| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0006335 |
| Description | The blood pressure during the contraction of the left ventricle of the heart. | Trait category |
Cardiovascular measurement
|
| Synonyms |
2 synonyms
|
| Mapped terms |
3 mapped terms
|
| 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) |
|---|---|---|---|---|---|---|
| PGS000301 (GRS970_SBP) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Systolic blood pressure | systolic blood pressure | 970 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000301/ScoringFiles/PGS000301.txt.gz |
| PGS000900 (PRS_SBP_f) |
PGP000233 | Kauko A et al. Hypertension (2021) |
Systolic blood pressure (female) | systolic blood pressure, female |
1,098,015 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000900/ScoringFiles/PGS000900.txt.gz |
| PGS000901 (PRS_SBP_m) |
PGP000233 | Kauko A et al. Hypertension (2021) |
Systolic blood pressure (male) | systolic blood pressure, male |
1,098,015 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000901/ScoringFiles/PGS000901.txt.gz |
| PGS000913 (ukb_sbp_prs) |
PGP000240 | Vaura F et al. Hypertension (2021) |
Systolic blood pressure | systolic blood pressure | 1,098,015 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000913/ScoringFiles/PGS000913.txt.gz |
| PGS001134 (GBE_INI4080) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Systolic BP (AR) | systolic blood pressure | 15,481 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001134/ScoringFiles/PGS001134.txt.gz |
| PGS002009 (portability-PLR_systolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Systolic blood pressure, automated reading | systolic blood pressure | 68,449 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002009/ScoringFiles/PGS002009.txt.gz |
| PGS002228 (portability-ldpred2_systolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Systolic blood pressure, automated reading | systolic blood pressure | 937,030 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002228/ScoringFiles/PGS002228.txt.gz |
| PGS002238 (SBP_PRS) |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Systolic blood pressure | systolic blood pressure | 1,119,444 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002238/ScoringFiles/PGS002238.txt.gz | |
| PGS002257 (GRS901_SBP) |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Systolic blood pressure | systolic blood pressure | 884 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002257/ScoringFiles/PGS002257.txt.gz |
| PGS002275 (SBP-PRS) |
PGP000303 | Groenland EH et al. Atherosclerosis (2022) |
Systolic blood pressure | systolic blood pressure | 425 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002275/ScoringFiles/PGS002275.txt.gz |
| PGS002349 (bp_SYSTOLICadjMEDz.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002349/ScoringFiles/PGS002349.txt.gz |
| PGS002376 (bp_SYSTOLICadjMEDz.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 920,928 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002376/ScoringFiles/PGS002376.txt.gz |
| PGS002421 (bp_SYSTOLICadjMEDz.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 11,737 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002421/ScoringFiles/PGS002421.txt.gz |
| PGS002470 (bp_SYSTOLICadjMEDz.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 32,439 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002470/ScoringFiles/PGS002470.txt.gz |
| PGS002519 (bp_SYSTOLICadjMEDz.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 139,179 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002519/ScoringFiles/PGS002519.txt.gz |
| PGS002568 (bp_SYSTOLICadjMEDz.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 3,510 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002568/ScoringFiles/PGS002568.txt.gz |
| PGS002617 (bp_SYSTOLICadjMEDz.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 2,060 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002617/ScoringFiles/PGS002617.txt.gz |
| PGS002666 (bp_SYSTOLICadjMEDz.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 548,088 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002666/ScoringFiles/PGS002666.txt.gz |
| PGS002715 (bp_SYSTOLICadjMEDz.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Systolic blood pressure | systolic blood pressure | 985,820 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002715/ScoringFiles/PGS002715.txt.gz |
| PGS002734 (GRS_SBP_362) |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Systolic blood pressure | systolic blood pressure | 362 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002734/ScoringFiles/PGS002734.txt.gz |
| PGS002807 (PRSCS_SBP) |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Systolic blood pressure | systolic blood pressure | 1,084,157 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002807/ScoringFiles/PGS002807.txt.gz |
| PGS003069 (ExPRSweb_SBP_4080-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 775,138 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003069/ScoringFiles/PGS003069.txt.gz | |
| PGS003070 (ExPRSweb_SBP_4080-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 24,765 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003070/ScoringFiles/PGS003070.txt.gz | |
| PGS003071 (ExPRSweb_SBP_4080-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 41,867 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003071/ScoringFiles/PGS003071.txt.gz | |
| PGS003072 (ExPRSweb_SBP_4080-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 7,477,086 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003072/ScoringFiles/PGS003072.txt.gz | |
| PGS003073 (ExPRSweb_SBP_4080-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 1,113,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003073/ScoringFiles/PGS003073.txt.gz | |
| PGS003074 (ExPRSweb_SBP_4080-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 730,914 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003074/ScoringFiles/PGS003074.txt.gz | |
| PGS003075 (ExPRSweb_SBP_4080-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 16,283 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003075/ScoringFiles/PGS003075.txt.gz | |
| PGS003076 (ExPRSweb_SBP_4080-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 25,673 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003076/ScoringFiles/PGS003076.txt.gz | |
| PGS003077 (ExPRSweb_SBP_4080-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 7,477,072 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003077/ScoringFiles/PGS003077.txt.gz | |
| PGS003078 (ExPRSweb_SBP_4080-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 1,113,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003078/ScoringFiles/PGS003078.txt.gz | |
| PGS003079 (ExPRSweb_SBP_93-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 354,112 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003079/ScoringFiles/PGS003079.txt.gz | |
| PGS003080 (ExPRSweb_SBP_93-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 11,085 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003080/ScoringFiles/PGS003080.txt.gz | |
| PGS003081 (ExPRSweb_SBP_93-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 22,519 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003081/ScoringFiles/PGS003081.txt.gz | |
| PGS003082 (ExPRSweb_SBP_93-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 6,341,932 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003082/ScoringFiles/PGS003082.txt.gz | |
| PGS003083 (ExPRSweb_SBP_93-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 1,113,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003083/ScoringFiles/PGS003083.txt.gz | |
| PGS003084 (ExPRSweb_SBP_93-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 353,555 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003084/ScoringFiles/PGS003084.txt.gz | |
| PGS003085 (ExPRSweb_SBP_93-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 13,447 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003085/ScoringFiles/PGS003085.txt.gz | |
| PGS003086 (ExPRSweb_SBP_93-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 27,471 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003086/ScoringFiles/PGS003086.txt.gz | |
| PGS003087 (ExPRSweb_SBP_93-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 6,762,103 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003087/ScoringFiles/PGS003087.txt.gz | |
| PGS003088 (ExPRSweb_SBP_93-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Systolic blood pressure | systolic blood pressure | 1,113,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003088/ScoringFiles/PGS003088.txt.gz | |
| PGS003571 (cont-decay-systolic_BP) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Systolic blood pressure, automated reading | systolic blood pressure | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003571/ScoringFiles/PGS003571.txt.gz |
| PGS003588 (SBP) |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Systolic blood pressure | systolic blood pressure | 1,064,898 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003588/ScoringFiles/PGS003588.txt.gz | |
| PGS003882 (SBP_PRScs_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Systolic blood pressure | systolic blood pressure | 1,056,790 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003882/ScoringFiles/PGS003882.txt.gz |
| PGS003965 (SBP_AFR) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Systolic blood pressure | systolic blood pressure | 1,221,464 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003965/ScoringFiles/PGS003965.txt.gz |
| PGS003966 (SBP_EAS) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Systolic blood pressure | systolic blood pressure | 978,280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003966/ScoringFiles/PGS003966.txt.gz |
| PGS003967 (SBP_EUR) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Systolic blood pressure | systolic blood pressure | 1,108,368 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003967/ScoringFiles/PGS003967.txt.gz |
| PGS003968 (SBP_weightedPRSsum) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Systolic blood pressure | systolic blood pressure | 1,267,240 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003968/ScoringFiles/PGS003968.txt.gz | |
| PGS003970 (HARE_META_SBP_PRS_MALE) |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Systolic blood pressure | systolic blood pressure | 1,115,602 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003970/ScoringFiles/PGS003970.txt.gz | |
| PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Systolic blood pressure | systolic blood pressure | 1,115,520 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003971/ScoringFiles/PGS003971.txt.gz | |
| PGS004231 (PRS732_SBP) |
PGP000529 | Acosta JN et al. Neurology (2023) |
Systolic blood pressure | systolic blood pressure | 732 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004231/ScoringFiles/PGS004231.txt.gz |
| PGS004235 (SBP_MVP) |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Systolic blood pressure | systolic blood pressure | 24,807 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004235/ScoringFiles/PGS004235.txt.gz | |
| PGS004372 (X4080.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Systolic blood pressure, automated reading | systolic blood pressure | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004372/ScoringFiles/PGS004372.txt.gz |
