| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0001379 |
| Description | A disease involving the endocrine system. | Trait category |
Other disease
|
| Synonyms |
46 synonyms
|
| Mapped terms |
14 mapped terms
|
| Child trait(s) |
27 child traits
|
| 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) |
|---|---|---|---|---|---|---|
| PGS000014 (GPS_T2D) |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,917,436 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000014/ScoringFiles/PGS000014.txt.gz | |
| PGS000020 (dGRS1000) |
PGP000010 | Läll K et al. Genet Med (2016) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 7,502 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000020/ScoringFiles/PGS000020.txt.gz |
| PGS000021 (GRS1) |
PGP000011 | Oram RA et al. Diabetes Care (2015) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 30 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000021/ScoringFiles/PGS000021.txt.gz | |
| PGS000022 (T1D_GRS) |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 37 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000022/ScoringFiles/PGS000022.txt.gz |
| PGS000023 (AA_GRS) |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 7 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000023/ScoringFiles/PGS000023.txt.gz |
| PGS000024 (GRS2) |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 67 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000024/ScoringFiles/PGS000024.txt.gz |
| PGS000031 (GRSt) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 62 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000031/ScoringFiles/PGS000031.txt.gz |
| PGS000032 (GRSB) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (based on SNPs involved in β-cell function) | type 2 diabetes mellitus | 20 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000032/ScoringFiles/PGS000032.txt.gz |
| PGS000033 (GRSIR) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (based on SNPs involved in insulin resistance) | type 2 diabetes mellitus | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000033/ScoringFiles/PGS000033.txt.gz |
| PGS000036 (gePS_T2D) |
PGP000023 | Mahajan A et al. Nat Genet (2018) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 171,249 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000036/ScoringFiles/PGS000036.txt.gz | |
| PGS000048 (OCPRS_Overall) |
PGP000033 | Kuchenbaecker KB et al. J Natl Cancer Inst (2017) |
Ovarian cancer | ovarian carcinoma | 17 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000048/ScoringFiles/PGS000048.txt.gz |
| PGS000068 (PRS_EOC) |
PGP000048 | Yang X et al. J Med Genet (2018) |
Epithelial ovarian cancer | ovarian carcinoma | 15 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000068/ScoringFiles/PGS000068.txt.gz |
| PGS000069 (PRS_sEOC) |
PGP000048 | Yang X et al. J Med Genet (2018) |
Serous epithelial ovarian cancer | ovarian serous carcinoma | 15 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000069/ScoringFiles/PGS000069.txt.gz |
| PGS000082 (CC_Ovary) |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Ovarian cancer | ovarian carcinoma | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000082/ScoringFiles/PGS000082.txt.gz |
| PGS000083 (CC_Pancreas) |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Pancreatic cancer | pancreatic carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000083/ScoringFiles/PGS000083.txt.gz |
| PGS000086 (CC_Testis) |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Testicular cancer | testicular carcinoma, Testicular Germ Cell Tumor |
52 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000086/ScoringFiles/PGS000086.txt.gz |
| PGS000087 (CC_Thyroid) |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Thyroid cancer | thyroid carcinoma | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000087/ScoringFiles/PGS000087.txt.gz |
| PGS000125 (Qi_T2D_2017) |
PGP000062 | Qi Q et al. Diabetes (2017) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 80 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000125/ScoringFiles/PGS000125.txt.gz |
| PGS000158 (cGRS_Ovarian) |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Ovarian cancer | ovarian carcinoma | 11 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000158/ScoringFiles/PGS000158.txt.gz |
| PGS000159 (cGRS_Pancreatic) |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Pancreatic cancer | pancreatic carcinoma | 9 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000159/ScoringFiles/PGS000159.txt.gz |
| PGS000162 (cGRS_Thyroid) |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Thyroid cancer | thyroid carcinoma | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000162/ScoringFiles/PGS000162.txt.gz |
| PGS000207 (TC10_Ohio) |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Thyroid cancer | thyroid carcinoma | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000207/ScoringFiles/PGS000207.txt.gz |
| PGS000208 (TC10_Iceland) |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Thyroid cancer | thyroid carcinoma | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000208/ScoringFiles/PGS000208.txt.gz |
| PGS000209 (TC10_UKB) |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Thyroid cancer | thyroid carcinoma | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000209/ScoringFiles/PGS000209.txt.gz |
| PGS000330 (PRS_T2D) |
PGP000100 | Mars N et al. Nat Med (2020) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,437,380 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000330/ScoringFiles/PGS000330.txt.gz | |
| PGS000351 (PRS_EOC) |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Invasive epithelial ovarian cancer | ovarian carcinoma | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000351/ScoringFiles/PGS000351.txt.gz |
| PGS000352 (PRS_HGS) |
PGP000117 | Barnes DR et al. Genet Med (2020) |
High grade serous ovarian cancer | high grade ovarian serous adenocarcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000352/ScoringFiles/PGS000352.txt.gz |
| PGS000385 (PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Pancreatic cancer | pancreatic carcinoma | 17 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000385/ScoringFiles/PGS000385.txt.gz | |
| PGS000386 (PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Pancreatic cancer | pancreatic carcinoma | 10 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000386/ScoringFiles/PGS000386.txt.gz | |
| PGS000544 (PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 21 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000544/ScoringFiles/PGS000544.txt.gz | |
| PGS000545 (PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 21 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000545/ScoringFiles/PGS000545.txt.gz | |
| PGS000546 (PRSWEB_PHECODE184.11_Phelan-ENOC_PRS-CS_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,115,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000546/ScoringFiles/PGS000546.txt.gz | |
| PGS000547 (PRSWEB_PHECODE184.11_Phelan-EPOC_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 6 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000547/ScoringFiles/PGS000547.txt.gz | |
| PGS000548 (PRSWEB_PHECODE184.11_Phelan-EPOC_LASSOSUM_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,441 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000548/ScoringFiles/PGS000548.txt.gz | |
| PGS000549 (PRSWEB_PHECODE184.11_Phelan-IEOC_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 16 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000549/ScoringFiles/PGS000549.txt.gz | |
| PGS000550 (PRSWEB_PHECODE184.11_Phelan-IEOC_PRS-CS_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,115,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000550/ScoringFiles/PGS000550.txt.gz | |
| PGS000551 (PRSWEB_PHECODE184.11_Phelan-IEOC_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000551/ScoringFiles/PGS000551.txt.gz | |
| PGS000552 (PRSWEB_PHECODE184.11_Phelan-IEOC_LASSOSUM_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 41,269 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000552/ScoringFiles/PGS000552.txt.gz | |
| PGS000553 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 10 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000553/ScoringFiles/PGS000553.txt.gz | |
| PGS000554 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_PRS-CS_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,115,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000554/ScoringFiles/PGS000554.txt.gz | |
| PGS000555 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 15 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000555/ScoringFiles/PGS000555.txt.gz | |
| PGS000556 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_LASSOSUM_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 486,841 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000556/ScoringFiles/PGS000556.txt.gz | |
| PGS000557 (PRSWEB_PHECODE184.11_Phelan-OCCC_PRS-CS_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,115,187 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000557/ScoringFiles/PGS000557.txt.gz | |
| PGS000558 (PRSWEB_PHECODE184.11_Phelan-OCCC_LASSOSUM_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,098,236 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000558/ScoringFiles/PGS000558.txt.gz | |
| PGS000559 (PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 21 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000559/ScoringFiles/PGS000559.txt.gz | |
| PGS000560 (PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 21 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000560/ScoringFiles/PGS000560.txt.gz | |
| PGS000561 (PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,114,056 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000561/ScoringFiles/PGS000561.txt.gz | |
| PGS000562 (PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 1,115,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000562/ScoringFiles/PGS000562.txt.gz | |
| PGS000563 (PRSWEB_PHECODE184.11_Phelan-SIOC_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000563/ScoringFiles/PGS000563.txt.gz | |
| PGS000564 (PRSWEB_PHECODE184.11_Phelan-SIOC_LASSOSUM_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of ovary | ovarian neoplasm | 110,710 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000564/ScoringFiles/PGS000564.txt.gz | |
| PGS000595 (PRSWEB_PHECODE187.2_20001-1045_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 9 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000595/ScoringFiles/PGS000595.txt.gz | |
| PGS000596 (PRSWEB_PHECODE187.2_20001-1045_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 5 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000596/ScoringFiles/PGS000596.txt.gz | |
| PGS000597 (PRSWEB_PHECODE187.2_20001-1045_LASSOSUM_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 771 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000597/ScoringFiles/PGS000597.txt.gz | |
| PGS000598 (PRSWEB_PHECODE187.2_C3-TESTIS_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 6 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000598/ScoringFiles/PGS000598.txt.gz | |
| PGS000599 (PRSWEB_PHECODE187.2_C3-TESTIS_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 31 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000599/ScoringFiles/PGS000599.txt.gz | |
| PGS000600 (PRSWEB_PHECODE187.2_C3-TESTIS_LASSOSUM_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 250 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000600/ScoringFiles/PGS000600.txt.gz | |
| PGS000601 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 40 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000601/ScoringFiles/PGS000601.txt.gz | |
| PGS000602 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 40 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000602/ScoringFiles/PGS000602.txt.gz | |
| PGS000603 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 22 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000603/ScoringFiles/PGS000603.txt.gz | |
| PGS000604 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Malignant neoplasm of testis | testicular carcinoma | 44 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000604/ScoringFiles/PGS000604.txt.gz | |
| PGS000626 (PRSWEB_PHECODE193_20001-1065_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 8 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000626/ScoringFiles/PGS000626.txt.gz | |
| PGS000627 (PRSWEB_PHECODE193_C3-THYROID-GLAND_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000627/ScoringFiles/PGS000627.txt.gz | |
| PGS000628 (PRSWEB_PHECODE193_C3-THYROID-GLAND_LASSOSUM_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 656 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000628/ScoringFiles/PGS000628.txt.gz | |
| PGS000629 (PRSWEB_PHECODE193_C73_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 8 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000629/ScoringFiles/PGS000629.txt.gz | |
| PGS000630 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 10 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000630/ScoringFiles/PGS000630.txt.gz | |
| PGS000631 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 10 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000631/ScoringFiles/PGS000631.txt.gz | |
| PGS000632 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 8 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000632/ScoringFiles/PGS000632.txt.gz | |
| PGS000633 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_UKB_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 5 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000633/ScoringFiles/PGS000633.txt.gz | |
| PGS000634 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PRS-CS_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 1,119,238 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000634/ScoringFiles/PGS000634.txt.gz | |
| PGS000635 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PT_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 5 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000635/ScoringFiles/PGS000635.txt.gz | |
| PGS000636 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_LASSOSUM_MGI_20200608) |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Thyroid cancer | thyroid carcinoma | 954 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000636/ScoringFiles/PGS000636.txt.gz | |
| PGS000655 (NAFLD-10) |
PGP000119 | Namjou B et al. BMC Med (2019) |
Non-alcoholic fatty liver disease | non-alcoholic fatty liver disease | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000655/ScoringFiles/PGS000655.txt.gz |
| PGS000663 (wGRS22) |
PGP000123 | Kim J et al. Cancer Epidemiol Biomarkers Prev (2020) |
Pancreatic cancer | pancreatic carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000663/ScoringFiles/PGS000663.txt.gz |
| PGS000704 (HC171) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Alcoholic cirrhosis | alcoholic liver cirrhosis | 183,271 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000704/ScoringFiles/PGS000704.txt.gz |
| PGS000712 (T2D_HbA1c_39) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
T2D (cases vs HbA1c filtered controls) | type 2 diabetes mellitus | 183,695 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000712/ScoringFiles/PGS000712.txt.gz |
| PGS000713 (T2D) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 183,830 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000713/ScoringFiles/PGS000713.txt.gz |
| PGS000724 (PRS_Ovary) |
PGP000135 | Jia G et al. JNCI Cancer Spectr (2020) |
Epithelial ovarian cancer | ovarian carcinoma | 31 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000724/ScoringFiles/PGS000724.txt.gz |
| PGS000725 (PRS_Pancreas) |
PGP000135 | Jia G et al. JNCI Cancer Spectr (2020) |
Pancreatic cancer | pancreatic carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000725/ScoringFiles/PGS000725.txt.gz |
| PGS000726 (PGS12_CIR) |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Cirrhosis | cirrhosis of liver | 12 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000726/ScoringFiles/PGS000726.txt.gz | |
| PGS000729 (T2D_PGS) |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,017,388 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000729/ScoringFiles/PGS000729.txt.gz |
| PGS000759 (hypoT) |
PGP000164 | Khan Z et al. Nat Commun (2021) |
Hypothyroidism | hypothyroidism | 140 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000759/ScoringFiles/PGS000759.txt.gz |
| PGS000761 (LDpred2_hypoT_PRS) |
PGP000164 | Khan Z et al. Nat Commun (2021) |
Hypothyroidism | hypothyroidism | 1,099,649 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000761/ScoringFiles/PGS000761.txt.gz |
| PGS000776 (GRS9_Cirr) |
PGP000180 | Innes H et al. Gastroenterology (2020) |
Cirrhosis | cirrhosis of liver | 9 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000776/ScoringFiles/PGS000776.txt.gz | |
| PGS000793 (CC_Ovary_IV) |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Ovarian cancer | ovarian carcinoma | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000793/ScoringFiles/PGS000793.txt.gz |
| PGS000794 (CC_Pancreas_IV) |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Pancreatic cancer | pancreatic carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000794/ScoringFiles/PGS000794.txt.gz |
| PGS000796 (CC_Testis_IV) |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Testicular cancer | testicular carcinoma, Testicular Germ Cell Tumor |
52 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000796/ScoringFiles/PGS000796.txt.gz |
| PGS000797 (CC_Thyroid_IV) |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Thyroid cancer | thyroid carcinoma | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000797/ScoringFiles/PGS000797.txt.gz |
| PGS000804 (GRS582_T2Dmulti) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000804/ScoringFiles/PGS000804.txt.gz |
| PGS000805 (GRS582_T2Deur) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000805/ScoringFiles/PGS000805.txt.gz |
| PGS000806 (GRS582_T2Dafr) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000806/ScoringFiles/PGS000806.txt.gz |
| PGS000807 (GRS582_T2Dasn) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000807/ScoringFiles/PGS000807.txt.gz |
| PGS000808 (GRS582_T2Dhis) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000808/ScoringFiles/PGS000808.txt.gz |
| PGS000820 (PRS_hypothyroidism) |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Hypothyroidism (self-reported) | hypothyroidism | 890,908 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000820/ScoringFiles/PGS000820.txt.gz |
| PGS000832 (T2D-GRS) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 384 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000832/ScoringFiles/PGS000832.txt.gz |
| PGS000833 (T1D) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 66 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000833/ScoringFiles/PGS000833.txt.gz |
| PGS000848 (T2D_Adiposity) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with adiposity) | type 2 diabetes mellitus | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000848/ScoringFiles/PGS000848.txt.gz |
| PGS000849 (T2D_Impaired_Lipids) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with impaired lipids) | type 2 diabetes mellitus | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000849/ScoringFiles/PGS000849.txt.gz |
| PGS000850 (T2D_Insulin_Action) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin action) | type 2 diabetes mellitus | 16 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000850/ScoringFiles/PGS000850.txt.gz |
