009072 | — | — | 4,062 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009073 | — | — | 3,729 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011398 | ICD-9-CM codes 362.51 or 362.52; ICD-10-CM codes H35.31 or H35.32 | — | [ ,
97.0 % Male samples |
— | European | — | MVP | — |
| PSS009075 | — | — | 4,011 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009076 | — | — | 4,112 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009077 | — | — | 4,055 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009078 | — | — | 4,043 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009089 | — | — | 4,121 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009090 | — | — | 4,046 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS012317 | — | — | [ ,
46.0 % Male samples |
— | African American or Afro-Caribbean, European, Hispanic or Latin American | 92% European and 8% non-European ancestry (African-American/African-Caribbean and Latin American) | PCL | — |
| PSS012318 | — | — | [ ,
62.0 % Male samples |
— | Not reported | — | NR | — |