| PGS004594 (ukb.sbp.female) |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Systolic blood pressure | systolic blood pressure | 1,097,355 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004594/ScoringFiles/PGS004594.txt.gz |
| PGS004603 (SBP-meta-analysis) |
PGP000581 | Keaton JM et al. Nat Genet (2024) |
Systolic blood pressure | systolic blood pressure | 7,356,519 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004603/ScoringFiles/PGS004603.txt.gz |
| PGS004829 (sbp_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Systolic blood pressure | systolic blood pressure | 1,194,211 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004829/ScoringFiles/PGS004829.txt.gz |
| PGS004830 (sbp_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Systolic blood pressure | systolic blood pressure | 4,805,129 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004830/ScoringFiles/PGS004830.txt.gz |
| PGS004831 (sbp_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Systolic blood pressure | systolic blood pressure | 3,827,774 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004831/ScoringFiles/PGS004831.txt.gz |
| PGS004832 (sbp_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Systolic blood pressure | systolic blood pressure | 6,013,177 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004832/ScoringFiles/PGS004832.txt.gz |
| PGS005008 (mean_Systolic_INT_ldpred_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005008/ScoringFiles/PGS005008.txt.gz |
| PGS005009 (mean_Systolic_INT_ldpred_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005009/ScoringFiles/PGS005009.txt.gz |
| PGS005010 (mean_Systolic_INT_ldpred_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005010/ScoringFiles/PGS005010.txt.gz |
| PGS005011 (mean_Systolic_INT_ldpred_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005011/ScoringFiles/PGS005011.txt.gz |
| PGS005012 (mean_Systolic_INT_ldpred_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005012/ScoringFiles/PGS005012.txt.gz |
| PGS005013 (mean_Systolic_INT_ldpred_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005013/ScoringFiles/PGS005013.txt.gz |
| PGS005014 (mean_Systolic_INT_prscs_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005014/ScoringFiles/PGS005014.txt.gz |
| PGS005015 (mean_Systolic_INT_prscs_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005015/ScoringFiles/PGS005015.txt.gz |
| PGS005016 (mean_Systolic_INT_prscs_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005016/ScoringFiles/PGS005016.txt.gz |
| PGS005017 (mean_Systolic_INT_prscs_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005017/ScoringFiles/PGS005017.txt.gz |
| PGS005018 (mean_Systolic_INT_prscs_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005018/ScoringFiles/PGS005018.txt.gz |
| PGS005019 (mean_Systolic_INT_prscs_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005019/ScoringFiles/PGS005019.txt.gz |
| PGS005020 (mean_Systolic_INT_prscsx_METAweight) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Systolic blood pressure | systolic blood pressure | 1,277,825 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005020/ScoringFiles/PGS005020.txt.gz |
| PGS005120 (PGS_Teixeira_2024_SBP) |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Systolic blood pressure | systolic blood pressure | 944,279 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005120/ScoringFiles/PGS005120.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000801 | PGS000301 (GRS970_SBP) |
PSS000371| European Ancestry| 288 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Systolic blood pressure (mmHg) | — | — | R²: 0.012 | Sex, age, age^2, BMI | — |
| PPM000771 | PGS000301 (GRS970_SBP) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Systolic blood pressure (mmHg) | — | — | R²: 0.0215 | Sex, age, age^2, BMI | — |
| PPM002648 | PGS000900 (PRS_SBP_f) |
PSS001169| European Ancestry| 123,579 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Hypertension | HR: 1.42 [1.4, 1.44] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.12 [1.99, 2.25] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002650 | PGS000900 (PRS_SBP_f) |
PSS001169| European Ancestry| 123,579 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Early-onset hypertension (< 55 years) | HR: 1.56 [1.53, 1.58] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.51 [2.32, 2.72] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002652 | PGS000900 (PRS_SBP_f) |
PSS001169| European Ancestry| 123,579 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Late-onset hypertension (> 55 years) | HR: 1.31 [1.28, 1.33] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.66 [1.5, 1.84] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002649 | PGS000901 (PRS_SBP_m) |
PSS001170| European Ancestry| 95,213 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Hypertension | HR: 1.27 [1.26, 1.29] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.8 [1.69, 1.92] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002651 | PGS000901 (PRS_SBP_m) |
PSS001170| European Ancestry| 95,213 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Early-onset hypertension (< 55 years) | HR: 1.35 [1.32, 1.37] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.1 [1.94, 2.28] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002653 | PGS000901 (PRS_SBP_m) |
PSS001170| European Ancestry| 95,213 individuals |
PGP000233 | Kauko A et al. Hypertension (2021) |
Reported Trait: Late-onset hypertension (> 55 years) | HR: 1.21 [1.19, 1.23] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.45 [1.3, 1.61] | Age as timescale, collection year, genotyping batch, PCs(1-10) | — |
| PPM002970 | PGS000913 (ukb_sbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Early onset incident hypertension (< 55 years) | HR: 1.54 [1.53, 1.56] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.62 [2.48, 2.77] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002971 | PGS000913 (ukb_sbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Late onset incident hypertension (≥55 years) | HR: 1.31 [1.29, 1.32] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.68 [1.57, 1.81] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002977 | PGS000913 (ukb_sbp_prs) |
PSS001448| European Ancestry| 218,792 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident cardiovascular disease | — | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.3 [1.22, 1.39] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002978 | PGS000913 (ukb_sbp_prs) |
PSS001447| European Ancestry| 218,792 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident coronary heart disease | HR: 1.15 [1.13, 1.17] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.33 [1.23, 1.44] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002979 | PGS000913 (ukb_sbp_prs) |
PSS001449| European Ancestry| 212,884 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident stroke | — | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.29 [1.16, 1.44] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002981 | PGS000913 (ukb_sbp_prs) |
PSS001447| European Ancestry| 218,792 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident coronary heart disease | — | C-index: 0.743 | — | Clinical atherosclerotic cardiovascular disease risk score (age, sex, total cholesterol, high density lipoprotein, antihypertensive medication, diabetes, current smoking) | — |
| PPM002982 | PGS000913 (ukb_sbp_prs) |
PSS001449| European Ancestry| 212,884 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident stroke | — | C-index: 0.732 | — | Clinical atherosclerotic cardiovascular disease risk score (age, sex, total cholesterol, high density lipoprotein, antihypertensive medication, diabetes, current smoking) | — |
| PPM002969 | PGS000913 (ukb_sbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | HR: 1.42 [1.41, 1.43] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.19 [2.1, 2.29] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002975 | PGS000913 (ukb_sbp_prs) |
PSS001450| European Ancestry| 9,906 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | — | C-index: 0.802 | — | Age, sex, systolic blood pressure, diastolic blood pressure, body mass index, diabetes, current smoking | — |
| PPM002980 | PGS000913 (ukb_sbp_prs) |
PSS001448| European Ancestry| 218,792 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.731 | — | Clinical atherosclerotic cardiovascular disease risk score (age, sex, total cholesterol, high density lipoprotein, antihypertensive medication, diabetes, current smoking) | — |
| PPM008400 | PGS001134 (GBE_INI4080) |
PSS007268| European Ancestry| 23,726 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Systolic BP (AR) | — | — | R²: 0.19444 [0.18561, 0.20326] Incremental R2 (full-covars): 0.04167 PGS R2 (no covariates): 0.04458 [0.03957, 0.04959] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008399 | PGS001134 (GBE_INI4080) |
PSS007267| East Asian Ancestry| 1,634 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Systolic BP (AR) | — | — | R²: 0.22915 [0.19418, 0.26412] Incremental R2 (full-covars): 0.03474 PGS R2 (no covariates): 0.04463 [0.0255, 0.06375] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008401 | PGS001134 (GBE_INI4080) |
PSS007269| South Asian Ancestry| 7,640 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Systolic BP (AR) | — | — | R²: 0.15314 [0.13847, 0.16782] Incremental R2 (full-covars): 0.02459 PGS R2 (no covariates): 0.0236 [0.01696, 0.03024] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008398 | PGS001134 (GBE_INI4080) |
PSS007266| African Ancestry| 6,409 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Systolic BP (AR) | — | — | R²: 0.1028 [0.08882, 0.11678] Incremental R2 (full-covars): 0.00145 PGS R2 (no covariates): 0.00628 [0.00245, 0.01011] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008402 | PGS001134 (GBE_INI4080) |
PSS007270| European Ancestry| 63,823 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Systolic BP (AR) | — | — | R²: 0.17232 [0.16713, 0.17751] Incremental R2 (full-covars): 0.04845 PGS R2 (no covariates): 0.04834 [0.04519, 0.0515] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010946 | PGS002009 (portability-PLR_systolic_BP) |
PSS009494| European Ancestry| 18,717 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2548 [0.2414, 0.2682] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010947 | PGS002009 (portability-PLR_systolic_BP) |
PSS009268| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2702 [0.2409, 0.299] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010948 | PGS002009 (portability-PLR_systolic_BP) |
PSS008822| European Ancestry| 6,337 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2197 [0.1961, 0.243] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010949 | PGS002009 (portability-PLR_systolic_BP) |
PSS008596| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2284 [0.1724, 0.2829] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010950 | PGS002009 (portability-PLR_systolic_BP) |
PSS008374| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1877 [0.1633, 0.2118] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010951 | PGS002009 (portability-PLR_systolic_BP) |