| PGS000851 (T2D_Insulin_Action_Secretion) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin action/secretion) | type 2 diabetes mellitus | 37 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000851/ScoringFiles/PGS000851.txt.gz |
| PGS000852 (T2D_Insulin_Secretion_1) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 8 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000852/ScoringFiles/PGS000852.txt.gz |
| PGS000853 (T2D_Insulin_Secretion_2) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000853/ScoringFiles/PGS000853.txt.gz |
| PGS000854 (T2D_BetaCell) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with beta cell function) | type 2 diabetes mellitus | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000854/ScoringFiles/PGS000854.txt.gz |
| PGS000855 (T2D_Lipodystrophy) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with lipodystrophy) | type 2 diabetes mellitus | 18 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000855/ScoringFiles/PGS000855.txt.gz |
| PGS000856 (T2D_LiverLipids) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with liver lipids) | type 2 diabetes mellitus | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000856/ScoringFiles/PGS000856.txt.gz |
| PGS000857 (T2D_Obesity) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with obesity) | type 2 diabetes mellitus | 4 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000857/ScoringFiles/PGS000857.txt.gz |
| PGS000858 (T2D_Proinsulin) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with proinsulin levels) | type 2 diabetes mellitus | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000858/ScoringFiles/PGS000858.txt.gz |
| PGS000864 (T2D-gPRS) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 389,243 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000864/ScoringFiles/PGS000864.txt.gz |
| PGS000868 (T2D_221) |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 221 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000868/ScoringFiles/PGS000868.txt.gz |
| PGS000869 (T1D_48) |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 48 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000869/ScoringFiles/PGS000869.txt.gz |
| PGS000872 (PRS-5) |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Non-alcoholic fatty liver disease | non-alcoholic fatty liver disease | 5 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000872/ScoringFiles/PGS000872.txt.gz | |
| PGS000928 (GBE_HC644) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other non-toxic goitre (time-to-event) | nontoxic goiter | 170 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000928/ScoringFiles/PGS000928.txt.gz |
| PGS000965 (GBE_HC219) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hypothyroidism/myxoedema | hypothyroidism, myxedema |
4,535 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000965/ScoringFiles/PGS000965.txt.gz |
| PGS001014 (GBE_HC654) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other disorders of pancreatic internal secretion (time-to-event) | pancreas disease | 69 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001014/ScoringFiles/PGS001014.txt.gz |
| PGS001042 (GBE_HC645) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Thyrotoxicosis [hyperthyroidism] (time-to-event) | Thyrotoxicosis | 226 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001042/ScoringFiles/PGS001042.txt.gz |
| PGS001043 (GBE_HC55) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hyperthyroidism, thyrotoxicosis | hyperthyroidism, Thyrotoxicosis |
69 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001043/ScoringFiles/PGS001043.txt.gz |
| PGS001164 (GBE_cancer1045) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Testicular cancer | testicular carcinoma | 280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001164/ScoringFiles/PGS001164.txt.gz |
| PGS001181 (GBE_HC643) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other hypothyroidism (time-to-event) | hypothyroidism | 4,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001181/ScoringFiles/PGS001181.txt.gz |
| PGS001289 (GBE_cancer1065) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Thyroid cancer | thyroid carcinoma | 11 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001289/ScoringFiles/PGS001289.txt.gz |
| PGS001293 (GBE_HC1123) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other diseases of liver (time-to-event) | liver disease | 92 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001293/ScoringFiles/PGS001293.txt.gz |
| PGS001294 (GBE_HC649) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Non-insulin-dependent diabetes (time-to-event) | type 2 diabetes mellitus | 3,496 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001294/ScoringFiles/PGS001294.txt.gz |
| PGS001295 (GBE_HC165) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 385 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001295/ScoringFiles/PGS001295.txt.gz |
| PGS001296 (GBE_HC648) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Insulin-dependent diabetes mellitus (time-to-event) | type 1 diabetes mellitus | 356 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001296/ScoringFiles/PGS001296.txt.gz |
| PGS001297 (GBE_HC337) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 69 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001297/ScoringFiles/PGS001297.txt.gz |
| PGS001327 (GBE_HC221) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Diabetes | diabetes mellitus | 4,053 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001327/ScoringFiles/PGS001327.txt.gz |
| PGS001329 (GBE_HC652) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Unspecified diabetes mellitus (time-to-event) | diabetes mellitus | 2,270 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001329/ScoringFiles/PGS001329.txt.gz |
| PGS001354 (PRS12_TC) |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Thyroid cancer | thyroid carcinoma | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001354/ScoringFiles/PGS001354.txt.gz |
| PGS001357 (T2D_AnnoPred_PRS) |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,996,761 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001357/ScoringFiles/PGS001357.txt.gz | |
| PGS001371 (GBE_INI2976) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Age diabetes diagnosed | diabetes mellitus, age at diagnosis |
26 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001371/ScoringFiles/PGS001371.txt.gz |
| PGS001777 (3-SNP_cirr) |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Cirrhosis (alcohol related) | alcoholic liver cirrhosis | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001777/ScoringFiles/PGS001777.txt.gz |
| PGS001781 (T2D_PRSCS) |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,091,673 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001781/ScoringFiles/PGS001781.txt.gz |
| PGS001794 (1kgeur_gbmi_leaveUKBBout_ThC_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Thyroid cancer | thyroid carcinoma | 911,462 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001794/ScoringFiles/PGS001794.txt.gz |
| PGS001799 (1kgeur_gbmi_ThC_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Thyroid cancer | thyroid carcinoma | 885,482 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001799/ScoringFiles/PGS001799.txt.gz |
| PGS001809 (portability-PLR_193) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Thyroid cancer | thyroid carcinoma | 111 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001809/ScoringFiles/PGS001809.txt.gz |
| PGS001814 (portability-PLR_241.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Nontoxic multinodular goiter | multinodular goiter, nontoxic goiter |
322 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001814/ScoringFiles/PGS001814.txt.gz |
| PGS001815 (portability-PLR_242) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Thyrotoxicosis with or without goiter | Thyrotoxicosis | 280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001815/ScoringFiles/PGS001815.txt.gz |
| PGS001816 (portability-PLR_244) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hypothyroidism | hypothyroidism | 11,130 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001816/ScoringFiles/PGS001816.txt.gz |
| PGS001817 (portability-PLR_250.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 825 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001817/ScoringFiles/PGS001817.txt.gz |
| PGS001818 (portability-PLR_250.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 30,745 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001818/ScoringFiles/PGS001818.txt.gz |
| PGS001860 (portability-PLR_571.5) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Other chronic nonalcoholic liver disease | liver disease | 497 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001860/ScoringFiles/PGS001860.txt.gz |
| PGS002018 (portability-ldpred2_193) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Thyroid cancer | thyroid carcinoma | 311,520 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002018/ScoringFiles/PGS002018.txt.gz |
| PGS002022 (portability-ldpred2_241.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Nontoxic multinodular goiter | multinodular goiter, nontoxic goiter |
375,470 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002022/ScoringFiles/PGS002022.txt.gz |
| PGS002023 (portability-ldpred2_242) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Thyrotoxicosis with or without goiter | Thyrotoxicosis | 279,385 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002023/ScoringFiles/PGS002023.txt.gz |
| PGS002024 (portability-ldpred2_244) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hypothyroidism | hypothyroidism | 632,597 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002024/ScoringFiles/PGS002024.txt.gz |
| PGS002025 (portability-ldpred2_250.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 106,800 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002025/ScoringFiles/PGS002025.txt.gz |
| PGS002026 (portability-ldpred2_250.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 830,783 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002026/ScoringFiles/PGS002026.txt.gz |
| PGS002071 (portability-ldpred2_571.5) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Other chronic nonalcoholic liver disease | liver disease | 352,506 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002071/ScoringFiles/PGS002071.txt.gz |
| PGS002243 (ldpred_t2d) |
PGP000271 | Mars N et al. Cell Genom (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,431,973 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002243/ScoringFiles/PGS002243.txt.gz | |
| PGS002250 (PRS_S4) |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Epithelial ovarian cancer | ovarian carcinoma | 27,240 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002250/ScoringFiles/PGS002250.txt.gz |
| PGS002256 (GRS4_GDM) |
PGP000282 | Wu Q et al. Diabetol Metab Syndr (2022) |
Gestational diabetes mellitus in early pregnancy | gestational diabetes | 4 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002256/ScoringFiles/PGS002256.txt.gz | |
| PGS002264 (PRS_Combined) |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Pancreatic ductal adenocarcinoma | pancreatic ductal adenocarcinoma | 49 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002264/ScoringFiles/PGS002264.txt.gz |
| PGS002277 (pPS_Insulin_secretion_1) |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 8 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002277/ScoringFiles/PGS002277.txt.gz |
| PGS002282 (GRS68_NAFLD) |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Nonalcoholic fatty liver disease | non-alcoholic fatty liver disease | 68 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002282/ScoringFiles/PGS002282.txt.gz |
| PGS002283 (GRS15_NAFLD) |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Nonalcoholic fatty liver disease | non-alcoholic fatty liver disease | 15 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002283/ScoringFiles/PGS002283.txt.gz |
| PGS002308 (PRScsx_T2D) |
PGP000331 | Ge T et al. Genome Med (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,259,754 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002308/ScoringFiles/PGS002308.txt.gz |
| PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002321/ScoringFiles/PGS002321.txt.gz |
| PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002324/ScoringFiles/PGS002324.txt.gz |
| PGS002336 (disease_HYPOTHYROIDISM_SELF_REP.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002336/ScoringFiles/PGS002336.txt.gz |
| PGS002351 (disease_THYROID_ANY_SELF_REP.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002351/ScoringFiles/PGS002351.txt.gz |
| PGS002354 (disease_T2D.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002354/ScoringFiles/PGS002354.txt.gz |
| PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 920,930 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002379/ScoringFiles/PGS002379.txt.gz |
| PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 3,813 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002393/ScoringFiles/PGS002393.txt.gz |
| PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
3,681 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002396/ScoringFiles/PGS002396.txt.gz |
| PGS002408 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 4,815 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002408/ScoringFiles/PGS002408.txt.gz |
| PGS002423 (disease_THYROID_ANY_SELF_REP.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 4,483 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002423/ScoringFiles/PGS002423.txt.gz |
| PGS002426 (disease_T2D.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 3,947 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002426/ScoringFiles/PGS002426.txt.gz |
| PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 15,915 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002442/ScoringFiles/PGS002442.txt.gz |
| PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
15,629 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002445/ScoringFiles/PGS002445.txt.gz |
| PGS002457 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 17,519 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002457/ScoringFiles/PGS002457.txt.gz |
| PGS002472 (disease_THYROID_ANY_SELF_REP.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 16,694 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002472/ScoringFiles/PGS002472.txt.gz |
| PGS002475 (disease_T2D.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 16,275 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002475/ScoringFiles/PGS002475.txt.gz |
| PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 95,066 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002491/ScoringFiles/PGS002491.txt.gz |
| PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
93,293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002494/ScoringFiles/PGS002494.txt.gz |
| PGS002506 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 97,010 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002506/ScoringFiles/PGS002506.txt.gz |
| PGS002521 (disease_THYROID_ANY_SELF_REP.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 95,522 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002521/ScoringFiles/PGS002521.txt.gz |
| PGS002524 (disease_T2D.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 95,287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002524/ScoringFiles/PGS002524.txt.gz |
| PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 598 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002540/ScoringFiles/PGS002540.txt.gz |
| PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
528 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002543/ScoringFiles/PGS002543.txt.gz |
| PGS002555 (disease_HYPOTHYROIDISM_SELF_REP.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 986 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002555/ScoringFiles/PGS002555.txt.gz |
| PGS002570 (disease_THYROID_ANY_SELF_REP.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 954 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002570/ScoringFiles/PGS002570.txt.gz |
| PGS002573 (disease_T2D.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 673 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002573/ScoringFiles/PGS002573.txt.gz |
| PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 267 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002589/ScoringFiles/PGS002589.txt.gz |
| PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
187 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002592/ScoringFiles/PGS002592.txt.gz |
| PGS002604 (disease_HYPOTHYROIDISM_SELF_REP.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 550 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002604/ScoringFiles/PGS002604.txt.gz |
| PGS002619 (disease_THYROID_ANY_SELF_REP.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 548 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002619/ScoringFiles/PGS002619.txt.gz |
| PGS002622 (disease_T2D.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002622/ScoringFiles/PGS002622.txt.gz |
| PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 247,386 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002638/ScoringFiles/PGS002638.txt.gz |
| PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
256,678 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002641/ScoringFiles/PGS002641.txt.gz |
| PGS002653 (disease_HYPOTHYROIDISM_SELF_REP.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 197,450 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002653/ScoringFiles/PGS002653.txt.gz |
| PGS002668 (disease_THYROID_ANY_SELF_REP.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 189,808 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002668/ScoringFiles/PGS002668.txt.gz |
| PGS002671 (disease_T2D.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 258,382 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002671/ScoringFiles/PGS002671.txt.gz |
| PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 923,080 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002687/ScoringFiles/PGS002687.txt.gz |
| PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
905,637 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002690/ScoringFiles/PGS002690.txt.gz |
| PGS002702 (disease_HYPOTHYROIDISM_SELF_REP.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypothyroidism | hypothyroidism | 889,041 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002702/ScoringFiles/PGS002702.txt.gz |
| PGS002717 (disease_THYROID_ANY_SELF_REP.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Thyroid (self-reported conditions) | thyroid disease | 895,602 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002717/ScoringFiles/PGS002717.txt.gz |
| PGS002720 (disease_T2D.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 911,809 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002720/ScoringFiles/PGS002720.txt.gz |
| PGS002733 (GRS17_T2D) |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 17 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002733/ScoringFiles/PGS002733.txt.gz |
| PGS002740 (PRS22_PC) |
PGP000347 | Yuan C et al. Ann Oncol (2022) |
Pancreatic cancer | pancreatic carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002740/ScoringFiles/PGS002740.txt.gz |
| PGS002766 (Hypothyroidism_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Hypothyroidism | hypothyroidism | 1,092,122 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002766/ScoringFiles/PGS002766.txt.gz |
| PGS002771 (Type_2_diabetes_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,091,608 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002771/ScoringFiles/PGS002771.txt.gz |
| PGS002779 (GTG_T2D_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident type 2 diabetes | type 2 diabetes mellitus | 46,353 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002779/ScoringFiles/PGS002779.txt.gz | |
| PGS002780 (GTG_T2D_SCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident type 2 diabetes | type 2 diabetes mellitus | 419,209 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002780/ScoringFiles/PGS002780.txt.gz | |
| PGS003089 (ExPRSweb_T2D_2443_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 488,969 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003089/ScoringFiles/PGS003089.txt.gz | |
| PGS003090 (ExPRSweb_T2D_2443_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,888 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003090/ScoringFiles/PGS003090.txt.gz | |
| PGS003091 (ExPRSweb_T2D_2443_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,707 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003091/ScoringFiles/PGS003091.txt.gz | |
| PGS003092 (ExPRSweb_T2D_2443_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 10,304,000 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003092/ScoringFiles/PGS003092.txt.gz | |
| PGS003093 (ExPRSweb_T2D_2443_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003093/ScoringFiles/PGS003093.txt.gz | |
| PGS003094 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 266,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003094/ScoringFiles/PGS003094.txt.gz | |
| PGS003095 (ExPRSweb_T2D_29358691-GCST005413_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 45 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003095/ScoringFiles/PGS003095.txt.gz | |
| PGS003096 (ExPRSweb_T2D_29358691-GCST005413_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 46 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003096/ScoringFiles/PGS003096.txt.gz | |
| PGS003097 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 229 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003097/ScoringFiles/PGS003097.txt.gz | |
| PGS003098 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,116,101 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003098/ScoringFiles/PGS003098.txt.gz | |
| PGS003099 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 555,512 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003099/ScoringFiles/PGS003099.txt.gz | |
| PGS003100 (ExPRSweb_T2D_30054458-GCST006867_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,693 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003100/ScoringFiles/PGS003100.txt.gz | |
| PGS003101 (ExPRSweb_T2D_30054458-GCST006867_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,693 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003101/ScoringFiles/PGS003101.txt.gz | |
| PGS003102 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,052,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003102/ScoringFiles/PGS003102.txt.gz | |
| PGS003103 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 945,820 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003103/ScoringFiles/PGS003103.txt.gz | |
| PGS003104 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 374,510 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003104/ScoringFiles/PGS003104.txt.gz | |
| PGS003105 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 187 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003105/ScoringFiles/PGS003105.txt.gz | |
| PGS003106 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 187 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003106/ScoringFiles/PGS003106.txt.gz | |
| PGS003107 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 995 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003107/ScoringFiles/PGS003107.txt.gz | |
| PGS003108 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,118,480 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003108/ScoringFiles/PGS003108.txt.gz | |
| PGS003109 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 311,565 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003109/ScoringFiles/PGS003109.txt.gz | |
| PGS003110 (ExPRSweb_T2D_29358691-GCST005413_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 118 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003110/ScoringFiles/PGS003110.txt.gz | |
| PGS003111 (ExPRSweb_T2D_29358691-GCST005413_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 143 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003111/ScoringFiles/PGS003111.txt.gz | |
| PGS003112 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 222 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003112/ScoringFiles/PGS003112.txt.gz | |
| PGS003113 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,117,087 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003113/ScoringFiles/PGS003113.txt.gz | |
| PGS003114 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 555,528 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003114/ScoringFiles/PGS003114.txt.gz | |
| PGS003115 (ExPRSweb_T2D_30054458-GCST006867_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 31,462 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003115/ScoringFiles/PGS003115.txt.gz | |
| PGS003116 (ExPRSweb_T2D_30054458-GCST006867_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 31,462 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003116/ScoringFiles/PGS003116.txt.gz | |
| PGS003117 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,052,993 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003117/ScoringFiles/PGS003117.txt.gz | |
| PGS003118 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 945,921 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003118/ScoringFiles/PGS003118.txt.gz | |
| PGS003119 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 407,553 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003119/ScoringFiles/PGS003119.txt.gz | |
| PGS003120 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 193 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003120/ScoringFiles/PGS003120.txt.gz | |
| PGS003121 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 193 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003121/ScoringFiles/PGS003121.txt.gz | |
| PGS003122 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 264 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003122/ScoringFiles/PGS003122.txt.gz | |
| PGS003123 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,119,522 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003123/ScoringFiles/PGS003123.txt.gz | |
| PGS003353 (GRS_T2D) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003353/ScoringFiles/PGS003353.txt.gz |
| PGS003385 (best_OV) |
PGP000413 | Namba S et al. Cancer Res (2022) |
Ovarian serous carcinoma | ovarian serous carcinoma | 144,810 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003385/ScoringFiles/PGS003385.txt.gz |
| PGS003394 (PRS_Stepwise) |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Epithelial ovarian cancer | ovarian carcinoma | 36 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003394/ScoringFiles/PGS003394.txt.gz | |
| PGS003402 (PRS_T2D) |
PGP000419 | Lamri A et al. Elife (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,838 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003402/ScoringFiles/PGS003402.txt.gz | |
| PGS003437 (PRS23_TC) |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |
Thyroid cancer | thyroid carcinoma | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003437/ScoringFiles/PGS003437.txt.gz |
| PGS003443 (PRScsx_T2D_LAT_EURweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,092,496 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003443/ScoringFiles/PGS003443.txt.gz | |
| PGS003444 (PRScsx_T2D_LAT_EASweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,001,579 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003444/ScoringFiles/PGS003444.txt.gz | |
| PGS003445 (PRScsx_T2D_LAT_LATweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,149,210 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003445/ScoringFiles/PGS003445.txt.gz | |
| PGS003728 (PS_T2D_183-AGEN) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 183 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003728/ScoringFiles/PGS003728.txt.gz |
| PGS003729 (PS_T2D_293-DIAGRAM) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003729/ScoringFiles/PGS003729.txt.gz |
| PGS003730 (PS_T2D_287-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003730/ScoringFiles/PGS003730.txt.gz |
| PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 282 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003731/ScoringFiles/PGS003731.txt.gz |
| PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003732/ScoringFiles/PGS003732.txt.gz |
| PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003733/ScoringFiles/PGS003733.txt.gz |
| PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003734/ScoringFiles/PGS003734.txt.gz |
| PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 276 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003735/ScoringFiles/PGS003735.txt.gz |
| PGS003741 (PRS28_OC) |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Ovarian cancer | ovarian carcinoma | 28 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003741/ScoringFiles/PGS003741.txt.gz | |
| PGS003742 (PRS19_PC) |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Pancreatic cancer | pancreatic neoplasm | 19 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003742/ScoringFiles/PGS003742.txt.gz | |
| PGS003746 (PRS11_TC) |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Thyroid cancer | thyroid carcinoma | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003746/ScoringFiles/PGS003746.txt.gz | |
| PGS003749 (ModelT1D_under25) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 6,612 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003749/ScoringFiles/PGS003749.txt.gz | |
| PGS003750 (ModelT1D) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 7,835 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003750/ScoringFiles/PGS003750.txt.gz | |
| PGS003751 (ModelT2D_over45) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 354 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003751/ScoringFiles/PGS003751.txt.gz | |
| PGS003752 (ModelT2D) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 333 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003752/ScoringFiles/PGS003752.txt.gz | |
| PGS003754 (PRS22_OCstepwise) |
PGP000474 | Hurwitz LM et al. JAMA Netw Open (2023) |
Nonmucinous Epithelial Ovarian Cancer | ovarian carcinoma | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003754/ScoringFiles/PGS003754.txt.gz |
| PGS003867 (T2D_PRScs_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,068,166 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003867/ScoringFiles/PGS003867.txt.gz |
| PGS003982 (dbslmm.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,071,764 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003982/ScoringFiles/PGS003982.txt.gz | |
| PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 63,182 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003993/ScoringFiles/PGS003993.txt.gz | |
| PGS003998 (lassosum.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,548 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003998/ScoringFiles/PGS003998.txt.gz | |
| PGS004009 (lassosum.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 4,031 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004009/ScoringFiles/PGS004009.txt.gz | |
| PGS004014 (lassosum.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 95,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004014/ScoringFiles/PGS004014.txt.gz | |
| PGS004020 (lassosum.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 6,682 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004020/ScoringFiles/PGS004020.txt.gz | |
| PGS004024 (ldpred2.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 958,046 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004024/ScoringFiles/PGS004024.txt.gz | |
| PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,562 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004035/ScoringFiles/PGS004035.txt.gz | |
| PGS004039 (ldpred2.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 958,046 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004039/ScoringFiles/PGS004039.txt.gz | |
| PGS004052 (megaprs.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 800,598 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004052/ScoringFiles/PGS004052.txt.gz | |
| PGS004063 (megaprs.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,288 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004063/ScoringFiles/PGS004063.txt.gz | |
| PGS004068 (megaprs.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 800,598 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004068/ScoringFiles/PGS004068.txt.gz | |
| PGS004078 (megaprs.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,288 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004078/ScoringFiles/PGS004078.txt.gz | |
| PGS004082 (prscs.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,043,329 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004082/ScoringFiles/PGS004082.txt.gz | |
| PGS004093 (prscs.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 61,651 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004093/ScoringFiles/PGS004093.txt.gz | |
| PGS004102 (prscs.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 61,651 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004102/ScoringFiles/PGS004102.txt.gz | |
| PGS004106 (pt_clump.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 35 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004106/ScoringFiles/PGS004106.txt.gz | |
| PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 131 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004117/ScoringFiles/PGS004117.txt.gz | |
| PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 297 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004122/ScoringFiles/PGS004122.txt.gz | |
| PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 354 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004132/ScoringFiles/PGS004132.txt.gz | |
| PGS004136 (sbayesr.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 930,497 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004136/ScoringFiles/PGS004136.txt.gz | |
| PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 45,996 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004147/ScoringFiles/PGS004147.txt.gz | |
| PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,071,786 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004152/ScoringFiles/PGS004152.txt.gz | |
| PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 62,645 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004162/ScoringFiles/PGS004162.txt.gz | |
| PGS004171 (t1d_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 520 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004171/ScoringFiles/PGS004171.txt.gz |
| PGS004172 (t1d_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 70 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004172/ScoringFiles/PGS004172.txt.gz |
| PGS004173 (t1d_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 295 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004173/ScoringFiles/PGS004173.txt.gz |
| PGS004174 (t1d_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 49 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004174/ScoringFiles/PGS004174.txt.gz |
| PGS004175 (t1d_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 315 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004175/ScoringFiles/PGS004175.txt.gz |
| PGS004181 (t2d_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 10,202 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004181/ScoringFiles/PGS004181.txt.gz |
| PGS004182 (t2d_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 10,778 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004182/ScoringFiles/PGS004182.txt.gz |
| PGS004183 (t2d_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 8,154 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004183/ScoringFiles/PGS004183.txt.gz |
| PGS004184 (t2d_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 9,645 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004184/ScoringFiles/PGS004184.txt.gz |
| PGS004185 (t2d_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 3,277 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004185/ScoringFiles/PGS004185.txt.gz |
| PGS004223 (PRS139_T2D) |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 139 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004223/ScoringFiles/PGS004223.txt.gz |
| PGS004225 (PRS46_T2DEastAsia) |
PGP000526 | Liu J et al. Nutrients (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 46 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004225/ScoringFiles/PGS004225.txt.gz |
| PGS004226 (PRS50_T2DEur) |
PGP000526 | Liu J et al. Nutrients (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 50 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004226/ScoringFiles/PGS004226.txt.gz |
| PGS004239 (PRS14AAD) |
PGP000538 | Aranda-Guillén M et al. J Intern Med (2023) |
Autoimmune Addison's disease | chronic primary adrenal insufficiency | 14 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004239/ScoringFiles/PGS004239.txt.gz | |
| PGS004249 (PRS25_ovary) |
PGP000542 | Kim ES et al. NPJ Precis Oncol (2023) |
Ovarian cancer | ovarian carcinoma | 25 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004249/ScoringFiles/PGS004249.txt.gz |
| PGS004250 (PRS19_pancreas) |
PGP000542 | Kim ES et al. NPJ Precis Oncol (2023) |
Pancreatic cancer | pancreatic carcinoma | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004250/ScoringFiles/PGS004250.txt.gz |
| PGS004323 (PRS91_T2D) |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 91 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004323/ScoringFiles/PGS004323.txt.gz |
| PGS004446 (disease.E03.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E03 (Other hypothyroidism) | hypothyroidism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004446/ScoringFiles/PGS004446.txt.gz |
| PGS004499 (disease.T2D.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004499/ScoringFiles/PGS004499.txt.gz |
| PGS004516 (meta.E03.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E03 (Other hypothyroidism) | hypothyroidism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004516/ScoringFiles/PGS004516.txt.gz |
| PGS004569 (meta.T2D.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004569/ScoringFiles/PGS004569.txt.gz |
| PGS004602 (PRS424_T2D) |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 424 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004602/ScoringFiles/PGS004602.txt.gz |
| PGS004692 (ovarian_cancer) |
PGP000596 | Hu J et al. JNCI Cancer Spectr (2024) |
Ovarian cancer | ovarian carcinoma | 6,385,666 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004692/ScoringFiles/PGS004692.txt.gz | |
| PGS004693 (pancreatic_cancer) |
PGP000596 | Hu J et al. JNCI Cancer Spectr (2024) |
Pancreatic cancer | pancreatic carcinoma | 6,351,686 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004693/ScoringFiles/PGS004693.txt.gz | |
| PGS004789 (hypothyroid_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypothyroidism | hypothyroidism | 1,109,333 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004789/ScoringFiles/PGS004789.txt.gz |