PSS008150| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2163 [0.1705, 0.2612] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010953 | PGS002009 (portability-PLR_systolic_BP) |
PSS009042| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1046 [0.0732, 0.1358] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010952 | PGS002009 (portability-PLR_systolic_BP) |
PSS007938| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.104 [0.0644, 0.1433] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM020890 | PGS002009 (portability-PLR_systolic_BP) |
PSS011442| European Ancestry| 564 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 0.92 [0.77, 1.11] | — | — | — | — |
| PPM020895 | PGS002009 (portability-PLR_systolic_BP) |
PSS011441| African Ancestry| 504 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 1.06 [0.86, 1.31] | — | — | — | — |
| PPM012670 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS009494| European Ancestry| 18,717 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2585 [0.2451, 0.2718] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012671 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS009268| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2775 [0.2483, 0.3061] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012672 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS008822| European Ancestry| 6,337 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2265 [0.203, 0.2498] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012673 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS008596| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2233 [0.1672, 0.278] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012674 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS008374| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1982 [0.1739, 0.2222] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012675 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS008150| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.198 [0.1519, 0.2433] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012676 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS007938| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0959 [0.0563, 0.1353] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012677 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS009042| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Systolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0994 [0.0679, 0.1306] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM022516 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011983| European Ancestry| 8,250 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to antihypertensives (absolute difference) | β: -0.456 (0.18) | — | — | sex, age and drug-specific covariates | beta unit = mmHg |
| PPM022517 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011983| European Ancestry| 8,250 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to antihypertensives (relative logarithmic difference) | β: -0.153 (0.121) | — | — | sex, age and drug-specific covariates | beta unit = % |
| PPM022518 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011979| European Ancestry| 5,034 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to ACEi (absolute difference) | β: -0.557 (0.227) | — | — | sex, age and drug-specific covariates | beta unit = mmHg |
| PPM022519 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011979| European Ancestry| 5,034 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to ACEi (relative logarithmic difference) | β: -0.208 (0.153) | — | — | sex, age and drug-specific covariates | beta unit = % |
| PPM022520 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011981| European Ancestry| 932 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to CCB (absolute difference) | β: -0.826 (0.595) | — | — | sex, age and drug-specific covariates | beta unit = mmHg |
| PPM022521 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011981| European Ancestry| 932 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to CCB (relative logarithmic difference) | β: -0.331 (0.392) | — | — | sex, age and drug-specific covariates | beta unit = % |
| PPM022522 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011982| European Ancestry| 2,145 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to diuretics (absolute difference) | β: -0.289 (0.343) | — | — | sex, age and drug-specific covariates | beta unit = mmHg |
| PPM022523 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011982| European Ancestry| 2,145 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to diuretics (relative logarithmic difference) | β: -0.102 (0.228) | — | — | sex, age and drug-specific covariates | beta unit = % |
| PPM022524 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011980| European Ancestry| 1,750 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to beta blockers (absolute difference) | β: -0.094 (0.415) | — | — | sex, age and drug-specific covariates | beta unit = mmHg |
| PPM022525 | PGS002228 (portability-ldpred2_systolic_BP) |
PSS011980| European Ancestry| 1,750 individuals |
PGP000721 | Sadler MC et al. Nat Commun (2025) |Ext. |
Reported Trait: SBP response to beta blockers (relative logarithmic difference) | β: 0.068 (0.284) | — | — | sex, age and drug-specific covariates | beta unit = % |
| PPM012729 | PGS002238 (SBP_PRS) |
PSS009511| African Ancestry| 10,052 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.05 [0.95, 1.17] | AUROC: 0.666 [0.637, 0.683] | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012730 | PGS002238 (SBP_PRS) |
PSS009512| European Ancestry| 57,090 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.11 [1.06, 1.17] | AUROC: 0.68 [0.669, 0.689] | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012731 | PGS002238 (SBP_PRS) |
PSS009510| Ancestry Not Reported| 4,407 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.1 [1.05, 1.15] | AUROC: 0.682 [0.67, 0.687] | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012835 | PGS002257 (GRS901_SBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.06 [1.79, 2.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012836 | PGS002257 (GRS901_SBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.64 [1.46, 1.81] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012837 | PGS002257 (GRS901_SBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.42 [0.25, 0.58] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012838 | PGS002257 (GRS901_SBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.27 [1.23, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012839 | PGS002257 (GRS901_SBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.38 [1.85, 2.9] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012840 | PGS002257 (GRS901_SBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.39 [1.09, 1.7] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012841 | PGS002257 (GRS901_SBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.99 [0.65, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012842 | PGS002257 (GRS901_SBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.26 [1.2, 1.33] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012843 | PGS002257 (GRS901_SBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.58 [2.13, 3.03] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012844 | PGS002257 (GRS901_SBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.49 [1.25, 1.74] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012845 | PGS002257 (GRS901_SBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 1.09 [0.8, 1.39] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012846 | PGS002257 (GRS901_SBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.3 [1.24, 1.36] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012863 | PGS002257 (GRS901_SBP) |
PSS009584| European Ancestry| 55,439 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Uncontrolled hypertension | — | — | Odds Ratio (OR, top vs. bottom quintile): 1.7 [1.6, 1.8] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), number of antihypertensives and the first four principal components of genetic ancestry, genotyping array and LDL-C value at baseline | 881 SNPs remained after QC |
| PPM012864 | PGS002257 (GRS901_SBP) |
PSS009581| European Ancestry| 55,439 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident major adverse cardiovascular events in hypertension treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 1.13 [1.04, 1.23] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), number of antihypertensives and the first four principal components of genetic ancestry, genotyping array and LDL-C value at baseline | 881 SNPs remained after QC |
| PPM012865 | PGS002257 (GRS901_SBP) |
PSS009582| European Ancestry| 55,439 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident myocardial infarction in hypertension treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 1.08 [0.97, 1.2] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), number of antihypertensives and the first four principal components of genetic ancestry, genotyping array and LDL-C value at baseline | 881 SNPs remained after QC |
| PPM012866 | PGS002257 (GRS901_SBP) |
PSS009583| European Ancestry| 55,439 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident stroke in hypertension treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 1.22 [1.06, 1.41] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), number of antihypertensives and the first four principal components of genetic ancestry, genotyping array and LDL-C value at baseline | 881 SNPs remained after QC |
| PPM013002 | PGS002257 (GRS901_SBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Diastolic blood pressure | β: 0.65 | — | — | PGS002258, age, age^2, sex, BMI, randomization arm, history of CVD event, serum creatinine, fasting blood glucose, LDL levels, 10 genetic PCs | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM013003 | PGS002257 (GRS901_SBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Adverse cardiovascular events | HR: 1.12 [1.02, 1.23] | — | — | PGS002258 | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM013001 | PGS002257 (GRS901_SBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Systolic blood pressure | β: 1.93 | — | — | PGS002258, age, age^2, sex, BMI, randomization arm, history of CVD event, serum creatinine, fasting blood glucose, LDL levels, 10 genetic PCs | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM015498 | PGS002257 (GRS901_SBP) |
PSS009963| European Ancestry| 33,770 individuals |
PGP000376 | Åberg F et al. Sci Rep (2022) |Ext. |
Reported Trait: Liver-related outcome | HR: 1.19 [1.01, 1.24] | — | — | Age, sex, body mass index, waist circumference, weekly alcohol use, fraction of alcohol use as wine, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, diabetes, exercise habits, smoking status (current, former, never smoker) and baseline cardiovascular disease | — |
| PPM020416 | PGS002257 (GRS901_SBP) |
PSS011352| Multi-ancestry (including European)| 23,030 individuals |
PGP000550 | Li C et al. J Glob Health (2023) |Ext. |