| PGS004790 (hypothyroid_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypothyroidism | hypothyroidism | 1,841,655 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004790/ScoringFiles/PGS004790.txt.gz |
| PGS004837 (t2d_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 3,306,136 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004837/ScoringFiles/PGS004837.txt.gz |
| PGS004838 (t2d_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,586,458 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004838/ScoringFiles/PGS004838.txt.gz |
| PGS004839 (t2d_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 4,594,694 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004839/ScoringFiles/PGS004839.txt.gz |
| PGS004840 (t2d_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,586,458 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004840/ScoringFiles/PGS004840.txt.gz |
| PGS004859 (T2D_PRS_CS) |
PGP000605 | Deutsch AJ et al. Diabetes Care (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,108,235 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004859/ScoringFiles/PGS004859.txt.gz |
| PGS004868 (T2DPGS) |
PGP000617 | Yun JS et al. Cardiovasc Diabetol (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,580,804 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004868/ScoringFiles/PGS004868.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000023 | PGS000014 (GPS_T2D) |
PSS000017| European Ancestry| 288,978 individuals |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.73 [0.72, 0.73] | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment): 0.029 | age; sex; Ancestry PC 1-4; genotyping chip | — |
| PPM002477 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.709 [0.696, 0.722] | Hazard ratio (HR, top 10% vs. remaining 90%): 2.0 [1.73, 2.31] | Sex, age, principal components, assessment center | — |
| PPM002478 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.68 [0.663, 0.697] | — | Age, principal components and assessment center | — |
| PPM002479 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.705 [0.682, 0.728] | — | Age, principal components and assessment center | — |
| PPM002480 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.776 [0.764, 0.788] | — | Sex, age, principal components, assessment center, polyexposure score | — |
| PPM002481 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.844 [0.834, 0.854] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002482 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.855 [0.845, 0.865] | — | Sex, age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM002483 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.786 [0.765, 0.807] | — | Age, principal components, assessment center, polyexposure score | — |
| PPM002485 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.859 [0.842, 0.876] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002486 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.749 [0.734, 0.764] | — | Age, principal components, assessment center, polyexposure score | — |
| PPM002487 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.821 [0.808, 0.834] | — | Age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM002488 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.834 [0.821, 0.847] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002484 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.869 [0.853, 0.885] | — | Age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM015522 | PGS000014 (GPS_T2D) |
PSS009971| Multi-ancestry (including European)| 36,422 individuals |
PGP000381 | Hao L et al. Nat Med (2022) |Ext. |
Reported Trait: Type 2 diabetes mellitus | OR: 1.75 [1.57, 1.95] | — | — | 4 genetic PCs | — |
| PPM019100 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | — | AUROC: 0.613 [0.565, 0.657] | — | — | — |
| PPM019098 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | OR: 1.67 [1.37, 2.03] | — | — | Age, Sex, BMI, Physical activity, FamRS | — |
| PPM019099 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Prevelant type 2 diabetes | — | AUROC: 0.869 [0.842, 0.896] | — | — | — |
| PPM019097 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Prevelant type 2 diabetes | OR: 6.21 [5.06, 7.74] | — | — | Age, Sex, BMI, Physical activity, FamRS | — |
| PPM000040 | PGS000020 (dGRS1000) |
PSS000025| European Ancestry| 6,280 individuals |
PGP000010 | Läll K et al. Genet Med (2016) |
Reported Trait: Incident type 2 diabetes | HR: 1.48 [1.32, 1.66] | C-index: 0.79 [0.771, 0.812] | — | BMI category, smoking level, waist-to-hip ratio, waist circumference, physical activity level, history of high blood glucose, fruit and vegetable consumption, and sex. | Cox age-as-time-scale |
| PPM000132 | PGS000021 (GRS1) |
PSS000083| European Ancestry| 2,768 individuals |
PGP000038 | Patel KA et al. Diabetes (2016) |Ext. |
Reported Trait: Type 1 diabetes aetiology (non-monogenic) | — | AUROC: 0.87 [0.86, 0.89] | — | — | Testing the ability of the GRS to discriminate between two sets of cases: - Positive: individuals with type 1 diabetes - Negative: individuals with diabetes and a maturity-onset diabetes of young (MODY) mutation |
| PPM000041 | PGS000021 (GRS1) |
PSS000026| European Ancestry| 223 individuals |
PGP000011 | Oram RA et al. Diabetes Care (2015) |
Reported Trait: Severe insulin deficiency | — | AUROC: 0.96 [0.94, 0.99] | AUROC (without covariates): 0.87 | islet auto-antibody status, body mass index (BMI), age at diagnosis | — |
| PPM000046 | PGS000021 (GRS1) |
PSS000030| African Ancestry| 3,949 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.798 | — | — | — |
| PPM000049 | PGS000021 (GRS1) |
PSS000032| European Ancestry| 374,000 individuals |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.893 | — | — | — |
| PPM000042 | PGS000022 (T1D_GRS) |
PSS000029| European Ancestry| 1,447 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.8508 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000043 | PGS000022 (T1D_GRS) |
PSS000028| Hispanic or Latin American Ancestry| 252 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.9003 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000044 | PGS000022 (T1D_GRS) |
PSS000027| African Ancestry| 299 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7522 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000045 | PGS000023 (AA_GRS) |
PSS000030| African Ancestry| 3,949 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.87 | — | — | NOTE: Evaluated using cross-validation on training samples (20% heldout, 1000 iterations) |
| PPM000047 | PGS000023 (AA_GRS) |
PSS000031| African Ancestry| 145 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.779 | — | — | — |
| PPM018536 | PGS000023 (AA_GRS) |
PSS011012| Multi-ancestry (including European)| 39,820 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.781 | — | — | — |
| PPM018537 | PGS000023 (AA_GRS) |
PSS011009| Multi-ancestry (including European)| 57,643 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.817 | — | — | — |
| PPM018539 | PGS000023 (AA_GRS) |
PSS011011| European Ancestry| 16,663 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 97.0 % PPV (reference): 86.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018541 | PGS000023 (AA_GRS) |
PSS011010| Multi-ancestry (excluding European)| 40,980 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 86.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018543 | PGS000023 (AA_GRS) |
PSS011013| Multi-ancestry (excluding European)| 4,881 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 83.0 % PPV (reference): 53.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM000048 | PGS000024 (GRS2) |
PSS000032| European Ancestry| 374,000 individuals |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.921 | Youden index: 0.698 | — | — |
| PPM000753 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (5 years horizon time; landmark age 2 years) | — | AUROC: 0.93 | — | autoantibodies, family history | — |
| PPM000754 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (8 years horizon time; landmark age 2 years) | — | AUROC: 0.87 | — | autoantibodies, family history | — |
| PPM000755 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (5 years horizon time; landmark age 4 years) | — | AUROC: 0.96 | — | autoantibodies, family history | — |
| PPM000751 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (1 year horizon time; landmark age 2 years) | — | AUROC: 0.96 | — | autoantibodies, family history | — |
| PPM000752 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (3 years horizon time; landmark age 2 years) | — | AUROC: 0.94 | — | autoantibodies, family history | — |
| PPM000750 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (by age 8; landmark age 2 years) | — | AUROC: 0.73 [0.7, 0.77] | — | — | — |
| PPM002249 | PGS000024 (GRS2) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002250 | PGS000024 (GRS2) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002251 | PGS000024 (GRS2) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.01 [0.95, 1.08] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002252 | PGS000024 (GRS2) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.99 [0.94, 1.04] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002248 | PGS000024 (GRS2) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Autoimmune Diabetes | OR: 2.55 [2.28, 2.86] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM014801 | PGS000024 (GRS2) |
PSS009895| European Ancestry| 1,168 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.864 [0.823, 0.905] | — | — | — |
| PPM014803 | PGS000024 (GRS2) |
PSS009893| African Ancestry| 366 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.851 [0.805, 0.897] | — | — | — |
| PPM014805 | PGS000024 (GRS2) |
PSS009894| Hispanic or Latin American Ancestry| 412 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.935 [0.906, 0.964] | — | — | — |
| PPM014807 | PGS000024 (GRS2) |
PSS009896| Ancestry Not Reported| 99 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.79 [0.679, 0.902] | — | — | — |
| PPM018532 | PGS000024 (GRS2) |
PSS011012| Multi-ancestry (including European)| 39,820 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.875 | — | — | — |
| PPM018533 | PGS000024 (GRS2) |
PSS011009| Multi-ancestry (including European)| 57,643 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.822 | — | — | — |
| PPM018534 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.888 | — | — | — |
| PPM018535 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.858 | — | — | — |
| PPM018538 | PGS000024 (GRS2) |
PSS011011| European Ancestry| 16,663 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 100.0 % PPV (reference): 86.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018540 | PGS000024 (GRS2) |
PSS011010| Multi-ancestry (excluding European)| 40,980 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 93.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018542 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 97.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM020098 | PGS000024 (GRS2) |
PSS011295| Ancestry Not Reported| 1,798 individuals |
PGP000519 | Thomas NJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes vs autoantibody negative T2D | — | — | p-value (inferior to): 0.0001 | — | — |
| PPM021124 | PGS000024 (GRS2) |
PSS011531| European Ancestry| 9,465 individuals |
PGP000614 | Qu HQ et al. Diabetes Obes Metab (2021) |Ext. |
Reported Trait: Type 1 diabetes | β: -0.22 | AUROC: 0.87 | — | — | — |
| PPM021125 | PGS000024 (GRS2) |
PSS011532| European Ancestry| 9,450 individuals |
PGP000614 | Qu HQ et al. Diabetes Obes Metab (2021) |Ext. |
Reported Trait: Type 1 diabetes | β: -0.234 | AUROC: 0.862 | — | — | — |
| PPM000062 | PGS000031 (GRSt) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [1.04, 1.08] | C-index: 0.906 [0.892, 0.92] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000063 | PGS000031 (GRSt) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [1.02, 1.1] | C-index: 0.853 [0.81, 0.896] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000064 | PGS000031 (GRSt) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.05 [1.0, 1.09] | C-index: 0.771 [0.727, 0.814] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM000065 | PGS000032 (GRSB) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.1 [1.06, 1.14] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000066 | PGS000032 (GRSB) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.09 [1.02, 1.17] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000067 | PGS000032 (GRSB) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [0.99, 1.15] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM002415 | PGS000032 (GRSB) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |Ext. |
Reported Trait: Cystic-fibrosis related diabetes onset | HR: 1.192 | — | — | PCs(1-4), site of recruitment | — |
| PPM000068 | PGS000033 (GRSIR) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 0.98 [0.93, 1.04] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000069 | PGS000033 (GRSIR) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.01 [0.91, 1.12] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000070 | PGS000033 (GRSIR) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [0.99, 1.15] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM000080 | PGS000036 (gePS_T2D) |
PSS000054| European Ancestry| 324,870 individuals |
PGP000024 | Udler MS et al. Endocr Rev (2019) |Ext. |
Reported Trait: Type 2 diabetes | — | AUROC: 0.66 | — | genotyping array, first 6 PCs of ancestry | — |
| PPM000081 | PGS000036 (gePS_T2D) |
PSS000054| European Ancestry| 324,870 individuals |
PGP000024 | Udler MS et al. Endocr Rev (2019) |Ext. |
Reported Trait: Type 2 diabetes | — | AUROC: 0.73 | — | age, sex, genotyping array, first 6 PCs of ancestry | — |
| PPM014802 | PGS000036 (gePS_T2D) |
PSS009895| European Ancestry| 1,168 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.661 [0.606, 0.716] | — | — | — |
| PPM014804 | PGS000036 (gePS_T2D) |
PSS009893| African Ancestry| 366 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.574 [0.506, 0.643] | — | — | — |
| PPM014806 | PGS000036 (gePS_T2D) |
PSS009894| Hispanic or Latin American Ancestry| 412 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.722 [0.667, 0.778] | — | — | — |
| PPM014808 | PGS000036 (gePS_T2D) |
PSS009896| Ancestry Not Reported| 99 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.677 [0.532, 0.822] | — | — | — |
| PPM000112 | PGS000048 (OCPRS_Overall) |
PSS000072| European Ancestry| 15,252 individuals |
PGP000033 | Kuchenbaecker KB et al. J Natl Cancer Inst (2017) |
Reported Trait: Ovarian cancer in BRCA1 mutation carriers | HR: 1.28 [1.22, 1.34] | C-index: 0.579 [0.559, 0.6] | — | Country, birth year | — |
| PPM000113 | PGS000048 (OCPRS_Overall) |
PSS000073| European Ancestry| 8,211 individuals |
PGP000033 | Kuchenbaecker KB et al. J Natl Cancer Inst (2017) |
Reported Trait: Ovarian cancer in BRCA2 mutation carriers | HR: 1.49 [1.34, 1.65] | C-index: 0.628 [0.592, 0.665] | — | Country, birth year | — |
| PPM000188 | PGS000068 (PRS_EOC) |
PSS000108| European Ancestry| 4,095 individuals |
PGP000048 | Yang X et al. J Med Genet (2018) |
Reported Trait: all invasive epithelial ovarian cancer | OR: 1.32 [1.21, 1.45] | C-index: 0.58 [0.55, 0.6] | — | — | — |
| PPM000189 | PGS000069 (PRS_sEOC) |
PSS000108| European Ancestry| 4,095 individuals |
PGP000048 | Yang X et al. J Med Genet (2018) |
Reported Trait: serous epithelial ovarian cancer | OR: 1.43 [1.29, 1.58] | C-index: 0.6 [0.57, 0.63] | — | — | — |
| PPM000202 | PGS000082 (CC_Ovary) |
PSS000121| European Ancestry| 220,909 individuals |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Reported Trait: Ovarian cancer | OR: 1.14 [1.08, 1.2] | — | — | Genotyping reagent kit (GERA cohort only), genotyping array (UK Biobank only), age, 10 PCs. | Results from meta-analysis of GERA and UKB |
| PPM002048 | PGS000082 (CC_Ovary) |
PSS001021| European Ancestry| 211,958 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |Ext. |
Reported Trait: Incident ovarian cancer | HR: 1.13 [1.04, 1.24] | AUROC: 0.656 C-index: 0.655 (0.015) |
— | Age at assessment, family history of breast cancer, genotyping array, PCs(1-15), parity ( ≥1 live birth vs. none), body mass index, Menopausal status (pre-menopausal vs. post-menopausal vs. unknown or hysterectomy), ever used hormone replacement therapy, oral contraceptive use (never used (0) vs. <20 years vs. ≥20 years), BMI*menopausal status | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM017174 | PGS000082 (CC_Ovary) |
PSS010149| European Ancestry| 315 individuals |
PGP000443 | Byrne S et al. Int J Epidemiol (2023) |Ext. |
Reported Trait: Ovarian cancer | HR: 1.09 [0.97, 1.21] | — | — | age at baseline, sex (where relevant), assessment centre, 40 principal components of ancestries (PCs), Townsend Index, education, birth location, income, lifestyle index, additional cancer-specific covariates | — |
| PPM000203 | PGS000083 (CC_Pancreas) |
PSS000122| European Ancestry| 411,019 individuals |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Reported Trait: Pancreatic cancer | OR: 1.44 [1.33, 1.55] | — | — | Genotyping reagent kit (GERA cohort only), genotyping array (UK Biobank only), age, sex, 10 PCs. | Results from meta-analysis of GERA and UKB |
| PPM002049 | PGS000083 (CC_Pancreas) |
PSS001022| European Ancestry| 391,491 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |Ext. |
Reported Trait: Incident pancreatic cancer | HR: 1.49 [1.36, 1.62] | AUROC: 0.745 C-index: 0.742 (0.012) |
— | Age at assessment, sex, genotyping array, PCs(1-15), family history of cancer (prostate, breast, lung, bowel), body mass index, cigarette pack-years, smoking status (never vs. former vs. current) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM017171 | PGS000083 (CC_Pancreas) |
PSS010154| European Ancestry| 451 individuals |
PGP000443 | Byrne S et al. Int J Epidemiol (2023) |Ext. |
Reported Trait: Pancreatic cancer | HR: 1.51 [1.38, 1.66] | — | — | age at baseline, sex (where relevant), assessment centre, 40 principal components of ancestries (PCs), Townsend Index, education, birth location, income, lifestyle index, additional cancer-specific covariates | — |
| PPM000206 | PGS000086 (CC_Testis) |
PSS000125| European Ancestry| 170,680 individuals |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Reported Trait: Testicular cancer | OR: 2.29 [2.13, 2.47] | — | — | Genotyping array, age, 10 PCs. | — |
| PPM002051 | PGS000086 (CC_Testis) |
PSS001024| European Ancestry| 179,537 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |Ext. |
Reported Trait: Incident testicular cancer | HR: 2.18 [1.66, 2.87] | AUROC: 0.783 C-index: 0.749 (0.034) |
— | Age at assessment, genotyping array, PCs(1-15) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM000207 | PGS000087 (CC_Thyroid) |
PSS000126| European Ancestry| 411,118 individuals |
PGP000050 | Graff RE et al. Nat Commun (2021) |
Reported Trait: Thyroid cancer | OR: 1.55 [1.44, 1.67] | — | — | Genotyping reagent kit (GERA cohort only), genotyping array (UK Biobank only), age, sex, 10 PCs. | Results from meta-analysis of GERA and UKB |
| PPM002052 | PGS000087 (CC_Thyroid) |
PSS001025| European Ancestry| 391,189 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |Ext. |
Reported Trait: Incident thyroid cancer | HR: 1.57 [1.36, 1.82] | AUROC: 0.679 C-index: 0.666 (0.023) |
— | Age at assessment, sex,, genotyping array, PCs(1-15), body mass index (BMI <25 vs. 25≤BMI<30, BMI≥30) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM000404 | PGS000125 (Qi_T2D_2017) |