Reported Trait: Incident diabetic retinopathy | — | — | Hazard ratio (HR, high vs low PRS tertile): 1.48 [1.21, 1.82] | Age, sex, body mass index, ethnicity, Townsend index, smoking status, alcohol consumption, glycosylated haemoglobin, duration of diabetes, anti-hyperglycaemic medication, anti-hypertensive medication, low-density lipoprotein cholesterol | — |
| PPM020417 | PGS002257 (GRS901_SBP) |
PSS011352| Multi-ancestry (including European)| 23,030 individuals |
PGP000550 | Li C et al. J Glob Health (2023) |Ext. |
Reported Trait: Incident diabetic kidney disease | — | — | Hazard ratio (HR, high vs low PRS tertile): 2.8 [1.57, 4.98] | Age, sex, body mass index, ethnicity, Townsend index, smoking status, alcohol consumption, glycosylated haemoglobin, duration of diabetes, anti-hyperglycaemic medication, anti-hypertensive medication, estimated glomerular filtration rate | — |
| PPM020418 | PGS002257 (GRS901_SBP) |
PSS011352| Multi-ancestry (including European)| 23,030 individuals |
PGP000550 | Li C et al. J Glob Health (2023) |Ext. |
Reported Trait: Incident diabetic neuropathy | — | — | Hazard ratio (HR, high vs low PRS tertile): 1.04 [0.77, 1.42] | Age, sex, body mass index, ethnicity, Townsend index, smoking status, alcohol consumption, glycosylated haemoglobin, duration of diabetes, anti-hyperglycaemic medication, anti-hypertensive medication, estimated glomerular filtration rate | — |
| PPM020415 | PGS002257 (GRS901_SBP) |
PSS011352| Multi-ancestry (including European)| 23,030 individuals |
PGP000550 | Li C et al. J Glob Health (2023) |Ext. |
Reported Trait: Incident diabetic microvascular complications | — | — | Hazard ratio (HR, high vs low PRS tertile): 1.32 [1.11, 1.56] | Age, sex, body mass index, ethnicity, Townsend index, smoking status, alcohol consumption, glycosylated haemoglobin, duration of diabetes, anti-hyperglycaemic medication, anti-hypertensive medication, low-density lipoprotein cholesterol and estimated glomerular filtration rate | — |
| PPM012945 | PGS002275 (SBP-PRS) |
PSS009627| European Ancestry| 4,416 individuals |
PGP000303 | Groenland EH et al. Atherosclerosis (2022) |
Reported Trait: Systolic blood pressure | β: 3.19 [2.6, 3.78] | — | — | Age, sex, the first 5 principal components, BMI, T2DM, smoking, alcohol use, LDL-cholesterol, eGFR, triglycerides, antihypertensive medication | — |
| PPM013114 | PGS002349 (bp_SYSTOLICadjMEDz.BOLT-LMM) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0236 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013163 | PGS002349 (bp_SYSTOLICadjMEDz.BOLT-LMM) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.07 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013212 | PGS002349 (bp_SYSTOLICadjMEDz.BOLT-LMM) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.106 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013261 | PGS002349 (bp_SYSTOLICadjMEDz.BOLT-LMM) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0691 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013288 | PGS002376 (bp_SYSTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013311 | PGS002376 (bp_SYSTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0426 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013334 | PGS002376 (bp_SYSTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0016 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013357 | PGS002376 (bp_SYSTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0019 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013402 | PGS002421 (bp_SYSTOLICadjMEDz.P+T.0.0001) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013451 | PGS002421 (bp_SYSTOLICadjMEDz.P+T.0.0001) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0346 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013500 | PGS002421 (bp_SYSTOLICadjMEDz.P+T.0.0001) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0377 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013549 | PGS002421 (bp_SYSTOLICadjMEDz.P+T.0.0001) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0187 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013598 | PGS002470 (bp_SYSTOLICadjMEDz.P+T.0.001) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013647 | PGS002470 (bp_SYSTOLICadjMEDz.P+T.0.001) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0078 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013696 | PGS002470 (bp_SYSTOLICadjMEDz.P+T.0.001) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0305 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013745 | PGS002470 (bp_SYSTOLICadjMEDz.P+T.0.001) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0106 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013794 | PGS002519 (bp_SYSTOLICadjMEDz.P+T.0.01) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013843 | PGS002519 (bp_SYSTOLICadjMEDz.P+T.0.01) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0042 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013892 | PGS002519 (bp_SYSTOLICadjMEDz.P+T.0.01) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0151 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013941 | PGS002519 (bp_SYSTOLICadjMEDz.P+T.0.01) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0037 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013990 | PGS002568 (bp_SYSTOLICadjMEDz.P+T.1e-06) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0076 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014088 | PGS002568 (bp_SYSTOLICadjMEDz.P+T.1e-06) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0271 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014137 | PGS002568 (bp_SYSTOLICadjMEDz.P+T.1e-06) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0132 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014039 | PGS002568 (bp_SYSTOLICadjMEDz.P+T.1e-06) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.031 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014186 | PGS002617 (bp_SYSTOLICadjMEDz.P+T.5e-08) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0079 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014235 | PGS002617 (bp_SYSTOLICadjMEDz.P+T.5e-08) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0269 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014284 | PGS002617 (bp_SYSTOLICadjMEDz.P+T.5e-08) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.022 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014333 | PGS002617 (bp_SYSTOLICadjMEDz.P+T.5e-08) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.011 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014382 | PGS002666 (bp_SYSTOLICadjMEDz.PolyFun-pred) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0256 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_SYSTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014431 | PGS002666 (bp_SYSTOLICadjMEDz.PolyFun-pred) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0819 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_SYSTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014480 | PGS002666 (bp_SYSTOLICadjMEDz.PolyFun-pred) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1129 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_SYSTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014529 | PGS002666 (bp_SYSTOLICadjMEDz.PolyFun-pred) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0723 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_SYSTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014578 | PGS002715 (bp_SYSTOLICadjMEDz.SBayesR) |
PSS009839| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0236 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014627 | PGS002715 (bp_SYSTOLICadjMEDz.SBayesR) |
PSS009840| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0629 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014676 | PGS002715 (bp_SYSTOLICadjMEDz.SBayesR) |
PSS009841| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.103 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014725 | PGS002715 (bp_SYSTOLICadjMEDz.SBayesR) |
PSS009842| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Systolic Blood Pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0668 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014825 | PGS002734 (GRS_SBP_362) |
PSS009904| Ancestry Not Reported| 2,944 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels untreated for hypertension | — | — | Correlation: 0.062 [0.026, 0.098] | — | — |
| PPM014826 | PGS002734 (GRS_SBP_362) |
PSS009905| Ancestry Not Reported| 2,541 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels untreated for hypertension | — | — | Correlation: 0.783 [0.488, 1.079] | — | — |
| PPM014827 | PGS002734 (GRS_SBP_362) |
PSS009906| Ancestry Not Reported| 1,920 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels untreated for hypertension | — | — | Correlation: 0.05 [0.003, 0.096] | — | — |
| PPM014828 | PGS002734 (GRS_SBP_362) |
PSS009903| Ancestry Not Reported| 4,333 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels treated for hypertension | — | — | Correlation: 0.054 [-0.006, 0.113] | — | — |
| PPM014829 | PGS002734 (GRS_SBP_362) |
PSS009904| Ancestry Not Reported| 2,944 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels treated for hypertension | — | — | Correlation: 0.045 [-0.011, 0.102] | — | — |
| PPM014830 | PGS002734 (GRS_SBP_362) |
PSS009905| Ancestry Not Reported| 2,541 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels treated for hypertension | — | — | Correlation: 0.05 [-0.012, 0.111] | — | — |
| PPM014831 | PGS002734 (GRS_SBP_362) |
PSS009906| Ancestry Not Reported| 1,920 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels treated for hypertension | — | — | Correlation: 0.066 [-0.001, 0.133] | — | — |
| PPM014824 | PGS002734 (GRS_SBP_362) |
PSS009903| Ancestry Not Reported| 4,333 individuals |
PGP000343 | Marques-Vidal P et al. J Hypertens (2022) |
Reported Trait: Systolic blood pressure levels untreated for hypertension | — | — | Correlation: 0.086 [0.058, 0.115] | — | — |
| PPM015554 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CVD events | HR: 1.1 [1.03, 1.17] | C-index: 0.58 | — | — | — |
| PPM015562 | PGS002807 (PRSCS_SBP) |
PSS009982| Multi-ancestry (including European)| 44,098 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Hypertension | OR: 1.28 [1.25, 1.3] | — | R²: 0.10982 | — | — |
| PPM015539 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Diastolic blood pressure | β: 2.04 [1.89, 2.19] | — | R²: 0.12136 | — | — |
| PPM015549 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Diastolic blood pressure | β: 1.07 [0.78, 1.36] | — | R²: 0.05373 | — | — |
| PPM015550 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Mean arterial pressure | β: 1.71 [1.39, 2.04] | — | R²: 0.02742 | — | — |
| PPM015540 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Mean arterial pressure | β: 2.82 [2.65, 3.0] | — | R²: 0.15868 | — | — |
| PPM015541 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Pulse pressure | β: 2.35 [2.17, 2.53] | — | R²: 0.31658 | — | — |
| PPM015542 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Hypertension | OR: 1.51 [1.46, 1.55] | — | R²: 0.21395 | — | — |
| PPM015543 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident ASCVD events | HR: 1.05 [1.02, 1.08] | C-index: 0.77 | — | — | — |
| PPM015544 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CVD events | HR: 1.06 [1.03, 1.09] | C-index: 0.76 | — | — | — |
| PPM015545 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CHF events | HR: 1.04 [1.0, 1.09] | C-index: 0.83 | — | — | — |
| PPM015547 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident stroke events | HR: 1.04 [1.0, 1.09] | C-index: 0.76 | — | — | — |
| PPM015548 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Systolic blood pressure | β: 2.33 [1.9, 2.75] | — | R²: 0.03615 | — | — |
| PPM015551 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Pulse pressure | β: 1.94 [1.58, 2.3] | — | R²: 0.1185 | — | — |
| PPM015552 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Hypertension | OR: 1.51 [1.39, 1.64] | — | R²: 0.04804 | — | — |
| PPM015553 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident ASCVD events | HR: 1.13 [1.06, 1.19] | C-index: 0.59 | — | — | — |
| PPM015555 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CHF events | HR: 1.18 [1.06, 1.3] | C-index: 0.65 | — | — | — |
| PPM015556 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CHD events | HR: 1.1 [1.03, 1.17] | C-index: 0.58 | — | — | — |
| PPM015557 | PGS002807 (PRSCS_SBP) |
PSS009981| Multi-ancestry (including European)| 6,335 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident stroke events | HR: 1.15 [0.96, 1.34] | C-index: 0.69 | — | — | — |
| PPM015558 | PGS002807 (PRSCS_SBP) |
PSS009982| Multi-ancestry (including European)| 44,098 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Systolic blood pressure | β: 2.96 [2.79, 3.12] | — | R²: 0.16035 | — | — |
| PPM015559 | PGS002807 (PRSCS_SBP) |
PSS009982| Multi-ancestry (including European)| 44,098 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Diastolic blood pressure | β: 1.43 [1.32, 1.54] | — | R²: 0.05359 | — | — |
| PPM015560 | PGS002807 (PRSCS_SBP) |
PSS009982| Multi-ancestry (including European)| 44,098 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Mean arterial pressure | β: 1.94 [1.82, 2.06] | — | R²: 0.08936 | — | — |
| PPM015561 | PGS002807 (PRSCS_SBP) |
PSS009982| Multi-ancestry (including European)| 44,098 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Pulse pressure | β: 1.53 [1.41, 1.64] | — | R²: 0.21397 | — | — |
| PPM015538 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Systolic blood pressure | β: 4.39 [4.13, 4.65] | — | R²: 0.23786 | — | — |
| PPM015546 | PGS002807 (PRSCS_SBP) |
PSS009980| Multi-ancestry (including European)| 21,883 individuals |
PGP000384 | Parcha V et al. Circ Genom Precis Med (2022) |
Reported Trait: Incident CHD events | HR: 1.07 [1.04, 1.11] | C-index: 0.77 | — | — | — |
| PPM015933 | PGS003069 (ExPRSweb_SBP_4080-irnt_LASSOSUM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.26 (0.0794) | — | R²: 0.0285 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015936 | PGS003070 (ExPRSweb_SBP_4080-irnt_PT_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.15 (0.0809) | — | R²: 0.0246 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015934 | PGS003071 (ExPRSweb_SBP_4080-irnt_PLINK_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 1.8 (0.0806) | — | R²: 0.0179 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015932 | PGS003072 (ExPRSweb_SBP_4080-irnt_DBSLMM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.03 (0.0795) | — | R²: 0.0236 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015935 | PGS003073 (ExPRSweb_SBP_4080-irnt_PRSCS_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.34 (0.0798) | — | R²: 0.0297 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015938 | PGS003074 (ExPRSweb_SBP_4080-raw_LASSOSUM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.22 (0.0793) | — | R²: 0.0277 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015941 | PGS003075 (ExPRSweb_SBP_4080-raw_PT_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.12 (0.0814) | — | R²: 0.0234 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015939 | PGS003076 (ExPRSweb_SBP_4080-raw_PLINK_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 1.79 (0.0805) | — | R²: 0.0183 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015937 | PGS003077 (ExPRSweb_SBP_4080-raw_DBSLMM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 1.99 (0.0799) | — | R²: 0.0224 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015940 | PGS003078 (ExPRSweb_SBP_4080-raw_PRSCS_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 2.33 (0.08) | — | R²: 0.0295 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015943 | PGS003079 (ExPRSweb_SBP_93-irnt_LASSOSUM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.622 (0.0788) | — | R²: 0.00238 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015946 | PGS003080 (ExPRSweb_SBP_93-irnt_PT_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.609 (0.0788) | — | R²: 0.0024 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015944 | PGS003081 (ExPRSweb_SBP_93-irnt_PLINK_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.507 (0.0806) | — | R²: 0.00175 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015942 | PGS003082 (ExPRSweb_SBP_93-irnt_DBSLMM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.383 (0.0789) | — | R²: 0.00106 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015945 | PGS003083 (ExPRSweb_SBP_93-irnt_PRSCS_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.848 (0.0794) | — | R²: 0.00432 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015948 | PGS003084 (ExPRSweb_SBP_93-raw_LASSOSUM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.642 (0.0788) | — | R²: 0.00251 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015951 | PGS003085 (ExPRSweb_SBP_93-raw_PT_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.557 (0.0788) | — | R²: 0.00188 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015949 | PGS003086 (ExPRSweb_SBP_93-raw_PLINK_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.464 (0.0799) | — | R²: 0.00148 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015947 | PGS003087 (ExPRSweb_SBP_93-raw_DBSLMM_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.33 (0.0788) | — | R²: 0.00076 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015950 | PGS003088 (ExPRSweb_SBP_93-raw_PRSCS_MGI_20211120) |
PSS010011| European Ancestry| 23,072 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Systolic Blood Pressure | β: 0.794 (0.0792) | — | R²: 0.00358 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM017499 | PGS003571 (cont-decay-systolic_BP) |
PSS010939| European Ancestry| 18,679 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
| PPM017583 | PGS003571 (cont-decay-systolic_BP) |
PSS010855| European Ancestry| 3,920 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
| PPM017667 | PGS003571 (cont-decay-systolic_BP) |
PSS010687| European Ancestry| 6,181 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM017751 | PGS003571 (cont-decay-systolic_BP) |
PSS010603| Greater Middle Eastern Ancestry| 1,122 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM017919 | PGS003571 (cont-decay-systolic_BP) |
PSS010519| South Asian Ancestry| 6,050 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.04 | sex, age, deprivation index, PC1-16 | — |
| PPM018003 | PGS003571 (cont-decay-systolic_BP) |
PSS010435| East Asian Ancestry| 1,709 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM018087 | PGS003571 (cont-decay-systolic_BP) |
PSS010351| African Ancestry| 2,424 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.01 | sex, age, deprivation index, PC1-16 | — |
| PPM018171 | PGS003571 (cont-decay-systolic_BP) |
PSS010771| African Ancestry| 3,819 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.01 | sex, age, deprivation index, PC1-16 | — |
| PPM017835 | PGS003571 (cont-decay-systolic_BP) |
PSS010267| European Ancestry| 2,194 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Systolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM018282 | PGS003588 (SBP) |
PSS010956| European Ancestry| 25,582 individuals |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Reported Trait: Pre-eclampsia/eclampsia | OR: 1.24 [1.17, 1.3] | — | — | maternal age at delivery, age2, and the first ten principal components of genetic ancestry | — |
| PPM018774 | PGS003882 (SBP_PRScs_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Systolic blood pressure | β: 3.1 (0.44) | — | R²: 0.1108 | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM019121 | PGS003968 (SBP_weightedPRSsum) |
PSS011189| Multi-ancestry (including European)| 88,521 individuals |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Reported Trait: Systolic blood pressure | β: 3.62 [3.47, 3.77] | — | — | age, sex at birth, BMI, self-reported race/ethnicity, and the first 10 PCs of genetic data | best performing SBP PRSs as selected in the TOPMed dataset (PRS-CSx2) |
| PPM019124 | PGS003970 (HARE_META_SBP_PRS_MALE) |
PSS011192| Multi-ancestry (including European)| 84,990 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Systolic Blood Pressure | β: 1.95 (0.06) | — | R²: 0.09 | — | — |
| PPM019126 | PGS003970 (HARE_META_SBP_PRS_MALE) |
PSS011192| Multi-ancestry (including European)| 84,990 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | OR: 1.22 [1.2, 1.23] | — | R²: 0.05 | — | — |
| PPM019128 | PGS003970 (HARE_META_SBP_PRS_MALE) |
PSS011192| Multi-ancestry (including European)| 84,990 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.61 [1.46, 1.77] | age, and the first 10 principal components of genetic ancestry | — |
| PPM019130 | PGS003970 (HARE_META_SBP_PRS_MALE) |
PSS011196| Multi-ancestry (including European)| 33,632 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.47 [1.27, 1.71] | age, and the first 10 principal components of genetic ancestry | — |
| PPM019132 | PGS003970 (HARE_META_SBP_PRS_MALE) |
PSS011194| Multi-ancestry (including European)| 51,358 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.61 [1.44, 1.8] | age, and the first 10 principal components of genetic ancestry | — |
| PPM019125 | PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PSS011191| Multi-ancestry (including European)| 127,679 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Systolic Blood Pressure | β: 2.47 (0.05) | — | R²: 0.18 | — | — |
| PPM019127 | PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PSS011191| Multi-ancestry (including European)| 127,679 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | OR: 1.29 [1.27, 1.3] | — | R²: 0.11 | — | — |
| PPM019129 | PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PSS011191| Multi-ancestry (including European)| 127,679 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.81 [1.68, 1.95] | age, and the first 10 principal components of genetic ancestry | — |
| PPM019131 | PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PSS011195| Multi-ancestry (including European)| 60,049 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.71 [1.48, 1.98] | age, and the first 10 principal components of genetic ancestry | — |
| PPM019133 | PGS003971 (HARE_META_SBP_PRS_FEMALE) |
PSS011193| Multi-ancestry (including European)| 67,630 individuals |
PGP000512 | Shetty NS et al. Circ Genom Precis Med (2023) |
Reported Trait: Hypertension | — | — | Odds ratio (OR, high vs low tertile): 1.65 [1.45, 1.84] | age, and the first 10 principal components of genetic ancestry | — |
| PPM020229 | PGS004231 (PRS732_SBP) |