PSS000232| Hispanic or Latin American Ancestry| 7,746 individuals |
PGP000062 | Qi Q et al. Diabetes (2017) |
Reported Trait: Type 2 Diabetes | — | — | OR (Odds Ratio, per risk allele): 1.07 [1.06, 1.08] | center, age, sex, 5 PCs of ancestry | Covariance matrices corresponding to genetic relatedness (kinship), household, and census block group were included as random effects in the mixed model analysis |
| PPM000489 | PGS000158 (cGRS_Ovarian) |
PSS000278| European Ancestry| 7,551 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Ovarian cancer | — | — | Odds Ratio (OR; high vs. average risk groups): 1.63 [1.3, 2.06] | — | — |
| PPM000478 | PGS000158 (cGRS_Ovarian) |
PSS000278| European Ancestry| 7,551 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Ovarian cancer | — | — | Mean realative risk: 1.12 [1.08, 1.16] Wilcoxon test (case vs. control) p-value: 0.00015 |
— | — |
| PPM000490 | PGS000159 (cGRS_Pancreatic) |
PSS000279| European Ancestry| 13,590 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Pancreatic cancer | — | — | Odds Ratio (OR; high vs. average risk groups): 1.67 [1.1, 2.53] | — | — |
| PPM000479 | PGS000159 (cGRS_Pancreatic) |
PSS000279| European Ancestry| 13,590 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Pancreatic cancer | — | — | Mean realative risk: 1.13 [1.07, 1.18] Wilcoxon test (case vs. control) p-value: 0.00015 |
— | — |
| PPM000493 | PGS000162 (cGRS_Thyroid) |
PSS000282| European Ancestry| 13,814 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Thyroid cancer | — | — | Odds Ratio (OR; high vs. average risk groups): 1.7 [1.29, 2.25] | — | — |
| PPM000482 | PGS000162 (cGRS_Thyroid) |
PSS000282| European Ancestry| 13,814 individuals |
PGP000075 | Shi Z et al. Cancer Med (2019) |
Reported Trait: Thyroid cancer | — | — | Mean realative risk: 1.09 [1.04, 1.15] Wilcoxon test (case vs. control) p-value: 4e-05 |
— | — |
| PPM000631 | PGS000207 (TC10_Ohio) |
PSS000342| European Ancestry| 3,137 individuals |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Reported Trait: Thyroid cancer | — | AUROC: 0.692 [0.673, 0.71] | — | gender, birth year, family history of disease (1st or 2nd degree relative) | AUROC (Clinical factors alone) = 0.585 [0.565 - 0.605] |
| PPM017146 | PGS000207 (TC10_Ohio) |
PSS010136| European Ancestry| 264,956 individuals |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |Ext. |
Reported Trait: Thyroid cancer | HR: 1.74 [1.56, 1.94] | AUROC: 0.62 [0.59, 0.64] | — | age, sex, and genetic composition, townsend deprivation index at recruitment, qualifications and average total household income before tax | — |
| PPM000632 | PGS000208 (TC10_Iceland) |
PSS000341| European Ancestry| 130,279 individuals |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Reported Trait: Thyroid cancer | — | AUROC: 0.751 [0.736, 0.768] | — | gender, birth year, family history of disease (1st or 2nd degree relative) | AUROC (Clinical factors alone) = 0.697 [0.680 - 0.714] |
| PPM000633 | PGS000209 (TC10_UKB) |
PSS000343| European Ancestry| 408,479 individuals |
PGP000085 | Liyanarachchi S et al. Proc Natl Acad Sci U S A (2020) |
Reported Trait: Thyroid cancer | — | AUROC: 0.694 [0.673, 0.716] | — | gender, birth year | AUROC (Clinical factors alone) = 0.629 [0.606 - 0.651] |
| PPM000897 | PGS000330 (PRS_T2D) |
PSS000441| European Ancestry| 21,030 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident type 2 diabetes | — | C-index: 0.845 | — | age, sex, BMI, history of stroke or CHD, parental history of diabetes, SBP, DBP, HDL, triglycerides, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000892 | PGS000330 (PRS_T2D) |
PSS000441| European Ancestry| 21,030 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident type 2 diabetes | HR: 1.7 [1.63, 1.78] | C-index: 0.763 | — | age, sex, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000887 | PGS000330 (PRS_T2D) |
PSS000448| European Ancestry| 135,300 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Type 2 diabetes (incident and prevalent cases) | HR: 1.74 [1.72, 1.77] | — | — | genotyping array/batch, 10 ancestry PCs, stratified by sex | — |
| PPM001030 | PGS000351 (PRS_EOC) |
PSS000524| European Ancestry| 18,935 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Ovarian cancer in BRCA1 carriers | HR: 1.31 [1.24, 1.39] | — | — | birth cohort, PCs(1-4) of ancestry, family history in first- and second-degree relatives | — |
| PPM001031 | PGS000351 (PRS_EOC) |
PSS000528| European Ancestry| 12,339 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Ovarian cancer in BRCA2 carriers | HR: 1.42 [1.28, 1.58] | — | — | birth cohort, PCs(1-4) of ancestry, family history in first- and second-degree relatives | — |
| PPM001032 | PGS000352 (PRS_HGS) |
PSS000524| European Ancestry| 18,935 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Ovarian cancer in BRCA1 carriers | HR: 1.32 [1.25, 1.4] | — | — | birth cohort, PCs(1-4) of ancestry, family history in first- and second-degree relatives | — |
| PPM001033 | PGS000352 (PRS_HGS) |
PSS000528| European Ancestry| 12,339 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Ovarian cancer in BRCA2 carriers | HR: 1.43 [1.29, 1.59] | — | — | birth cohort, PCs(1-4) of ancestry, family history in first- and second-degree relatives | — |
| PPM001036 | PGS000352 (PRS_HGS) |
PSS000530| European Ancestry| 3,152 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Incident ovarian cancer in BRCA1 carriers | HR: 1.28 [1.06, 1.55] | — | — | family history of the appropriate cancer in first- and second-degree relatives | — |
| PPM001037 | PGS000352 (PRS_HGS) |
PSS000532| European Ancestry| 2,495 individuals |
PGP000117 | Barnes DR et al. Genet Med (2020) |
Reported Trait: Incident ovarian cancer in BRCA2 carriers | HR: 1.45 [1.13, 1.86] | — | — | family history of the appropriate cancer in first- and second-degree relatives | — |
| PPM001070 | PGS000385 (PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_P_5e-08_UKB_20200608) |
PSS000565| European Ancestry| 3,591 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Pancreatic cancer | OR: 1.384 [1.235, 1.552] β: 0.325 (0.0583) |
AUROC: 0.589 [0.559, 0.622] | Nagelkerke's Pseudo-R²: 0.019 Brier score: 0.082 Odds Ratio (OR, top 1% vs. Rest): 2.58 [1.19, 5.57] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_P_5e-08_UKB_20200608 |
| PPM001071 | PGS000386 (PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_PT_UKB_20200608) |
PSS000565| European Ancestry| 3,591 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Pancreatic cancer | OR: 1.342 [1.199, 1.503] β: 0.294 (0.0577) |
AUROC: 0.579 [0.548, 0.611] | Nagelkerke's Pseudo-R²: 0.0157 Brier score: 0.0822 Odds Ratio (OR, top 1% vs. Rest): 1.64 [0.655, 4.12] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE157_GWAS-Catalog-r2019-05-03-X157_PT_UKB_20200608 |
| PPM001229 | PGS000544 (PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_P_5e-08_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.12 [1.021, 1.23] β: 0.114 (0.0475) |
AUROC: 0.532 [0.506, 0.559] | Nagelkerke's Pseudo-R²: 0.00239 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 0.923 [0.347, 2.45] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_P_5e-08_UKB_20200608 |
| PPM001230 | PGS000545 (PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_PT_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.12 [1.021, 1.23] β: 0.114 (0.0475) |
AUROC: 0.532 [0.506, 0.559] | Nagelkerke's Pseudo-R²: 0.00239 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 0.923 [0.347, 2.45] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_GWAS-Catalog-r2019-05-03-X184.11_PT_UKB_20200608 |
| PPM001231 | PGS000546 (PRSWEB_PHECODE184.11_Phelan-ENOC_PRS-CS_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.119 [1.017, 1.231] β: 0.112 (0.0488) |
AUROC: 0.526 [0.498, 0.554] | Nagelkerke's Pseudo-R²: 0.00221 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 1.97 [0.973, 4.0] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-ENOC_PRS-CS_UKB_20200608 |
| PPM001232 | PGS000547 (PRSWEB_PHECODE184.11_Phelan-EPOC_P_5e-08_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.156 [1.051, 1.27] β: 0.145 (0.0482) |
AUROC: 0.544 [0.517, 0.573] | Nagelkerke's Pseudo-R²: 0.00379 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 0.922 [0.347, 2.45] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-EPOC_P_5e-08_UKB_20200608 |
| PPM001233 | PGS000548 (PRSWEB_PHECODE184.11_Phelan-EPOC_LASSOSUM_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.132 [1.03, 1.244] β: 0.124 (0.0483) |
AUROC: 0.538 [0.512, 0.565] | Nagelkerke's Pseudo-R²: 0.00277 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 1.13 [0.463, 2.77] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-EPOC_LASSOSUM_UKB_20200608 |
| PPM001234 | PGS000549 (PRSWEB_PHECODE184.11_Phelan-IEOC_P_5e-08_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.263 [1.15, 1.387] β: 0.234 (0.0479) |
AUROC: 0.567 [0.539, 0.595] | Nagelkerke's Pseudo-R²: 0.00996 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.839, 3.69] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-IEOC_P_5e-08_UKB_20200608 |
| PPM001235 | PGS000550 (PRSWEB_PHECODE184.11_Phelan-IEOC_PRS-CS_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.286 [1.169, 1.414] β: 0.251 (0.0485) |
AUROC: 0.568 [0.542, 0.595] | Nagelkerke's Pseudo-R²: 0.0113 Brier score: 0.0823 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.838, 3.7] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-IEOC_PRS-CS_UKB_20200608 |
| PPM001236 | PGS000551 (PRSWEB_PHECODE184.11_Phelan-IEOC_PT_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.234 [1.125, 1.354] β: 0.21 (0.0473) |
AUROC: 0.558 [0.53, 0.586] | Nagelkerke's Pseudo-R²: 0.00819 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 1.55 [0.71, 3.38] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-IEOC_PT_UKB_20200608 |
| PPM001237 | PGS000552 (PRSWEB_PHECODE184.11_Phelan-IEOC_LASSOSUM_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.19 [1.084, 1.308] β: 0.174 (0.048) |
AUROC: 0.552 [0.523, 0.58] | Nagelkerke's Pseudo-R²: 0.00552 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 1.97 [0.97, 3.99] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-IEOC_LASSOSUM_UKB_20200608 |
| PPM001238 | PGS000553 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_P_5e-08_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.188 [1.079, 1.308] β: 0.172 (0.0491) |
AUROC: 0.556 [0.53, 0.584] | Nagelkerke's Pseudo-R²: 0.00531 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.839, 3.69] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-LSASBOC_P_5e-08_UKB_20200608 |
| PPM001239 | PGS000554 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_PRS-CS_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.11 [1.009, 1.221] β: 0.104 (0.0486) |
AUROC: 0.522 [0.491, 0.548] | Nagelkerke's Pseudo-R²: 0.00193 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 3.92 [2.27, 6.79] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-LSASBOC_PRS-CS_UKB_20200608 |
| PPM001240 | PGS000555 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_PT_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.133 [1.03, 1.245] β: 0.125 (0.0483) |
AUROC: 0.539 [0.513, 0.568] | Nagelkerke's Pseudo-R²: 0.00282 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 2.18 [1.11, 4.3] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-LSASBOC_PT_UKB_20200608 |
| PPM001241 | PGS000556 (PRSWEB_PHECODE184.11_Phelan-LSASBOC_LASSOSUM_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.122 [1.022, 1.233] β: 0.116 (0.0478) |
AUROC: 0.516 [0.489, 0.544] | Nagelkerke's Pseudo-R²: 0.00242 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 2.4 [1.24, 4.62] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-LSASBOC_LASSOSUM_UKB_20200608 |
| PPM001242 | PGS000557 (PRSWEB_PHECODE184.11_Phelan-OCCC_PRS-CS_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.149 [1.045, 1.262] β: 0.139 (0.048) |
AUROC: 0.534 [0.508, 0.562] | Nagelkerke's Pseudo-R²: 0.00348 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 1.55 [0.71, 3.38] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-OCCC_PRS-CS_UKB_20200608 |
| PPM001243 | PGS000558 (PRSWEB_PHECODE184.11_Phelan-OCCC_LASSOSUM_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.207 [1.102, 1.321] β: 0.188 (0.0463) |
AUROC: 0.546 [0.52, 0.574] | Nagelkerke's Pseudo-R²: 0.00676 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.839, 3.69] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-OCCC_LASSOSUM_UKB_20200608 |
| PPM001244 | PGS000559 (PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_MGI_20200608) |
PSS000550| European Ancestry| 1,904 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.183 [1.015, 1.378] β: 0.168 (0.078) |
AUROC: 0.554 [0.509, 0.597] | Nagelkerke's Pseudo-R²: 0.00516 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 0.784 [0.142, 4.32] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_MGI_20200608 |
| PPM001245 | PGS000560 (PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.233 [1.125, 1.352] β: 0.21 (0.047) |
AUROC: 0.552 [0.523, 0.581] | Nagelkerke's Pseudo-R²: 0.00819 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.839, 3.69] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_P_5e-08_UKB_20200608 |
| PPM001246 | PGS000561 (PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_MGI_20200608) |
PSS000550| European Ancestry| 1,904 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.185 [1.011, 1.39] β: 0.17 (0.0812) |
AUROC: 0.552 [0.513, 0.598] | Nagelkerke's Pseudo-R²: 0.00517 Brier score: 0.0827 |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_MGI_20200608 |
| PPM001247 | PGS000562 (PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.209 [1.099, 1.329] β: 0.19 (0.0484) |
AUROC: 0.552 [0.526, 0.58] | Nagelkerke's Pseudo-R²: 0.00646 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 1.55 [0.708, 3.38] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_PRS-CS_UKB_20200608 |
| PPM001248 | PGS000563 (PRSWEB_PHECODE184.11_Phelan-SIOC_PT_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.192 [1.086, 1.308] β: 0.175 (0.0476) |
AUROC: 0.547 [0.52, 0.574] | Brier score: 0.0826 Nagelkerke's Pseudo-R²: 0.00564 Odds Ratio (OR, top 1% vs. Rest): 0.511 [0.142, 1.84] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_PT_UKB_20200608 |
| PPM001249 | PGS000564 (PRSWEB_PHECODE184.11_Phelan-SIOC_LASSOSUM_UKB_20200608) |
PSS000572| European Ancestry| 5,196 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of ovary | OR: 1.215 [1.106, 1.336] β: 0.195 (0.0481) |
AUROC: 0.556 [0.529, 0.583] | Nagelkerke's Pseudo-R²: 0.00692 Brier score: 0.0825 Odds Ratio (OR, top 1% vs. Rest): 1.76 [0.839, 3.69] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE184.11_Phelan-SIOC_LASSOSUM_UKB_20200608 |
| PPM001280 | PGS000595 (PRSWEB_PHECODE187.2_20001-1045_P_5e-08_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.713 [1.33, 2.206] β: 0.538 (0.129) |
AUROC: 0.658 [0.594, 0.719] | Nagelkerke's Pseudo-R²: 0.0543 Brier score: 0.0838 Odds Ratio (OR, top 1% vs. Rest): 2.64 [0.535, 13.0] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_20001-1045_P_5e-08_MGI_20200608 |
| PPM001281 | PGS000596 (PRSWEB_PHECODE187.2_20001-1045_PT_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.68 [1.28, 2.206] β: 0.519 (0.139) |
AUROC: 0.649 [0.586, 0.714] | Nagelkerke's Pseudo-R²: 0.0475 Brier score: 0.0841 Odds Ratio (OR, top 1% vs. Rest): 3.49 [0.816, 14.9] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_20001-1045_PT_MGI_20200608 |
| PPM001282 | PGS000597 (PRSWEB_PHECODE187.2_20001-1045_LASSOSUM_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.667 [1.296, 2.143] β: 0.511 (0.128) |
AUROC: 0.656 [0.593, 0.717] | Nagelkerke's Pseudo-R²: 0.0487 Brier score: 0.084 Odds Ratio (OR, top 1% vs. Rest): 2.72 [0.568, 13.1] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_20001-1045_LASSOSUM_MGI_20200608 |
| PPM001283 | PGS000598 (PRSWEB_PHECODE187.2_C3-TESTIS_P_5e-08_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.639 [1.263, 2.126] β: 0.494 (0.133) |
AUROC: 0.648 [0.581, 0.712] | Nagelkerke's Pseudo-R²: 0.0447 Brier score: 0.0841 Odds Ratio (OR, top 1% vs. Rest): 3.85 [0.942, 15.7] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_C3-TESTIS_P_5e-08_MGI_20200608 |
| PPM001284 | PGS000599 (PRSWEB_PHECODE187.2_C3-TESTIS_PT_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.628 [1.281, 2.069] β: 0.487 (0.122) |
AUROC: 0.637 [0.568, 0.703] | Nagelkerke's Pseudo-R²: 0.0473 Brier score: 0.0844 Odds Ratio (OR, top 1% vs. Rest): 4.35 [1.08, 17.5] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_C3-TESTIS_PT_MGI_20200608 |
| PPM001285 | PGS000600 (PRSWEB_PHECODE187.2_C3-TESTIS_LASSOSUM_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.619 [1.267, 2.067] β: 0.482 (0.125) |
AUROC: 0.636 [0.565, 0.698] | Nagelkerke's Pseudo-R²: 0.046 Brier score: 0.0839 Odds Ratio (OR, top 1% vs. Rest): 6.35 [1.81, 22.3] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_C3-TESTIS_LASSOSUM_MGI_20200608 |
| PPM001286 | PGS000601 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.438 [1.132, 1.827] β: 0.363 (0.122) |
AUROC: 0.598 [0.526, 0.672] | Nagelkerke's Pseudo-R²: 0.0258 Brier score: 0.085 |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_MGI_20200608 |
| PPM001287 | PGS000602 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_UKB_20200608) |
PSS000574| European Ancestry| 1,484 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 2.055 [1.692, 2.496] β: 0.72 (0.0993) |
AUROC: 0.698 [0.656, 0.74] | Nagelkerke's Pseudo-R²: 0.0839 Brier score: 0.0795 Odds Ratio (OR, top 1% vs. Rest): 4.6 [1.75, 12.1] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_P_5e-08_UKB_20200608 |
| PPM001288 | PGS000603 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_MGI_20200608) |
PSS000553| European Ancestry| 755 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 1.625 [1.27, 2.079] β: 0.485 (0.126) |
AUROC: 0.625 [0.557, 0.693] | Nagelkerke's Pseudo-R²: 0.044 Brier score: 0.084 Odds Ratio (OR, top 1% vs. Rest): 6.05 [1.73, 21.2] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_MGI_20200608 |
| PPM001289 | PGS000604 (PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_UKB_20200608) |
PSS000574| European Ancestry| 1,484 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Malignant neoplasm of testis | OR: 2.106 [1.729, 2.565] β: 0.745 (0.101) |
AUROC: 0.703 [0.659, 0.745] | Brier score: 0.0793 Nagelkerke's Pseudo-R²: 0.0882 Odds Ratio (OR, top 1% vs. Rest): 4.6 [1.75, 12.1] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE187.2_GWAS-Catalog-r2019-05-03-X187.2_PT_UKB_20200608 |
| PPM001311 | PGS000626 (PRSWEB_PHECODE193_20001-1065_PT_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.161 [1.048, 1.285] β: 0.149 (0.052) |
AUROC: 0.529 [0.496, 0.559] | Nagelkerke's Pseudo-R²: 0.0041 Brier score: 0.0826 Odds Ratio (OR, top 1% vs. Rest): 2.44 [1.18, 5.02] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_20001-1065_PT_MGI_20200608 |
| PPM001312 | PGS000627 (PRSWEB_PHECODE193_C3-THYROID-GLAND_PT_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.27 [1.148, 1.405] β: 0.239 (0.0515) |
AUROC: 0.56 [0.53, 0.59] | Nagelkerke's Pseudo-R²: 0.0107 Brier score: 0.0824 Odds Ratio (OR, top 1% vs. Rest): 2.42 [1.17, 4.98] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_C3-THYROID-GLAND_PT_MGI_20200608 |
| PPM001313 | PGS000628 (PRSWEB_PHECODE193_C3-THYROID-GLAND_LASSOSUM_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.276 [1.155, 1.41] β: 0.244 (0.0509) |
AUROC: 0.565 [0.535, 0.595] | Nagelkerke's Pseudo-R²: 0.0114 Brier score: 0.0823 Odds Ratio (OR, top 1% vs. Rest): 1.91 [0.861, 4.22] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_C3-THYROID-GLAND_LASSOSUM_MGI_20200608 |