PSS011310| European Ancestry| 1,750 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Systolic blood pressure | — | — | Beta (beta, top PRS quintile vs bottom PRS quintile): 3.62 (1.39) | — | — |
| PPM020230 | PGS004231 (PRS732_SBP) |
PSS011310| European Ancestry| 1,750 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Resistant blood pressure | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.27 [1.3, 4.1] | — | — |
| PPM020232 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Systolic blood pressure in all stroke | — | — | Beta (beta, top PRS quintile vs bottom PRS quintile): 5.97 (0.76) | age, sex, and vascular risk factors | — |
| PPM020233 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Uncontrolled blood pressure in all stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.71 [1.45, 2.03] | age, sex, and vascular risk factors | — |
| PPM020234 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Resistant blood pressure in all stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.25 [1.59, 3.25] | age, sex, and vascular risk factors | — |
| PPM020238 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Systolic blood pressure in Ischemic stroke | — | — | Beta (beta, top PRS quintile vs bottom PRS quintile): 4.89 (1.51) | age, sex, and vascular risk factors | — |
| PPM020240 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Resistant blood pressure in Ischemic stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.65 [1.39, 5.35] | age, sex, and vascular risk factors | — |
| PPM020244 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Systolic blood pressure in Hemorrhagic stroke | — | — | Beta (beta, top PRS quintile vs bottom PRS quintile): 4.84 (1.91) | age, sex, and vascular risk factors | — |
| PPM020245 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Uncontrolled blood pressure in Hemorrhagic stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.17 [1.41, 3.36] | age, sex, and vascular risk factors | — |
| PPM020246 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Resistant blood pressure in Hemorrhagic stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.77 [0.69, 4.97] | age, sex, and vascular risk factors | — |
| PPM020239 | PGS004231 (PRS732_SBP) |
PSS011309| European Ancestry| 408,475 individuals |
PGP000529 | Acosta JN et al. Neurology (2023) |
Reported Trait: Uncontrolled blood pressure in Ischemic stroke | — | — | Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.73 [1.23, 2.43] | age, sex, and vascular risk factors | — |
| PPM020254 | PGS004235 (SBP_MVP) |
PSS011312| Multi-ancestry (including European)| 39,035 individuals |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Reported Trait: Prevelant hypertension | — | AUROC: 0.757 [0.744, 0.771] | — | sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components | — |
| PPM020487 | PGS004372 (X4080.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Systolic blood pressure, automated reading | — | — | PGS R2 (no covariates): 0.18257 | — | — |
| PPM020741 | PGS004594 (ukb.sbp.female) |
PSS011387| European Ancestry| 138,317 individuals |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Reported Trait: Gestational hypertension | HR: 1.38 [1.35, 1.41] | — | — | Collection year, genotyping batch, and the first 10 genetic principal components | — |
| PPM020742 | PGS004594 (ukb.sbp.female) |
PSS011388| European Ancestry| 136,354 individuals |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Reported Trait: Preeclampsia | HR: 1.26 [1.23, 1.29] | — | — | Collection year, genotyping batch, and the first 10 genetic principal components | — |
| PPM020761 | PGS004603 (SBP-meta-analysis) |
PSS011397| European Ancestry| 10,210 individuals |
PGP000581 | Keaton JM et al. Nat Genet (2024) |
Reported Trait: Systolic blood pressure | — | — | R²: 0.1137 beta (high vs low tertile): 16.85 |
Age, Age2, Sex, BMI | — |
| PPM020764 | PGS004603 (SBP-meta-analysis) |
PSS011396| African Ancestry| 21,843 individuals |
PGP000581 | Keaton JM et al. Nat Genet (2024) |
Reported Trait: Systolic blood pressure | — | — | beta (high vs low tertile): 10.59 | Age, Age2, Sex, BMI | — |
| PPM021054 | PGS004829 (sbp_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Systolic blood pressure | — | — | Incremental R2 (Full model versus model with only covariates): 0.037 [0.029, 0.044] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021055 | PGS004830 (sbp_PRSmix_sas) |
PSS011505| South Asian Ancestry| 7,188 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Systolic blood pressure | — | — | Incremental R2 (Full model versus model with only covariates): 0.036 [0.027, 0.044] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021056 | PGS004831 (sbp_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Systolic blood pressure | — | — | Incremental R2 (Full model versus model with only covariates): 0.043 [0.035, 0.051] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021057 | PGS004832 (sbp_PRSmixPlus_sas) |
PSS011505| South Asian Ancestry| 7,188 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Systolic blood pressure | — | — | Incremental R2 (Full model versus model with only covariates): 0.044 [0.035, 0.054] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM022151 | PGS005008 (mean_Systolic_INT_ldpred_AFRss_afrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.083 [0.07, 0.09] | — | R²: 0.008 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022157 | PGS005008 (mean_Systolic_INT_ldpred_AFRss_afrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.114 [0.1, 0.13] | — | R²: 0.015 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022163 | PGS005008 (mean_Systolic_INT_ldpred_AFRss_afrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.102 [0.09, 0.12] | — | R²: 0.013 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022153 | PGS005009 (mean_Systolic_INT_ldpred_EURss_eurld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.167 [0.16, 0.18] | — | R²: 0.032 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022159 | PGS005009 (mean_Systolic_INT_ldpred_EURss_eurld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.084 [0.07, 0.1] | — | R²: 0.008 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022165 | PGS005009 (mean_Systolic_INT_ldpred_EURss_eurld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.143 [0.13, 0.16] | — | R²: 0.026 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022152 | PGS005010 (mean_Systolic_INT_ldpred_HISss_amrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.097 [0.09, 0.11] | — | R²: 0.011 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022158 | PGS005010 (mean_Systolic_INT_ldpred_HISss_amrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.072 [0.06, 0.08] | — | R²: 0.006 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022164 | PGS005010 (mean_Systolic_INT_ldpred_HISss_amrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.122 [0.11, 0.14] | — | R²: 0.019 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022148 | PGS005011 (mean_Systolic_INT_ldpred_METAss_afrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.16 [0.15, 0.17] | — | R²: 0.03 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022154 | PGS005011 (mean_Systolic_INT_ldpred_METAss_afrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.131 [0.12, 0.14] | — | R²: 0.02 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022160 | PGS005011 (mean_Systolic_INT_ldpred_METAss_afrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.16 [0.14, 0.17] | — | R²: 0.032 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022149 | PGS005012 (mean_Systolic_INT_ldpred_METAss_amrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.184 [0.18, 0.19] | — | R²: 0.039 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022161 | PGS005012 (mean_Systolic_INT_ldpred_METAss_amrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.185 [0.17, 0.2] | — | R²: 0.043 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022155 | PGS005012 (mean_Systolic_INT_ldpred_METAss_amrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.145 [0.13, 0.16] | — | R²: 0.024 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022150 | PGS005013 (mean_Systolic_INT_ldpred_METAss_eurld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.194 [0.19, 0.2] | — | R²: 0.044 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022156 | PGS005013 (mean_Systolic_INT_ldpred_METAss_eurld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.138 [0.12, 0.15] | — | R²: 0.022 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022162 | PGS005013 (mean_Systolic_INT_ldpred_METAss_eurld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.177 [0.16, 0.19] | — | R²: 0.039 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022059 | PGS005014 (mean_Systolic_INT_prscs_AFRss_afrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.082 [0.07, 0.09] | — | R²: 0.008 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022066 | PGS005014 (mean_Systolic_INT_prscs_AFRss_afrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.098 [0.09, 0.11] | — | R²: 0.011 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022073 | PGS005014 (mean_Systolic_INT_prscs_AFRss_afrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.087 [0.07, 0.1] | — | R²: 0.009 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022068 | PGS005015 (mean_Systolic_INT_prscs_EURss_eurld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.107 [0.09, 0.12] | — | R²: 0.013 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022075 | PGS005015 (mean_Systolic_INT_prscs_EURss_eurld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.176 [0.16, 0.19] | — | R²: 0.039 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022061 | PGS005015 (mean_Systolic_INT_prscs_EURss_eurld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.191 [0.18, 0.2] | — | R²: 0.042 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022060 | PGS005016 (mean_Systolic_INT_prscs_HISss_amrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.095 [0.09, 0.1] | — | R²: 0.01 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022067 | PGS005016 (mean_Systolic_INT_prscs_HISss_amrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.066 [0.05, 0.08] | — | R²: 0.005 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022074 | PGS005016 (mean_Systolic_INT_prscs_HISss_amrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.111 [0.1, 0.13] | — | R²: 0.015 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022056 | PGS005017 (mean_Systolic_INT_prscs_METAss_afrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.128 [0.12, 0.14] | — | R²: 0.019 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022063 | PGS005017 (mean_Systolic_INT_prscs_METAss_afrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.104 [0.09, 0.12] | — | R²: 0.012 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022070 | PGS005017 (mean_Systolic_INT_prscs_METAss_afrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.128 [0.11, 0.14] | — | R²: 0.02 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022057 | PGS005018 (mean_Systolic_INT_prscs_METAss_amrld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.178 [0.17, 0.19] | — | R²: 0.037 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022071 | PGS005018 (mean_Systolic_INT_prscs_METAss_amrld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.177 [0.16, 0.19] | — | R²: 0.039 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022064 | PGS005018 (mean_Systolic_INT_prscs_METAss_amrld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.141 [0.13, 0.15] | — | R²: 0.023 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022058 | PGS005019 (mean_Systolic_INT_prscs_METAss_eurld) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.189 [0.18, 0.2] | — | R²: 0.042 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022065 | PGS005019 (mean_Systolic_INT_prscs_METAss_eurld) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.137 [0.12, 0.15] | — | R²: 0.021 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022072 | PGS005019 (mean_Systolic_INT_prscs_METAss_eurld) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.18 [0.17, 0.2] | — | R²: 0.041 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022062 | PGS005020 (mean_Systolic_INT_prscsx_METAweight) |