| PPM001314 | PGS000629 (PRSWEB_PHECODE193_C73_PT_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | β: 0.114 (0.0517) OR: 1.121 [1.013, 1.24] |
AUROC: 0.52 [0.488, 0.55] | Nagelkerke's Pseudo-R²: 0.00247 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 2.15 [1.01, 4.59] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_C73_PT_MGI_20200608 |
| PPM001315 | PGS000630 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.598 [1.439, 1.775] β: 0.469 (0.0536) |
AUROC: 0.626 [0.597, 0.655] | Nagelkerke's Pseudo-R²: 0.0393 Brier score: 0.0811 Odds Ratio (OR, top 1% vs. Rest): 3.53 [1.87, 6.66] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_MGI_20200608 |
| PPM021099 | PGS000630 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_MGI_20200608) |
PSS011527| Multi-ancestry (including European)| 359 individuals |
PGP000610 | Wang JR et al. J Clin Endocrinol Metab (2023) |Ext. |
Reported Trait: BRAFV600E tumor driver subtype in individuals with papillary thyroid carcinoma | OR: 1.51 [1.09, 2.08] | — | — | — | — |
| PPM001316 | PGS000631 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_UKB_20200608) |
PSS000579| European Ancestry| 1,778 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.651 [1.41, 1.934] β: 0.501 (0.0806) |
AUROC: 0.636 [0.589, 0.682] | Nagelkerke's Pseudo-R²: 0.0478 Brier score: 0.0803 Odds Ratio (OR, top 1% vs. Rest): 4.4 [1.81, 10.7] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_P_5e-08_UKB_20200608 |
| PPM001317 | PGS000632 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.568 [1.412, 1.74] β: 0.45 (0.0532) |
AUROC: 0.618 [0.587, 0.647] | Nagelkerke's Pseudo-R²: 0.0365 Brier score: 0.0812 Odds Ratio (OR, top 1% vs. Rest): 5.14 [2.94, 8.99] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_MGI_20200608 |
| PPM001318 | PGS000633 (PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_UKB_20200608) |
PSS000579| European Ancestry| 1,778 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.609 [1.38, 1.876] β: 0.476 (0.0783) |
AUROC: 0.628 [0.582, 0.675] | Nagelkerke's Pseudo-R²: 0.0447 Brier score: 0.0804 Odds Ratio (OR, top 1% vs. Rest): 4.41 [1.81, 10.7] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_GWAS-Catalog-r2019-05-03-X193_PT_UKB_20200608 |
| PPM001319 | PGS000634 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PRS-CS_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.119 [1.008, 1.241] β: 0.112 (0.053) |
AUROC: 0.535 [0.504, 0.567] | Nagelkerke's Pseudo-R²: 0.00228 Brier score: 0.0827 Odds Ratio (OR, top 1% vs. Rest): 1.39 [0.562, 3.45] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PRS-CS_MGI_20200608 |
| PPM001320 | PGS000635 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PT_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.315 [1.194, 1.448] β: 0.274 (0.0492) |
AUROC: 0.569 [0.538, 0.598] | Nagelkerke's Pseudo-R²: 0.0151 Brier score: 0.0822 Odds Ratio (OR, top 1% vs. Rest): 1.65 [0.708, 3.83] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_PT_MGI_20200608 |
| PPM001321 | PGS000636 (PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_LASSOSUM_MGI_20200608) |
PSS000558| European Ancestry| 4,270 individuals |
PGP000118 | Fritsche LG et al. Am J Hum Genet (2020) |
Reported Trait: Thyroid cancer | OR: 1.385 [1.254, 1.529] β: 0.325 (0.0507) |
AUROC: 0.578 [0.548, 0.607] | Nagelkerke's Pseudo-R²: 0.0205 Brier score: 0.0819 Odds Ratio (OR, top 1% vs. Rest): 3.21 [1.67, 6.15] |
age, sex, batch PCs 1-4 | Cancer PRSweb PheWAS Results: PRSWEB_PHECODE193_UKBB-SAIGE-HRC-X193_LASSOSUM_MGI_20200608 |
| PPM001341 | PGS000655 (NAFLD-10) |
PSS000584| European Ancestry| 235 individuals |
PGP000119 | Namjou B et al. BMC Med (2019) |
Reported Trait: Nonalcoholic fatty liver disease severity (NAFLD activity score above 5) | — | AUROC: 0.724 | Odds Ratio (OR, highest vs. lowest quintile): 8.5 [3.45, 20.96] | sex, age, PCs (1-3), BMI, study site/medical centre | — |
| PPM001340 | PGS000655 (NAFLD-10) |
PSS000583| European Ancestry| 9,677 individuals |
PGP000119 | Namjou B et al. BMC Med (2019) |
Reported Trait: Nonalcoholic fatty liver disease | — | AUROC: 0.596 | Odds Ratio (OR, highest vs. lowest quintile): 2.16 [1.81, 2.58] | sex, age, PCs (1-3), BMI, study site/medical centre | — |
| PPM001367 | PGS000663 (wGRS22) |
PSS000598| European Ancestry| 1,591 individuals |
PGP000123 | Kim J et al. Cancer Epidemiol Biomarkers Prev (2020) |
Reported Trait: Pancreatic cancer | OR: 1.37 [1.23, 1.53] | — | — | — | Cross validation approach-testing sample = 20% |
| PPM001368 | PGS000663 (wGRS22) |
PSS000597| European Ancestry| 956 individuals |
PGP000123 | Kim J et al. Cancer Epidemiol Biomarkers Prev (2020) |
Reported Trait: Pancreatic cancer (0-10 years of follow-up) | OR: 1.46 [1.27, 1.68] | — | — | — | Cross validation approach-testing sample = 20% |
| PPM001369 | PGS000663 (wGRS22) |
PSS000598| European Ancestry| 1,591 individuals |
PGP000123 | Kim J et al. Cancer Epidemiol Biomarkers Prev (2020) |
Reported Trait: Pancreatic cancer | OR: 1.37 [1.22, 1.53] | AUROC: 0.65 | — | matching factors, age, cohort (also gender), race/ethnicity, smoking status, fasting status, month/year of blood collection, body mass index, waist-to-hip ratio, diabetic status | Cross validation approach-testing sample = 20% |
| PPM001370 | PGS000663 (wGRS22) |
PSS000597| European Ancestry| 956 individuals |
PGP000123 | Kim J et al. Cancer Epidemiol Biomarkers Prev (2020) |
Reported Trait: Pancreatic cancer (0-10 years of follow-up) | OR: 1.44 [1.25, 1.67] | AUROC: 0.67 | — | matching factors, age, cohort (also gender), race/ethnicity, smoking status, fasting status, month/year of blood collection, body mass index, waist-to-hip ratio, diabetic status | Cross validation approach-testing sample = 20% |
| PPM001596 | PGS000704 (HC171) |
PSS000792| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Alcoholic cirrhosis | — | AUROC: 0.55471 | — | Age, sex, PCs(1-10) | — |
| PPM001607 | PGS000704 (HC171) |
PSS000793| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Alcoholic cirrhosis | HR: 1.18 [1.11, 1.27] | C-index: 0.711 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001604 | PGS000712 (T2D_HbA1c_39) |
PSS000755| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68713 | — | Age, sex, PCs(1-10) | — |
| PPM001605 | PGS000713 (T2D) |
PSS000754| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.688 | — | Age, sex, PCs(1-10) | — |
| PPM001615 | PGS000713 (T2D) |
PSS000756| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | HR: 1.49 [1.47, 1.51] | C-index: 0.669 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001654 | PGS000724 (PRS_Ovary) |
PSS000858| European Ancestry| 400,812 individuals |
PGP000135 | Jia G et al. JNCI Cancer Spectr (2020) |
Reported Trait: Incident epithelial ovarian cancer | — | AUROC: 0.568 [0.537, 0.598] | — | Genotyping array | — |
| PPM001655 | PGS000725 (PRS_Pancreas) |
PSS000859| European Ancestry| 400,812 individuals |
PGP000135 | Jia G et al. JNCI Cancer Spectr (2020) |
Reported Trait: Incident Pancreatic cancer | — | AUROC: 0.639 [0.613, 0.664] | — | Genotyping array | — |
| PPM001656 | PGS000726 (PGS12_CIR) |
PSS000861| European Ancestry| 30,469 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Cirrhosis | OR: 1.32 | — | Odds Ratio (OR, top 20% vs. bottom 20%): 2.26 [1.87, 2.73] | Age, sex, PCs (1-5) | — |
| PPM001657 | PGS000726 (PGS12_CIR) |
PSS000861| European Ancestry| 30,469 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Biopsy-confirmed cirrhosis | OR: 1.39 | — | Odds Ratio (OR, top 20% vs. bottom 20%): 2.21 [1.59, 3.08] | Age, sex, PCs (1-5) | — |
| PPM001658 | PGS000726 (PGS12_CIR) |
PSS000861| European Ancestry| 30,469 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Esophageal varices | OR: 1.45 | — | Odds Ratio (OR, top 20% vs. bottom 20%): 3.1 [1.97, 4.9] | Age, sex, PCs (1-5) | — |
| PPM001659 | PGS000726 (PGS12_CIR) |
PSS000861| European Ancestry| 30,469 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Hepatocellular carcioma | OR: 1.39 | — | Odds Ratio (OR, top 20% vs. bottom 20%): 2.51 [1.59, 3.97] | Age, sex, PCs (1-5) | — |
| PPM001660 | PGS000726 (PGS12_CIR) |
PSS000861| European Ancestry| 30,469 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Death from liver disease | OR: 1.29 | — | Odds Ratio (OR, top 20% vs. bottom 20%): 2.03 [1.24, 3.32] | Age, sex, PCs (1-5) | — |
| PPM001661 | PGS000726 (PGS12_CIR) |
PSS000866| African Ancestry| 1,442 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Cirrhosis | — | — | Odds Ratio (OR, 20-80% vs. bottom 20%): 3.63 [1.55, 8.5] Odds Ratio (OR, top 20% risk vs. bottom 20%): 2.44 [0.92, 6.48] |
Age, sex, PCs (1-5) | — |
| PPM001662 | PGS000726 (PGS12_CIR) |
PSS000863| Ancestry Not Reported| 13,826 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Cirrhosis | — | — | Odds Ratio (OR, top 1% vs. bottom 20%): 3.16 [2.03, 4.9] | Age, sex, PCs (1-5) | — |
| PPM001663 | PGS000726 (PGS12_CIR) |
PSS000862| Ancestry Not Reported| 13,047 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Biopsy-confirmed cirrhosis | — | — | Odds Ratio (OR, top 1% vs. bottom 20%): 6.12 [3.55, 10.58] | Age, sex, PCs (1-5) | — |
| PPM001664 | PGS000726 (PGS12_CIR) |
PSS000864| European Ancestry| 213 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Cirrhosis in individuals with hepatitis B | — | — | Odds ratio (OR, top 20% vs. bottom 20%): 4.83 [1.12, 20.0] | Age, sex, PCs (1-5) | — |
| PPM001665 | PGS000726 (PGS12_CIR) |
PSS000865| European Ancestry| 661 individuals |
PGP000136 | Emdin CA et al. Gastroenterology (2020) |
Reported Trait: Cirrhosis in individuals with hepatitis C | — | — | Odds ratio (OR, top 20% vs. bottom 20%): 2.2 [1.2, 4.05] | Age, sex, PCs (1-5) | — |
| PPM001667 | PGS000729 (T2D_PGS) |
PSS000869| European Ancestry| 3,087 individuals |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Reported Trait: Incident type 2 diabetes | HR: 2.0 [1.36, 2.94] | — | — | age, sex, 10 genetic PCs | — |
| PPM001934 | PGS000759 (hypoT) |
PSS000970| European Ancestry| 1,584 individuals |
PGP000164 | Khan Z et al. Nat Commun (2021) |
Reported Trait: anti-PD-L1 induced hypothyroidism in cancer patients | HR: 1.52 [1.31, 1.74] | — | meta-analysis p-value: 7.52e-09 | 5 genotype PCs | — |
| PPM001936 | PGS000761 (LDpred2_hypoT_PRS) |
PSS000970| European Ancestry| 1,584 individuals |
PGP000164 | Khan Z et al. Nat Commun (2021) |
Reported Trait: anti-PD-L1 induced hypothyroidism in cancer patients | HR: 1.49 [1.3, 1.71] | — | meta-analysis p-value: 5.49e-09 | 5 genotype PCs | — |
| PPM002011 | PGS000776 (GRS9_Cirr) |
PSS000996| Ancestry Not Reported| 107,014 individuals |
PGP000180 | Innes H et al. Gastroenterology (2020) |
Reported Trait: Incident liver cirrhosis in individuals at-risk for nonalcoholic fatty liver disease (time to first hospitilisation) | — | C-index: 0.62 [0.59, 0.64] | Hazard Ratio (HR, top 20% vs bottom 20%): 3.12 [2.37, 4.12] | — | — |
| PPM002012 | PGS000776 (GRS9_Cirr) |
PSS000996| Ancestry Not Reported| 107,014 individuals |
PGP000180 | Innes H et al. Gastroenterology (2020) |
Reported Trait: Incident liver cirrhosis in individuals at-risk for nonalcoholic fatty liver disease (time to first hospitilisation) | — | — | Hazard Ratio (HR, top 20% vs bottom 20%): 3.16 [2.38, 4.21] | Age, sex, BMI, diabetes, units of alcohol consumed per week | — |
| PPM002013 | PGS000776 (GRS9_Cirr) |
PSS000996| Ancestry Not Reported| 107,014 individuals |
PGP000180 | Innes H et al. Gastroenterology (2020) |
Reported Trait: Incident liver cirrhosis in individuals at-risk for nonalcoholic fatty liver disease (time to first hospitilisation) | — | C-index: 0.677 [0.653, 0.7] | — | Age, sex | — |
| PPM002064 | PGS000793 (CC_Ovary_IV) |
PSS001021| European Ancestry| 211,958 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Reported Trait: Incident ovarian cancer | HR: 1.2 [1.1, 1.32] | AUROC: 0.66 C-index: 0.654 (0.015) |
R²: 0.193 | Age at assessment, family history of breast cancer, genotyping array, PCs(1-15), parity ( ≥1 live birth vs. none), body mass index, Menopausal status (pre-menopausal vs. post-menopausal vs. unknown or hysterectomy), ever used hormone replacement therapy, oral contraceptive use (never used (0) vs. <20 years vs. ≥20 years), BMI*menopausal status | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM002065 | PGS000794 (CC_Pancreas_IV) |
PSS001022| European Ancestry| 391,491 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Reported Trait: Incident pancreatic cancer | HR: 1.49 [1.37, 1.63] | AUROC: 0.745 C-index: 0.743 (0.012) |
R²: 0.439 | Age at assessment, sex, genotyping array, PCs(1-15), family history of cancer (prostate, breast, lung, bowel), body mass index, cigarette pack-years, smoking status (never vs. former vs. current) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM002067 | PGS000796 (CC_Testis_IV) |
PSS001024| European Ancestry| 179,537 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Reported Trait: Incident testicular cancer | HR: 2.26 [1.71, 2.99] | AUROC: 0.787 C-index: 0.766 (0.033) |
R²: 0.605 | Age at assessment, genotyping array, PCs(1-15) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM002068 | PGS000797 (CC_Thyroid_IV) |
PSS001025| European Ancestry| 391,189 individuals |
PGP000186 | Kachuri L et al. Nat Commun (2020) |
Reported Trait: Incident thyroid cancer | HR: 1.75 [1.53, 2.01] | AUROC: 0.701 C-index: 0.692 (0.022) |
R²: 0.31 | Age at assessment, sex,, genotyping array, PCs(1-15), body mass index (BMI <25 vs. 25≤BMI<30, BMI≥30) | C-index calculated as a weighted average between 1 and 5 years and AUC at 5 years. |
| PPM002117 | PGS000804 (GRS582_T2Dmulti) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.568 [0.5588, 0.5772] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002119 | PGS000804 (GRS582_T2Dmulti) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.825 [0.8222, 0.8279] | Odds Ratio (OR, top 10% vs middle 20%): 2.94 [2.8, 3.08] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002121 | PGS000804 (GRS582_T2Dmulti) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6586 [0.6547, 0.6624] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002123 | PGS000804 (GRS582_T2Dmulti) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7293 [0.721, 0.7376] | Odds Ratio (OR, top 10% vs middle 20%): 2.39 [2.1, 2.73] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002125 | PGS000804 (GRS582_T2Dmulti) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6249 [0.6156, 0.6342] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002127 | PGS000804 (GRS582_T2Dmulti) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8411 [0.8298, 0.8523] | Odds Ratio (OR, top 10% vs middle 20%): 3.08 [2.4, 3.95] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002129 | PGS000804 (GRS582_T2Dmulti) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6263 [0.6101, 0.6425] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002131 | PGS000804 (GRS582_T2Dmulti) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7989 [0.7845, 0.8133] | Odds Ratio (OR, top 10% vs middle 20%): 2.02 [1.54, 2.65] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002133 | PGS000804 (GRS582_T2Dmulti) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6214 [0.603, 0.6399] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002115 | PGS000804 (GRS582_T2Dmulti) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6701 [0.6615, 0.6788] | Odds Ratio (OR, top 10% vs middle 20%): 1.57 [1.39, 1.77] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002120 | PGS000805 (GRS582_T2Deur) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8253 [0.8224, 0.8281] | Odds Ratio (OR, top 10% vs middle 20%): 2.95 [2.81, 3.1] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002122 | PGS000805 (GRS582_T2Deur) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6593 [0.6555, 0.6632] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002134 | PGS000805 (GRS582_T2Deur) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6213 [0.6029, 0.6397] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Deur was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002132 | PGS000805 (GRS582_T2Deur) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7985 [0.7842, 0.8129] | Odds Ratio (OR, top 10% vs middle 20%): 2.13 [1.63, 2.79] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Deur was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002116 | PGS000806 (GRS582_T2Dafr) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6656 [0.6569, 0.6743] | Odds Ratio (OR, top 10% vs middle 20%): 1.53 [1.36, 1.73] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002118 | PGS000806 (GRS582_T2Dafr) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.5592 [0.5499, 0.5684] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002128 | PGS000807 (GRS582_T2Dasn) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8388 [0.8274, 0.8502] | Odds Ratio (OR, top 10% vs middle 20%): 2.84 [2.21, 3.65] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002130 | PGS000807 (GRS582_T2Dasn) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6161 [0.5998, 0.6324] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002135 | PGS000807 (GRS582_T2Dasn) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7909 [0.7763, 0.8056] | Odds Ratio (OR, top 10% vs middle 20%): 1.62 [1.23, 2.14] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Dasn was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002136 | PGS000807 (GRS582_T2Dasn) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.5768 [0.558, 0.5956] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Dasn was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002124 | PGS000808 (GRS582_T2Dhis) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7202 [0.7118, 0.7286] | Odds Ratio (OR, top 10% vs middle 20%): 2.04 [1.79, 2.32] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002126 | PGS000808 (GRS582_T2Dhis) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6098 [0.6004, 0.6192] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002193 | PGS000820 (PRS_hypothyroidism) |
PSS001068| European Ancestry| 51,070 individuals |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Reported Trait: Spontaneous hypothyroidism | OR: 1.33 [1.29, 1.37] | AUROC: 0.6 | — | Age, sex, PCs(1-10) | — |
| PPM002195 | PGS000820 (PRS_hypothyroidism) |
PSS001070| Multi-ancestry (including European)| 744 individuals |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Reported Trait: Immune checkpoint inhibitor therapy induced immune-related thyroid dysfunction in individuals with non-small cell lung cancer | HR: 1.34 [1.08, 1.66] | AUROC: 0.6 | — | Age, sex, PCs(1-10) | — |
| PPM002197 | PGS000820 (PRS_hypothyroidism) |
PSS001070| Multi-ancestry (including European)| 744 individuals |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Reported Trait: Anti-PD-(L)1 monotherapy induced immune-related thyroid dysfunction in individuals with non-small cell lung cancer | HR: 1.34 [1.07, 1.69] | — | — | Age, sex, PCs(1-10) | — |
| PPM002199 | PGS000820 (PRS_hypothyroidism) |
PSS001069| Multi-ancestry (including European)| 561 individuals |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Reported Trait: Immune checkpoint inhibitor therapy induced immune-related thyroid dysfunction in individuals with non-small cell lung cancer | HR: 1.39 [1.07, 1.82] | AUROC: 0.64 | — | Age, sex, PCs(1-10) | — |
| PPM002198 | PGS000820 (PRS_hypothyroidism) |
PSS001071| European Ancestry| 634 individuals |
PGP000204 | Luo J et al. Clin Cancer Res (2021) |
Reported Trait: Immune checkpoint inhibitor therapy induced immune-related thyroid dysfunction in individuals with non-small cell lung cancer | HR: 1.27 [1.02, 1.59] | — | — | Age, sex | — |
| PPM002240 | PGS000832 (T2D-GRS) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.24 [1.16, 1.34] | — | — | PC1-10 | — |
| PPM002242 | PGS000832 (T2D-GRS) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.77 [1.67, 1.88] | — | — | PC1-10 | — |
| PPM002239 | PGS000832 (T2D-GRS) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.96 [1.81, 2.12] | — | — | PC1-10 | — |
| PPM002238 | PGS000832 (T2D-GRS) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.28 [1.16, 1.42] | — | — | PC1-10 | — |
| PPM002241 | PGS000832 (T2D-GRS) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.73 [1.61, 1.86] | — | — | PC1-10 | — |
| PPM020163 | PGS000832 (T2D-GRS) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.78 [1.49, 2.13] | — | — | age, sex and BMI | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020196 | PGS000832 (T2D-GRS) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.5 [1.27, 1.76] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020207 | PGS000832 (T2D-GRS) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.54 [1.27, 1.87] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020184 | PGS000832 (T2D-GRS) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.66 [1.42, 1.93] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM002243 | PGS000833 (T1D) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.39 [1.25, 1.54] | — | — | PC1-10 | — |
| PPM002246 | PGS000833 (T1D) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.04 [0.97, 1.11] | — | — | PC1-10 | — |
| PPM002247 | PGS000833 (T1D) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.02 [0.97, 1.07] | — | — | PC1-10 | — |
| PPM002244 | PGS000833 (T1D) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002245 | PGS000833 (T1D) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.03 [0.96, 1.11] | — | — | PC1-10 | — |
| PPM002323 | PGS000848 (T2D_Adiposity) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.11 [1.0, 1.23] | — | — | PC1-10 | — |
| PPM002324 | PGS000848 (T2D_Adiposity) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.1 [1.02, 1.18] | — | — | PC1-10 | — |
| PPM002325 | PGS000848 (T2D_Adiposity) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.11 [1.03, 1.19] | — | — | PC1-10 | — |
| PPM002326 | PGS000848 (T2D_Adiposity) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.2 [1.12, 1.28] | — | — | PC1-10 | — |
| PPM002327 | PGS000848 (T2D_Adiposity) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.06 [1.0, 1.12] | — | — | PC1-10 | — |
| PPM020167 | PGS000848 (T2D_Adiposity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.14 [1.01, 1.28] | — | — | sex | — |
| PPM020183 | PGS000848 (T2D_Adiposity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: BMI | β: 0.06772 (0.027943) | — | — | — | — |
| PPM020187 | PGS000848 (T2D_Adiposity) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.23 [1.07, 1.43] | — | — | sex | — |
| PPM002329 | PGS000849 (T2D_Impaired_Lipids) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.07 [1.0, 1.15] | — | — | PC1-10 | — |
| PPM002330 | PGS000849 (T2D_Impaired_Lipids) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.09 [1.01, 1.17] | — | — | PC1-10 | — |
| PPM002331 | PGS000849 (T2D_Impaired_Lipids) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | — |
| PPM002332 | PGS000849 (T2D_Impaired_Lipids) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.06 [1.0, 1.12] | — | — | PC1-10 | — |
| PPM002328 | PGS000849 (T2D_Impaired_Lipids) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.08 [0.97, 1.2] | — | — | PC1-10 | — |
| PPM020176 | PGS000849 (T2D_Impaired_Lipids) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.2 [1.0, 1.44] | — | — | age, sex and BMI | — |
| PPM020194 | PGS000849 (T2D_Impaired_Lipids) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.2 [1.03, 1.4] | — | — | sex | — |
| PPM020204 | PGS000849 (T2D_Impaired_Lipids) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.26 [1.07, 1.49] | — | — | sex | — |
| PPM002333 | PGS000850 (T2D_Insulin_Action) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.08 [0.98, 1.2] | — | — | PC1-10 | — |
| PPM002334 | PGS000850 (T2D_Insulin_Action) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.17 [1.09, 1.25] | — | — | PC1-10 | — |
| PPM002335 | PGS000850 (T2D_Insulin_Action) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.17 [1.09, 1.26] | — | — | PC1-10 | — |
| PPM002337 | PGS000850 (T2D_Insulin_Action) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.16 [1.1, 1.23] | — | — | PC1-10 | — |
| PPM002336 | PGS000850 (T2D_Insulin_Action) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.14 [1.07, 1.22] | — | — | PC1-10 | — |
| PPM020173 | PGS000850 (T2D_Insulin_Action) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.16 [1.03, 1.3] | — | — | sex | — |
| PPM020201 | PGS000850 (T2D_Insulin_Action) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.17 [1.0, 1.36] | — | — | sex | — |
| PPM020213 | PGS000850 (T2D_Insulin_Action) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.26 [1.04, 1.53] | — | — | sex | — |
| PPM002338 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.24 [1.12, 1.37] | — | — | PC1-10 | — |
| PPM002339 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.23 [1.15, 1.32] | — | — | PC1-10 | — |
| PPM002340 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.04 [0.97, 1.11] | — | — | PC1-10 | — |
| PPM002341 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.19 [1.12, 1.28] | — | — | PC1-10 | — |
| PPM002342 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.19 [1.13, 1.26] | — | — | PC1-10 | — |
| PPM020172 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.07 [0.9, 1.28] | — | — | age, sex and BMI | — |
| PPM020192 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.17 [1.01, 1.34] | — | — | sex | — |
| PPM020212 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.45 [1.19, 1.78] | — | — | sex | — |
| PPM002343 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.01 [0.91, 1.12] | — | — | PC1-10 | — |
| PPM002344 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.31 [1.22, 1.41] | — | — | PC1-10 | — |
| PPM002345 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.04 [0.97, 1.12] | — | — | PC1-10 | — |
| PPM002347 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.29 [1.22, 1.37] | — | — | PC1-10 | — |
| PPM002346 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.26 [1.18, 1.35] | — | — | PC1-10 | — |
| PPM020170 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.33 [1.12, 1.58] | — | — | age, sex and BMI | — |
| PPM020190 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.38 [1.19, 1.59] | — | — | sex | — |
| PPM020199 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.25 [1.08, 1.46] | — | — | sex | — |
| PPM020210 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.33 [1.1, 1.61] | — | — | sex | — |
| PPM002348 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.99 [0.9, 1.1] | — | — | PC1-10 | — |
| PPM002349 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.26 [1.18, 1.36] | — | — | PC1-10 | — |
| PPM002350 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.02 [0.95, 1.09] | — | — | PC1-10 | — |
| PPM002351 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.18 [1.11, 1.27] | — | — | PC1-10 | — |
| PPM002352 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.23 [1.17, 1.3] | — | — | PC1-10 | — |
| PPM020171 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.32 [1.11, 1.57] | — | — | age, sex and BMI | — |
| PPM020200 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.24 [1.07, 1.45] | — | — | sex | — |
| PPM020211 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.32 [1.1, 1.59] | — | — | sex | — |
| PPM002353 | PGS000854 (T2D_BetaCell) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.0 [0.91, 1.11] | — | — | PC1-10 | — |
| PPM002354 | PGS000854 (T2D_BetaCell) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.32 [1.23, 1.42] | — | — | PC1-10 | — |
| PPM002355 | PGS000854 (T2D_BetaCell) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002357 | PGS000854 (T2D_BetaCell) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.27 [1.2, 1.34] | — | — | PC1-10 | — |
| PPM002356 | PGS000854 (T2D_BetaCell) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.21 [1.13, 1.3] | — | — | PC1-10 | — |
| PPM020168 | PGS000854 (T2D_BetaCell) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 0.89 [0.79, 1.0] | — | — | sex | — |
| PPM020188 | PGS000854 (T2D_BetaCell) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 0.87 [0.75, 1.0] | — | — | sex | — |
| PPM020209 | PGS000854 (T2D_BetaCell) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 0.81 [0.67, 0.97] | — | — | sex | — |
| PPM002358 | PGS000855 (T2D_Lipodystrophy) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.12 [1.01, 1.25] | — | — | PC1-10 | — |
| PPM002359 | PGS000855 (T2D_Lipodystrophy) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.23 [1.15, 1.33] | — | — | PC1-10 | — |
| PPM002360 | PGS000855 (T2D_Lipodystrophy) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.15 [1.07, 1.24] | — | — | PC1-10 | — |
| PPM002361 | PGS000855 (T2D_Lipodystrophy) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.14 [1.06, 1.22] | — | — | PC1-10 | — |
| PPM002362 | PGS000855 (T2D_Lipodystrophy) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.18 [1.11, 1.24] | — | — | PC1-10 | — |
| PPM020175 | PGS000855 (T2D_Lipodystrophy) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.17 [1.04, 1.31] | — | — | sex | — |
| PPM020193 | PGS000855 (T2D_Lipodystrophy) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.16 [1.0, 1.34] | — | — | sex | — |
| PPM020203 | PGS000855 (T2D_Lipodystrophy) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.18 [1.01, 1.37] | — | — | sex | — |
| PPM002363 | PGS000856 (T2D_LiverLipids) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.35 [1.22, 1.51] | — | — | PC1-10 | — |
| PPM002364 | PGS000856 (T2D_LiverLipids) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002366 | PGS000856 (T2D_LiverLipids) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.02 [0.95, 1.09] | — | — | PC1-10 | — |
| PPM002367 | PGS000856 (T2D_LiverLipids) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.95 [0.9, 1.01] | — | — | PC1-10 | — |
| PPM002365 | PGS000856 (T2D_LiverLipids) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 0.97 [0.91, 1.05] | — | — | PC1-10 | — |
| PPM020177 | PGS000856 (T2D_LiverLipids) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.29 [1.09, 1.54] | — | — | age, sex and BMI | — |
| PPM020195 | PGS000856 (T2D_LiverLipids) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.24 [1.07, 1.43] | — | — | sex | — |
| PPM020205 | PGS000856 (T2D_LiverLipids) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.31 [1.12, 1.53] | — | — | sex | — |
| PPM020206 | PGS000856 (T2D_LiverLipids) |
PSS011304| South Asian Ancestry| 482 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin-resistant diabetes | OR: 2.04 [1.26, 3.3] | — | — | sex | — |
| PPM002368 | PGS000857 (T2D_Obesity) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.07 [0.97, 1.19] | — | — | PC1-10 | — |
| PPM002369 | PGS000857 (T2D_Obesity) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.08 [1.01, 1.16] | — | — | PC1-10 | — |
| PPM002370 | PGS000857 (T2D_Obesity) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.13 [1.05, 1.22] | — | — | PC1-10 | — |
| PPM002371 | PGS000857 (T2D_Obesity) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.19 [1.11, 1.27] | — | — | PC1-10 | — |
| PPM002372 | PGS000857 (T2D_Obesity) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.04 [0.99, 1.1] | — | — | PC1-10 | — |
| PPM020164 | PGS000857 (T2D_Obesity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 0.87 [0.77, 0.99] | — | — | sex | — |
| PPM002373 | PGS000858 (T2D_Proinsulin) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.94 [0.85, 1.04] | — | — | PC1-10 | — |
| PPM002374 | PGS000858 (T2D_Proinsulin) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.14 [1.06, 1.22] | — | — | PC1-10 | — |
| PPM002376 | PGS000858 (T2D_Proinsulin) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.06 [0.99, 1.13] | — | — | PC1-10 | — |
| PPM002377 | PGS000858 (T2D_Proinsulin) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.1 [1.04, 1.16] | — | — | PC1-10 | — |
| PPM002375 | PGS000858 (T2D_Proinsulin) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 0.93 [0.87, 1.0] | — | — | PC1-10 | — |
| PPM020174 | PGS000858 (T2D_Proinsulin) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.22 [1.03, 1.44] | — | — | age, sex and BMI | — |
| PPM020202 | PGS000858 (T2D_Proinsulin) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.2 [1.03, 1.4] | — | — | sex | — |
| PPM020214 | PGS000858 (T2D_Proinsulin) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.23 [1.01, 1.48] | — | — | sex | — |
| PPM002403 | PGS000864 (T2D-gPRS) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.42 [1.28, 1.58] | — | — | PC1-10 | — |
| PPM002404 | PGS000864 (T2D-gPRS) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.93 [1.79, 2.09] | — | — | PC1-10 | — |
| PPM002406 | PGS000864 (T2D-gPRS) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 2.12 [1.96, 2.29] | — | — | PC1-10 | — |
| PPM002407 | PGS000864 (T2D-gPRS) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.59 [1.5, 1.69] | — | — | PC1-10 | — |
| PPM002405 | PGS000864 (T2D-gPRS) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.56 [1.45, 1.69] | — | — | PC1-10 | — |
| PPM002413 | PGS000868 (T2D_221) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Reported Trait: Cystic-fibrosis related diabetes | HR: 1.285 | — | — | PCs(1-4), site of recruitment | — |
| PPM002414 | PGS000869 (T1D_48) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Reported Trait: Cystic-fibrosis related diabetes | HR: 1.077 | — | — | PCs(1-4), site of recruitment | — |
| PPM002418 | PGS000872 (PRS-5) |
PSS001096| European Ancestry| 364,048 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Cirrhosis | OR: 4.4 [3.5, 5.6] | — | — | — | — |
| PPM002420 | PGS000872 (PRS-5) |
PSS001096| European Ancestry| 364,048 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Cirrhosis | OR: 4.5 [3.6, 5.7] | — | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | — |
| PPM002432 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Severe fibrosis in individuals within stage F3-F4 of fatty liver disease | OR: 9.4 [5.4, 16.2] | — | — | Age, sex, body mass index, type 2 diabetes | — |
| PPM002419 | PGS000872 (PRS-5) |
PSS001096| European Ancestry| 364,048 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 11.9 [6.6, 21.3] | — | — | — | — |
| PPM002421 | PGS000872 (PRS-5) |
PSS001096| European Ancestry| 364,048 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 11.7 [6.54, 21.0] | — | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | — |
| PPM002422 | PGS000872 (PRS-5) |
PSS001096| European Ancestry| 364,048 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 4.8 [2.6, 8.9] | — | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre, diagnosis of cirrhosis | — |
| PPM002428 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Fatty liver disease | OR: 9.0 [6.0, 13.4] | — | — | — | — |
| PPM002429 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Severe fibrosis in individuals within stage F3-F4 of fatty liver disease | OR: 12.6 [8.2, 19.3] | — | — | — | — |
| PPM002430 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 9.1 [5.2, 16.0] | — | — | — | — |
| PPM002431 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Fatty liver disease | OR: 10.7 [6.6, 17.3] | — | — | Age, sex, body mass index, type 2 diabetes | — |
| PPM002433 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 3.3 [1.6, 6.9] | — | — | Age, sex, body mass index, type 2 diabetes | — |
| PPM002440 | PGS000872 (PRS-5) |
PSS001094| European Ancestry| 2,564 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 2.9 [2.1, 3.8] | AUROC: 0.65 | — | Age, sex, body mass index, type 2 diabetes | Only 2,245 participants were available for this analysis. |
| PPM002443 | PGS000872 (PRS-5) |
PSS001097| European Ancestry| 356,943 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 3.4 [2.5, 4.7] | AUROC: 0.63 | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | PRS-5 was treated as a binary variable with a cutoff of ≥0.495 |
| PPM002445 | PGS000872 (PRS-5) |
PSS001101| European Ancestry| 355,450 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma in individuals with no cirrhosis | OR: 1.9 [1.1, 3.2] | AUROC: 0.54 | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | PRS-5 was treated as a binary variable with a cutoff of ≥0.495 |
| PPM002447 | PGS000872 (PRS-5) |
PSS001098| European Ancestry| 85,890 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma in individuals with a body mass index ≥30 | OR: 5.5 [3.6, 8.5] | AUROC: 0.69 | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | PRS-5 was treated as a binary variable with a cutoff of ≥0.495 |
| PPM002449 | PGS000872 (PRS-5) |
PSS001103| European Ancestry| 25,039 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma in individuals with type 2 diabetes | OR: 4.6 [2.9, 7.3] | AUROC: 0.71 | — | Age, sex, body mass index, type 2 diabetes, PCs(1-10), array batch, assessment centre | PRS-5 was treated as a binary variable with a cutoff of ≥0.495 |
| PPM002451 | PGS000872 (PRS-5) |
PSS001095| Ancestry Not Reported| 429 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 8.61 [3.31, 22.37] | AUROC: 0.65 | — | — | — |
| PPM002453 | PGS000872 (PRS-5) |
PSS001095| Ancestry Not Reported| 429 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 6.36 [1.67, 24.31] | — | — | Age, sex, body mass index, type 2 diabetes | — |
| PPM002455 | PGS000872 (PRS-5) |
PSS001095| Ancestry Not Reported| 429 individuals |
PGP000215 | Bianco C et al. J Hepatol (2020) |
Reported Trait: Hepatocellular carcinoma | OR: 2.4 [1.19, 4.83] | — | — | — | PRS-5 was treated as a binary variable with a cutoff of ≥0.495 |
| PPM019102 | PGS000872 (PRS-5) |
PSS011182| European Ancestry| 381,825 individuals |
PGP000505 | Liu Z et al. Liver Int (2023) |Ext. |
Reported Trait: Non-alcoholic fatty liver disease | — | — | p-value (inferior to): 0.001 | age, sex, ethnicity, Townsend deprivation index (quintiles), education level, household income, employment status, self-reported smoking status, self-reported frequency of alcohol intake, sedentary behaviour, body mass index, baseline diabetes, baseline hypertension, serum triglyceride level, C-reactive protein level, and eGFR | — |
| PPM019103 | PGS000872 (PRS-5) |
PSS011182| European Ancestry| 381,825 individuals |
PGP000505 | Liu Z et al. Liver Int (2023) |Ext. |
Reported Trait: Severe liver disease | — | — | p-value (inferior to): 0.001 | age, sex, ethnicity, Townsend deprivation index (quintiles), education level, household income, employment status, self-reported smoking status, self-reported frequency of alcohol intake, sedentary behaviour, body mass index, baseline diabetes, baseline hypertension, serum triglyceride level, C-reactive protein level, and eGFR | — |
| PPM019104 | PGS000872 (PRS-5) |
PSS011182| European Ancestry| 381,825 individuals |
PGP000505 | Liu Z et al. Liver Int (2023) |Ext. |
Reported Trait: Serum uric acid levels x PRS interaction for liver disease | HR: 1.03 [1.01, 1.05] | — | — | age, sex, ethnicity, Townsend deprivation index (quintiles), education level, household income, employment status, self-reported smoking status, self-reported frequency of alcohol intake, sedentary behaviour, body mass index, baseline diabetes, baseline hypertension, serum triglyceride level, C-reactive protein level, and eGFR | — |