PSS011804| African Ancestry| 19,359 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.146 [0.13, 0.16] | — | R²: 0.024 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022069 | PGS005020 (mean_Systolic_INT_prscsx_METAweight) |
PSS011814| Hispanic or Latin American Ancestry| 13,129 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.189 [0.17, 0.2] | — | R²: 0.045 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022055 | PGS005020 (mean_Systolic_INT_prscsx_METAweight) |
PSS011824| European Ancestry| 45,505 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Systolic blood pressure | β: 0.19 [0.18, 0.2] | — | R²: 0.042 | score previously adjusted for age, sex, 20 PCs | — |
| PPM022330 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Hypertension | OR: 1.47 [1.3, 1.6] | AUROC: 0.77 [0.74, 0.81] | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022323 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Systolic Blood Pressure | β: 2.8 [2.1, 3.5] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022324 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Systolic Blood Pressure | β: 2.6 [2.2, 3.0] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022325 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Systolic Blood Pressure | β: 5.2 [5.1, 5.3] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022326 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Diastolic Blood Pressure | β: 1.2 [0.7, 1.7] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022327 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Diastolic Blood Pressure | β: 1.8 [1.4, 2.1] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022328 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Diastolic Blood Pressure | β: 2.1 [2.0, 2.2] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022329 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Hypertension | OR: 1.28 [1.2, 1.4] | AUROC: 0.79 [0.75, 0.84] | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022331 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Hypertension | OR: 1.56 [1.54, 1.56] | AUROC: 0.73 [0.72, 0.74] | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022332 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Elevated hypertension | OR: 1.2 [0.5, 2.66] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022333 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Elevated hypertension | OR: 1.87 [1.2, 2.8] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022335 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 1 hypertension | OR: 1.4 [0.77, 2.7] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022336 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 1 hypertension | OR: 2.14 [1.53, 3.1] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022337 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 1 hypertension | OR: 2.52 [2.2, 2.8] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022338 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011913| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 2 hypertension | OR: 2.5 [1.4, 5.0] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022339 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011914| Hispanic or Latin American Ancestry| 2,904 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 2 hypertension | OR: 2.14 [1.53, 3.1] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022340 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Stage 2 hypertension | OR: 4.9 [4.42, 5.56] | — | — | Age, sex, BMI, first four genetic principal components | — |
| PPM022334 | PGS005120 (PGS_Teixeira_2024_SBP) |
PSS011915| European Ancestry| 73,790 individuals |
PGP000702 | Teixeira SK et al. Sci Rep (2024) |
Reported Trait: Elevated hypertension | OR: 1.8 [1.6, 2.1] | — | — | Age, sex, BMI, first four genetic principal components | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS008150 | — | — | 1,719 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS010687 | — | — | 6,181 individuals, 45.0 % Male samples |
Mean = 54.5 years Sd = 8.4 years |
European | Italian | UKB | — |
| PSS011441 | — | — | [ ,
82.0 % Male samples |
Mean = 27.5 years | African unspecified | — | PDAY | — |
| PSS011442 | — | — | [ ,
77.0 % Male samples |
Mean = 26.7 years | European | — | PDAY | — |
| PSS007266 | — | — | 6,409 individuals | — | African unspecified | — | UKB | — |
| PSS007267 | — | — | 1,634 individuals | — | East Asian | — | UKB | — |
| PSS007268 | — | — | 23,726 individuals | — | European | non-white British ancestry | UKB | — |
| PSS007269 | — | — | 7,640 individuals | — | South Asian | — | UKB | — |
| PSS007270 | — | — | 63,823 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS010011 | Systolic Blood Pressure; Quantitative | — | 23,072 individuals | — | European | — | MGI | — |
| PSS011913 | Systolic blood pressure (adjusted for medication use: +15 mmHg) | — | 2,374 individuals, 42.4 % Male samples |
— | Hispanic or Latin American (Brazilian) |
Admixed population | Baependi | Genotyping using Affymetrix arrays |
| PSS011914 | Systolic blood pressure (adjusted for medication use: +15 mmHg) | — | 2,904 individuals, 49.3 % Male samples |
— | Hispanic or Latin American (Brazilian) |
Admixed population | 1982 PELOTAS | Genotyping using Illumina arrays |
| PSS011915 | Systolic blood pressure (adjusted for medication use: +15 mmHg) | — | 73,790 individuals, 46.0 % Male samples |
— | European | Homogeneous European population | UKB | — |
| PSS001169 | Cases were individuals with hypertension. Of the 27,804 cases, 13,279 had early-onset hypertension (age of onset < 55 years) whilst 14,525 had late-onset hypertension (age of onset ≥ 55 years). | — | [ ,
0.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS001170 | Cases were individuals with hypertension. Of the 28,113 cases, 14,082 had early-onset hypertension (age of onset < 55 years) whilst 14,031 had late-onset hypertension (age of onset ≥ 55 years). | — | [ ,
100.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS009903 | — | — | 4,333 individuals, 46.0 % Male samples |
Mean = 52.0 years | Not reported | — | CoLaus | CoLaus|PsyCoLaus |
| PSS009904 | — | — | 2,944 individuals, 44.0 % Male samples |
Mean = 56.0 years | Not reported | — | CoLaus | CoLaus|PsyCoLaus |
| PSS009905 | — | — | 2,541 individuals, 42.0 % Male samples |
Mean = 61.0 years | Not reported | — | CoLaus | CoLaus|PsyCoLaus |
| PSS009906 | — | — | 1,920 individuals, 41.0 % Male samples |
Mean = 63.0 years | Not reported | — | CoLaus | CoLaus|PsyCoLaus |
| PSS009268 | — | — | 3,930 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS010771 | — | — | 3,819 individuals, 46.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
| PSS010267 | — | — | 2,194 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
| PSS009627 | — | — | 4,416 individuals, 75.0 % Male samples |
European | — | UCC-SMART | UCC-SMART | |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS008822 | — | — | 6,337 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS009643 | Corrected for baseline antihypertensive use | — | 6,335 individuals, 62.7 % Male samples |
Median = 62.1 years Sd = [57.8, 67.1] years |
Not reported | 30.4% non-White individuals | ACCORD | — |
| PSS011505 | — | — | 7,188 individuals | — | South Asian | — | G&H | — |
| PSS010855 | — | — | 3,920 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
| PSS010351 | — | — | 2,424 individuals, 36.0 % Male samples |
Mean = 52.5 years Sd = 8.1 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
| PSS011309 | — | — | 408,475 individuals, 59.0 % Male samples |
Mean = 61.0 years Sd = 7.0 years |
European | — | UKB | — |
| PSS011310 | — | — | 1,750 individuals, 65.0 % Male samples |
Mean = 68.0 years Sd = 11.0 years |
European | — | VISP | — |
| PSS011312 | — | — | 22,701 individuals, 27.8 % Male samples |
— | European | — | ARIC, CHS, FHS, MESA, WHI | — |
| PSS011312 | — | — | 8,822 individuals, 31.9 % Male samples |
— | African American or Afro-Caribbean | — | 6 cohorts
|
— |
| PSS011312 | — | — | 6,718 individuals, 38.0 % Male samples |
— | Hispanic or Latin American | — | 6 cohorts
|
— |
| PSS011979 | — | — | 5,034 individuals | — | European (British) |
— | UKB | — |
| PSS011980 | — | — | 1,750 individuals | — | European (British) |
— | UKB | — |
| PSS011981 | — | — | 932 individuals | — | European (British) |
— | UKB | — |
| PSS011982 | — | — | 2,145 individuals | — | European (British) |
— | UKB | — |
| PSS011983 | — | — | 8,250 individuals | — | European (British) |
— | UKB | — |
| PSS011312 | — | — | 794 individuals, 37.9 % Male samples |
— | Asian unspecified | — | MESA, WHI | — |
| PSS008374 | — | — | 6,098 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009963 | — | Median = 12.9 years | 33,770 individuals, 46.5 % Male samples |
Mean = 49.6 years | European (Finnish) |
Finland | FINRISK, Health2000 | — |
| PSS010939 | — | — | 18,679 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
| PSS010435 | — | — | 1,709 individuals, 33.0 % Male samples |
Mean = 52.5 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
| PSS007938 | — | — | 2,438 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011352 | — | — | 19,883 individuals | — | European | — | UKB | Median age of full combined ancestry cohort = 61 years; mean follow-up time of full combined ancestry cohort = 11.95 years |
| PSS011352 | — | — | 3,147 individuals | — | Not reported | — | UKB | Median age of full combined ancestry cohort = 61 years; mean follow-up time of full combined ancestry cohort = 11.95 years |
| PSS010956 | — | — | [
|
— | European | — | HUNT | — |
| PSS009980 | — | — | 14,069 individuals | — | European (White) |
— | 6 cohorts
|
— |
| PSS009494 | — | — | 18,717 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009980 | — | — | 1,022 individuals | — | Hispanic or Latin American (Hispanics) |
— | 6 cohorts
|
— |
| PSS009980 | — | — | 606 individuals | — | Asian unspecified | — | 6 cohorts
|
— |
| PSS009980 | — | — | 6,186 individuals | — | African American or Afro-Caribbean (Black) |
— | 6 cohorts
|
— |
| PSS009981 | — | — | 936 individuals | — | African American or Afro-Caribbean (Black) |
— | NR | — |
| PSS009981 | — | — | 383 individuals | — | Hispanic or Latin American (Hispanics) |
— | NR | — |
| PSS009981 | — | — | 608 individuals | — | Other | — | NR | — |
| PSS009981 | — | — | 4,408 individuals | — | European | — | NR | — |
| PSS009982 | — | — | 1,453 individuals | — | Asian unspecified | — | NR | — |
| PSS009982 | — | — | 9,680 individuals | — | African American or Afro-Caribbean (Black) |
— | NR | — |
| PSS009982 | — | — | 314 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Middle Eastern) |
— | NR | — |
| PSS009982 | — | — | 40 individuals | — | Native American | — | NR | — |
| PSS009982 | — | — | 31,706 individuals | — | European | — | NR | — |
| PSS009982 | — | — | 905 individuals | — | Other admixed ancestry | more than 1 population | NR | — |
| PSS011189 | — | — | 19,441 individuals, 44.7 % Male samples |
Mean = 47.36 years Sd = 14.8 years |
African unspecified | — | AllofUs | — |
| PSS011189 | — | — | 2,891 individuals, 40.3 % Male samples |
Mean = 42.96 years Sd = 16.67 years |
Asian unspecified | — | AllofUs | — |
| PSS011189 | — | — | 48,155 individuals, 40.4 % Male samples |
Mean = 53.65 years Sd = 16.61 years |
European | — | AllofUs | — |
| PSS011189 | — | — | 18,034 individuals, 31.9 % Male samples |
Mean = 44.27 years Sd = 15.79 years |
Hispanic or Latin American | — | AllofUs | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS011804 | — | — | 19,359 individuals | — | African American or Afro-Caribbean | — | AllofUs | — |
| PSS011191 | — | — | 127,679 individuals, 0.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011192 | — | — | 84,990 individuals, 100.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011193 | — | — | 67,630 individuals, 0.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011194 | — | — | 51,358 individuals, 100.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011195 | — | — | 60,049 individuals, 0.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011196 | — | — | 33,632 individuals, 100.0 % Male samples |
— | European, African unspecified, East Asian, South Asian, Greater Middle Eastern (Middle Eastern, North African or Persian), Hispanic or Latin American | — | AllofUs | — |
| PSS011814 | — | — | 13,129 individuals | — | Hispanic or Latin American | — | AllofUs | — |
| PSS010519 | — | — | 6,050 individuals, 54.0 % Male samples |
Mean = 53.4 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
| PSS001446 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). Of the 55,917 cases, 27,361 had early-onset incident hypertension, whilst 28,556 had late-onset incident hypertension. Early-onset and late-onset hypertension were defined as age of onset <55 and ≥55 years, respectively. | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS001447 | Cases were individuals with incident coronary heart disease (CHD). CHD was defined as Major coronary heart disease event: coronary revascularization (angioplasty or bypass grafting) or myocardial infarction. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (410/4110) , ICD-9 codes (410), and ICD-10 codes (I200/I21/I22). | — | [ ,
44.0 % Male samples |
Mean = 58.0 years | European (Finnish) |
— | FinnGen | — |
| PSS001448 | Cases were individuals with incident cardiovascular disease (CVD). CVD was defined as ard cardiovascular diseases: coronary heart disease or stroke. | — | [ ,
44.0 % Male samples |
Mean = 58.0 years | European (Finnish) |
— | FinnGen | — |
| PSS001449 | Cases were individuals with incident stroke. Stroke was defined as stroke, excluding subarachnoid hemorrhage. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (431/433/434/436) , ICD-9 codes (431/4330A/4331A/4339A/4340A/4341A/4349A/436), and ICD-10 codes (I61/I63/I64 (excluding I636)). | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS009510 | Apparent Treatment-Resistant Hypertension | — | [
|
— | Not reported | — | BioVU | Multi-Ancestry analysis |
| PSS009511 | Apparent Treatment-Resistant Hypertension | — | [ ,
37.0 % Male samples |
Mean = 50.6 years | African American or Afro-Caribbean | African American, Non-Hispanic Black | BioVU | — |
| PSS009511 | Apparent Treatment-Resistant Hypertension | — | [ ,
37.0 % Male samples |
Mean = 50.6 years | African American or Afro-Caribbean | African American, Non-Hispanic Black | BioVU | Multi-Ancestry analysis |
| PSS009512 | Apparent Treatment-Resistant Hypertension | — | [ ,
46.0 % Male samples |
Mean = 58.58 years | European | European, Non-Hispanic White | BioVU | — |
| PSS009512 | Apparent Treatment-Resistant Hypertension | — | [ ,
46.0 % Male samples |
Mean = 58.58 years | European | European, Non-Hispanic White | BioVU | Multi-Ancestry analysis |
| PSS001450 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). | — | [
|
— | European (Finnish) |
— | FINRISK | — |
| PSS011824 | — | — | 45,505 individuals | — | European | — | AllofUs | — |
| PSS009042 | — | — | 3,850 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011387 | — | — | [ ,
0.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS011388 | — | — | [ ,
0.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS011396 | the earliest median eligible non-Emergency Department outpatient measured SBP in the electronic health record, and the corresponding DBP. For individuals with an even number of SBP measures in their record, the lower value was used to compute the median. For individuals with fewer than three measurements available, the lowest available SBP and corresponding DBP were used. Measures were considered ineligible if they occurred at or after an ICD-9/10 billing code from the groups 585/N18 (chronic kidney disease), 405/I15 (secondary hypertension), or 428/I50 (heart failure). For participants who had started an antihypertensive medication before the date of their median SBP measurement, 15 mm Hg was added to SBP and 10 mm Hg to DBP. Eligible SBP measures were restricted to a range of 30 to 300 mmHg. Eligible DBP measures were restricted to values over 30 mmHg. Eligible DBP measures were restricted to values over 30 mmHg. Sample size for SBP, DBP, and PP GWAS analysis included 21,843 individuals. Pulse pressure was defined as SBP minus DBP. Hypertension status was defined by phecodes 401* and/or antihypertensive medication use. | — | 21,843 individuals, 42.69 % Male samples |
Mean = 48.3 years Sd = 14.75 years |
African American or Afro-Caribbean (American) |
— | AllofUs | — |
| PSS011397 | In Lifelines, BP was measured every minute during a period of ten minutes using an automated DINAMAP Monitor (GE Healthcare) and the average of the final three readings was recorded for SBP and DBP. Participants with a measured BP ≥140/90 mm Hg irrespective of treatment and those taking antihypertensive medication (ATC codes C02, C03, C07, C08, C09) irrespective of BP were defined as having hypertension. In continuous trait analyses, 15 mm Hg was added to SBP and 10 mm Hg was added to DBP for 1,236 individuals who were taking antihypertensive medication. PP was calculated using these medication-adjusted BP values. | — | 10,210 individuals, 41.6 % Male samples |
Mean = 44.66 years Sd = 13.05 years |
European (Dutch) |
— | LifeLines | — |
| PSS000371 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 288 individuals, 69.2 % Male samples |
Mean = 15.83 years Sd = 0.6 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS000376 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,354 individuals, 47.56 % Male samples |
Mean = 16.22 years Sd = 0.66 years |
European | — | TRAILS | — |
| PSS010603 | — | — | 1,122 individuals, 60.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
| PSS008596 | — | — | 1,151 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009839 | — | — | 6,128 individuals | — | African unspecified | — | UKB | — |
| PSS009840 | — | — | 859 individuals | — | East Asian | — | UKB | — |
| PSS009841 | — | — | 40,059 individuals | — | European | Non-British European | UKB | — |
| PSS009842 | — | — | 7,573 individuals | — | South Asian | — | UKB | — |
| PSS009574 | — | — | 14,004 individuals | — | European | — | Airwave | — |
| PSS009575 | — | — | 6,970 individuals | — | African unspecified | — | UKB | — |
| PSS009576 | — | — | 8,827 individuals | — | South Asian | — | UKB | — |
| PSS009581 | The treated hypertension sub-cohort was participants who were presently taking antihypertensive medications (indicated by selecting ‘blood pressure medication’ in response to the question ‘Do you regularly take any of the following medications?’ or reporting an antihypertensive medication in a verbal interview with a trained nurse). The antihypertensive medication classes considered were beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium-channel blocker, alpha blockers, and diuretics. Uncontrolled hypertension was defined as having a mean systolic BP >_140 mmHg or mean diastolic BP >_90 mmHg, among individuals in the treated hypertension sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.5 years | [ ,
51.0 % Male samples |
Mean = 61.0 years | European (white British) |
— | UKB | — |
| PSS009582 | The treated hypertension sub-cohort was participants who were presently taking antihypertensive medications (indicated by selecting ‘blood pressure medication’ in response to the question ‘Do you regularly take any of the following medications?’ or reporting an antihypertensive medication in a verbal interview with a trained nurse). The antihypertensive medication classes considered were beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium-channel blocker, alpha blockers, and diuretics. Uncontrolled hypertension was defined as having a mean systolic BP >_140 mmHg or mean diastolic BP >_90 mmHg, among individuals in the treated hypertension sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.5 years | [ ,
51.0 % Male samples |
Mean = 61.0 years | European (white British) |
— | UKB | — |
| PSS009583 | The treated hypertension sub-cohort was participants who were presently taking antihypertensive medications (indicated by selecting ‘blood pressure medication’ in response to the question ‘Do you regularly take any of the following medications?’ or reporting an antihypertensive medication in a verbal interview with a trained nurse). The antihypertensive medication classes considered were beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium-channel blocker, alpha blockers, and diuretics. Uncontrolled hypertension was defined as having a mean systolic BP >_140 mmHg or mean diastolic BP >_90 mmHg, among individuals in the treated hypertension sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.5 years | [ ,
51.0 % Male samples |
Mean = 61.0 years | European (white British) |
— | UKB | — |
| PSS009584 | The treated hypertension sub-cohort was participants who were presently taking antihypertensive medications (indicated by selecting ‘blood pressure medication’ in response to the question ‘Do you regularly take any of the following medications?’ or reporting an antihypertensive medication in a verbal interview with a trained nurse). The antihypertensive medication classes considered were beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium-channel blocker, alpha blockers, and diuretics. Uncontrolled hypertension was defined as having a mean systolic BP >_140 mmHg or mean diastolic BP >_90 mmHg, among individuals in the treated hypertension sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.5 years | [ ,
51.0 % Male samples |
Mean = 61.0 years | European (white British) |
— | UKB | — |