| PPM019105 | PGS000872 (PRS-5) |
PSS011182| European Ancestry| 381,825 individuals |
PGP000505 | Liu Z et al. Liver Int (2023) |Ext. |
Reported Trait: Serum uric acid levels x PRS interaction for severe liver disease | HR: 1.06 [1.03, 1.1] | — | — | age, sex, ethnicity, Townsend deprivation index (quintiles), education level, household income, employment status, self-reported smoking status, self-reported frequency of alcohol intake, sedentary behaviour, body mass index, baseline diabetes, baseline hypertension, serum triglyceride level, C-reactive protein level, and eGFR | — |
| PPM019101 | PGS000872 (PRS-5) |
PSS011182| European Ancestry| 381,825 individuals |
PGP000505 | Liu Z et al. Liver Int (2023) |Ext. |
Reported Trait: Liver disease | — | — | p-value (inferior to): 0.001 | age, sex, ethnicity, Townsend deprivation index (quintiles), education level, household income, employment status, self-reported smoking status, self-reported frequency of alcohol intake, sedentary behaviour, body mass index, baseline diabetes, baseline hypertension, serum triglyceride level, C-reactive protein level, and eGFR | — |
| PPM007467 | PGS000928 (GBE_HC644) |
PSS004560| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other non-toxic goitre | — | AUROC: 0.72128 [0.66829, 0.77427] | R²: 0.0605 Incremental AUROC (full-covars): 0.01397 PGS R2 (no covariates): 0.01481 PGS AUROC (no covariates): 0.60656 [0.54212, 0.67101] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007468 | PGS000928 (GBE_HC644) |
PSS004561| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other non-toxic goitre | — | AUROC: 0.6964 [0.60514, 0.78765] | R²: 0.04766 Incremental AUROC (full-covars): 0.00791 PGS R2 (no covariates): 0.00213 PGS AUROC (no covariates): 0.559 [0.46259, 0.65542] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007469 | PGS000928 (GBE_HC644) |
PSS004562| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other non-toxic goitre | — | AUROC: 0.71135 [0.68228, 0.74042] | R²: 0.0552 Incremental AUROC (full-covars): 0.0365 PGS R2 (no covariates): 0.01651 PGS AUROC (no covariates): 0.62112 [0.58564, 0.6566] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007470 | PGS000928 (GBE_HC644) |
PSS004563| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other non-toxic goitre | — | AUROC: 0.77727 [0.73439, 0.82016] | R²: 0.09335 Incremental AUROC (full-covars): 0.02392 PGS R2 (no covariates): 0.01984 PGS AUROC (no covariates): 0.62519 [0.56312, 0.68726] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007471 | PGS000928 (GBE_HC644) |
PSS004564| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other non-toxic goitre | — | AUROC: 0.72495 [0.70529, 0.74461] | R²: 0.05905 Incremental AUROC (full-covars): 0.03129 PGS R2 (no covariates): 0.01271 PGS AUROC (no covariates): 0.60048 [0.57499, 0.62598] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007649 | PGS000965 (GBE_HC219) |
PSS004354| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypothyroidism/myxoedema | — | AUROC: 0.70914 [0.67391, 0.74437] | R²: 0.06732 Incremental AUROC (full-covars): 0.00847 PGS R2 (no covariates): 0.01005 PGS AUROC (no covariates): 0.58277 [0.54281, 0.62272] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007650 | PGS000965 (GBE_HC219) |
PSS004355| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypothyroidism/myxoedema | — | AUROC: 0.68903 [0.61236, 0.7657] | R²: 0.05952 Incremental AUROC (full-covars): 0.01842 PGS R2 (no covariates): 0.01318 PGS AUROC (no covariates): 0.58777 [0.50589, 0.66966] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007651 | PGS000965 (GBE_HC219) |
PSS004356| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypothyroidism/myxoedema | — | AUROC: 0.76462 [0.75294, 0.7763] | R²: 0.14559 Incremental AUROC (full-covars): 0.06544 PGS R2 (no covariates): 0.06844 PGS AUROC (no covariates): 0.68233 [0.66882, 0.69583] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007652 | PGS000965 (GBE_HC219) |
PSS004357| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypothyroidism/myxoedema | — | AUROC: 0.74628 [0.72661, 0.76594] | R²: 0.13858 Incremental AUROC (full-covars): 0.03694 PGS R2 (no covariates): 0.04737 PGS AUROC (no covariates): 0.64507 [0.62236, 0.66778] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007653 | PGS000965 (GBE_HC219) |
PSS004358| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypothyroidism/myxoedema | — | AUROC: 0.76828 [0.76142, 0.77515] | R²: 0.14978 Incremental AUROC (full-covars): 0.07249 PGS R2 (no covariates): 0.07271 PGS AUROC (no covariates): 0.68907 [0.68098, 0.69716] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007833 | PGS001014 (GBE_HC654) |
PSS004585| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other disorders of pancreatic internal secretion | — | AUROC: 0.65665 [0.58207, 0.73122] | R²: 0.03396 Incremental AUROC (full-covars): -0.00764 PGS R2 (no covariates): 0.00359 PGS AUROC (no covariates): 0.4188 [0.34373, 0.49387] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007834 | PGS001014 (GBE_HC654) |
PSS004586| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other disorders of pancreatic internal secretion | — | AUROC: 0.86357 [0.7171, 1.0] | R²: 0.15881 Incremental AUROC (full-covars): -0.01283 PGS R2 (no covariates): 0.02019 PGS AUROC (no covariates): 0.35821 [0.13039, 0.58603] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007835 | PGS001014 (GBE_HC654) |
PSS004587| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other disorders of pancreatic internal secretion | — | AUROC: 0.64476 [0.60172, 0.6878] | R²: 0.02426 Incremental AUROC (full-covars): -0.00192 PGS R2 (no covariates): 0.00131 PGS AUROC (no covariates): 0.52076 [0.4675, 0.57402] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007836 | PGS001014 (GBE_HC654) |
PSS004588| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other disorders of pancreatic internal secretion | — | AUROC: 0.73516 [0.68282, 0.7875] | R²: 0.07572 Incremental AUROC (full-covars): -0.00172 PGS R2 (no covariates): 0.00033 PGS AUROC (no covariates): 0.50209 [0.4372, 0.56698] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007837 | PGS001014 (GBE_HC654) |
PSS004589| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other disorders of pancreatic internal secretion | — | AUROC: 0.63289 [0.60549, 0.66029] | R²: 0.01894 Incremental AUROC (full-covars): 0.01617 PGS R2 (no covariates): 0.00452 PGS AUROC (no covariates): 0.55692 [0.52735, 0.58649] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007968 | PGS001042 (GBE_HC645) |
PSS004565| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE thyrotoxicosis [hyperthyroidism] | — | AUROC: 0.74292 [0.70274, 0.7831] | R²: 0.0808 Incremental AUROC (full-covars): -0.001 PGS R2 (no covariates): 0.00441 PGS AUROC (no covariates): 0.55406 [0.50519, 0.60292] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007969 | PGS001042 (GBE_HC645) |
PSS004566| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE thyrotoxicosis [hyperthyroidism] | — | AUROC: 0.64568 [0.56662, 0.72474] | R²: 0.04341 Incremental AUROC (full-covars): 0.0279 PGS R2 (no covariates): 0.02341 PGS AUROC (no covariates): 0.6179 [0.53755, 0.69825] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007970 | PGS001042 (GBE_HC645) |
PSS004567| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE thyrotoxicosis [hyperthyroidism] | — | AUROC: 0.69253 [0.66505, 0.72] | R²: 0.0468 Incremental AUROC (full-covars): 0.03643 PGS R2 (no covariates): 0.01594 PGS AUROC (no covariates): 0.61209 [0.58178, 0.6424] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007971 | PGS001042 (GBE_HC645) |
PSS004568| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE thyrotoxicosis [hyperthyroidism] | — | AUROC: 0.68899 [0.63846, 0.73951] | R²: 0.04589 Incremental AUROC (full-covars): 0.03955 PGS R2 (no covariates): 0.01668 PGS AUROC (no covariates): 0.60594 [0.54869, 0.66319] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007972 | PGS001042 (GBE_HC645) |
PSS004569| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE thyrotoxicosis [hyperthyroidism] | — | AUROC: 0.71296 [0.69708, 0.72884] | R²: 0.05914 Incremental AUROC (full-covars): 0.04673 PGS R2 (no covariates): 0.02359 PGS AUROC (no covariates): 0.63392 [0.61562, 0.65223] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007973 | PGS001043 (GBE_HC55) |
PSS004526| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hyperthyroidism/thyrotoxicosis | — | AUROC: 0.73999 [0.69812, 0.78186] | R²: 0.07663 Incremental AUROC (full-covars): -0.00598 PGS R2 (no covariates): 0.00164 PGS AUROC (no covariates): 0.53513 [0.48316, 0.5871] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007974 | PGS001043 (GBE_HC55) |
PSS004527| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hyperthyroidism/thyrotoxicosis | — | AUROC: 0.62359 [0.53601, 0.71117] | R²: 0.03132 Incremental AUROC (full-covars): 0.0205 PGS R2 (no covariates): 0.01311 PGS AUROC (no covariates): 0.58858 [0.50442, 0.67274] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007975 | PGS001043 (GBE_HC55) |
PSS004528| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hyperthyroidism/thyrotoxicosis | — | AUROC: 0.69729 [0.66674, 0.72784] | R²: 0.04646 Incremental AUROC (full-covars): 0.03676 PGS R2 (no covariates): 0.01638 PGS AUROC (no covariates): 0.61845 [0.58525, 0.65166] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007976 | PGS001043 (GBE_HC55) |
PSS004529| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hyperthyroidism/thyrotoxicosis | — | AUROC: 0.68797 [0.63675, 0.7392] | R²: 0.04145 Incremental AUROC (full-covars): 0.04372 PGS R2 (no covariates): 0.01807 PGS AUROC (no covariates): 0.60983 [0.54762, 0.67204] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007977 | PGS001043 (GBE_HC55) |
PSS004530| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hyperthyroidism/thyrotoxicosis | — | AUROC: 0.71366 [0.6965, 0.73082] | R²: 0.0566 Incremental AUROC (full-covars): 0.04641 PGS R2 (no covariates): 0.02158 PGS AUROC (no covariates): 0.6323 [0.61251, 0.6521] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008542 | PGS001164 (GBE_cancer1045) |
PSS007643| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Testicular cancer | — | AUROC: 0.89735 [0.86792, 0.92679] | R²: 0.1704 Incremental AUROC (full-covars): 0.01226 PGS R2 (no covariates): 0.01529 PGS AUROC (no covariates): 0.62484 [0.5376, 0.71208] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008543 | PGS001164 (GBE_cancer1045) |
PSS007644| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Testicular cancer | — | AUROC: 0.9816 [0.96678, 0.99641] | R²: 0.29699 Incremental AUROC (full-covars): 0.00299 PGS R2 (no covariates): 0.00616 PGS AUROC (no covariates): 0.386 [0.0998, 0.67219] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008544 | PGS001164 (GBE_cancer1045) |
PSS007645| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Testicular cancer | — | AUROC: 0.83915 [0.8185, 0.85981] | R²: 0.1291 Incremental AUROC (full-covars): 0.03126 PGS R2 (no covariates): 0.01573 PGS AUROC (no covariates): 0.62956 [0.58302, 0.67611] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008594 | PGS001181 (GBE_HC643) |
PSS004555| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other hypothyroidism | — | AUROC: 0.70862 [0.67381, 0.74343] | R²: 0.06703 Incremental AUROC (full-covars): 0.01118 PGS R2 (no covariates): 0.01121 PGS AUROC (no covariates): 0.58683 [0.5475, 0.62616] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008595 | PGS001181 (GBE_HC643) |
PSS004556| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other hypothyroidism | — | AUROC: 0.71469 [0.64687, 0.78251] | R²: 0.07343 Incremental AUROC (full-covars): 0.03489 PGS R2 (no covariates): 0.01956 PGS AUROC (no covariates): 0.60912 [0.53836, 0.67988] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008596 | PGS001181 (GBE_HC643) |
PSS004557| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other hypothyroidism | — | AUROC: 0.76338 [0.75207, 0.77469] | R²: 0.14671 Incremental AUROC (full-covars): 0.06656 PGS R2 (no covariates): 0.06971 PGS AUROC (no covariates): 0.68243 [0.66936, 0.69549] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008597 | PGS001181 (GBE_HC643) |
PSS004558| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other hypothyroidism | — | AUROC: 0.74011 [0.72045, 0.75977] | R²: 0.1348 Incremental AUROC (full-covars): 0.03883 PGS R2 (no covariates): 0.04904 PGS AUROC (no covariates): 0.6475 [0.62543, 0.66957] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008598 | PGS001181 (GBE_HC643) |
PSS004559| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other hypothyroidism | — | AUROC: 0.76691 [0.7602, 0.77362] | R²: 0.15134 Incremental AUROC (full-covars): 0.0729 PGS R2 (no covariates): 0.07419 PGS AUROC (no covariates): 0.68962 [0.68178, 0.69747] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008943 | PGS001289 (GBE_cancer1065) |
PSS007656| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Thyroid cancer | — | AUROC: 0.72837 [0.59989, 0.85685] | R²: 0.0395 Incremental AUROC (full-covars): 0.01385 PGS R2 (no covariates): 0.0141 PGS AUROC (no covariates): 0.6101 [0.46446, 0.75575] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008944 | PGS001289 (GBE_cancer1065) |
PSS007657| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Thyroid cancer | — | AUROC: 0.83233 [0.67782, 0.98683] | R²: 0.16699 Incremental AUROC (full-covars): -0.00184 PGS R2 (no covariates): 0.01024 PGS AUROC (no covariates): 0.54057 [0.24283, 0.83831] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008945 | PGS001289 (GBE_cancer1065) |
PSS007658| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Thyroid cancer | — | AUROC: 0.71465 [0.65621, 0.77309] | R²: 0.04643 Incremental AUROC (full-covars): 0.00897 PGS R2 (no covariates): 0.00455 PGS AUROC (no covariates): 0.55967 [0.48236, 0.63699] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008946 | PGS001289 (GBE_cancer1065) |
PSS007659| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Thyroid cancer | — | AUROC: 0.71171 [0.57425, 0.84917] | R²: 0.04277 Incremental AUROC (full-covars): 0.00229 PGS R2 (no covariates): 0.00022 PGS AUROC (no covariates): 0.51375 [0.35907, 0.66843] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008947 | PGS001289 (GBE_cancer1065) |
PSS007660| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Thyroid cancer | — | AUROC: 0.63744 [0.5901, 0.68478] | R²: 0.016 Incremental AUROC (full-covars): 0.03389 PGS R2 (no covariates): 0.01236 PGS AUROC (no covariates): 0.61843 [0.56413, 0.67273] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008963 | PGS001293 (GBE_HC1123) |
PSS004134| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other diseases of liver | — | AUROC: 0.63246 [0.57311, 0.69181] | R²: 0.03109 Incremental AUROC (full-covars): -0.0062 PGS R2 (no covariates): 0.0 PGS AUROC (no covariates): 0.50545 [0.44895, 0.56196] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008964 | PGS001293 (GBE_HC1123) |
PSS004135| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other diseases of liver | — | AUROC: 0.69904 [0.62545, 0.77263] | PGS R2 (no covariates): 0.01113 Incremental AUROC (full-covars): 0.02137 R²: 0.05749 PGS AUROC (no covariates): 0.60324 [0.52305, 0.68342] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008965 | PGS001293 (GBE_HC1123) |
PSS004136| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other diseases of liver | — | AUROC: 0.63842 [0.61377, 0.66307] | R²: 0.02524 Incremental AUROC (full-covars): 0.02435 PGS R2 (no covariates): 0.01187 PGS AUROC (no covariates): 0.59189 [0.56464, 0.61913] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008966 | PGS001293 (GBE_HC1123) |
PSS004137| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other diseases of liver | — | AUROC: 0.60451 [0.56674, 0.64227] | R²: 0.01731 Incremental AUROC (full-covars): 0.00746 PGS R2 (no covariates): 0.00179 PGS AUROC (no covariates): 0.53523 [0.49417, 0.57629] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008967 | PGS001293 (GBE_HC1123) |
PSS004138| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other diseases of liver | — | AUROC: 0.58372 [0.56726, 0.60017] | R²: 0.00961 Incremental AUROC (full-covars): 0.01977 PGS R2 (no covariates): 0.00443 PGS AUROC (no covariates): 0.5536 [0.53634, 0.57086] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008968 | PGS001294 (GBE_HC649) |
PSS004575| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.70052 [0.68094, 0.7201] | R²: 0.10493 Incremental AUROC (full-covars): 0.00213 PGS R2 (no covariates): 0.00615 PGS AUROC (no covariates): 0.54526 [0.52378, 0.56673] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008969 | PGS001294 (GBE_HC649) |
PSS004576| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.75536 [0.71488, 0.79584] | R²: 0.1242 Incremental AUROC (full-covars): 0.01544 PGS R2 (no covariates): 0.01604 PGS AUROC (no covariates): 0.5808 [0.52621, 0.63538] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008970 | PGS001294 (GBE_HC649) |
PSS004577| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.72888 [0.71557, 0.7422] | R²: 0.10344 Incremental AUROC (full-covars): 0.03534 PGS R2 (no covariates): 0.03413 PGS AUROC (no covariates): 0.63582 [0.62119, 0.65045] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008971 | PGS001294 (GBE_HC649) |
PSS004578| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.68707 [0.67293, 0.70121] | R²: 0.11343 Incremental AUROC (full-covars): 0.01724 PGS R2 (no covariates): 0.02384 PGS AUROC (no covariates): 0.58532 [0.56986, 0.60078] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008972 | PGS001294 (GBE_HC649) |
PSS004579| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.71038 [0.70256, 0.71821] | R²: 0.08854 Incremental AUROC (full-covars): 0.04133 PGS R2 (no covariates): 0.03493 PGS AUROC (no covariates): 0.63323 [0.62453, 0.64194] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008973 | PGS001295 (GBE_HC165) |
PSS004312| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68145 [0.62426, 0.73864] | R²: 0.04466 Incremental AUROC (full-covars): 0.00427 PGS R2 (no covariates): 0.00162 PGS AUROC (no covariates): 0.5359 [0.47698, 0.59482] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008974 | PGS001295 (GBE_HC165) |
PSS004313| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.83509 [0.71831, 0.95186] | R²: 0.20575 Incremental AUROC (full-covars): -0.00085 PGS R2 (no covariates): 0.00265 PGS AUROC (no covariates): 0.56328 [0.47919, 0.64736] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008975 | PGS001295 (GBE_HC165) |
PSS004314| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69318 [0.65625, 0.73011] | R²: 0.04603 Incremental AUROC (full-covars): 0.0115 PGS R2 (no covariates): 0.00675 PGS AUROC (no covariates): 0.58258 [0.54116, 0.62401] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008976 | PGS001295 (GBE_HC165) |
PSS004315| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.65806 [0.61856, 0.69756] | R²: 0.0392 Incremental AUROC (full-covars): 0.01243 PGS R2 (no covariates): 0.00618 PGS AUROC (no covariates): 0.5613 [0.5184, 0.60421] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008977 | PGS001295 (GBE_HC165) |
PSS004316| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68247 [0.66155, 0.70338] | R²: 0.03772 Incremental AUROC (full-covars): 0.01405 PGS R2 (no covariates): 0.00633 PGS AUROC (no covariates): 0.57592 [0.55208, 0.59975] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008978 | PGS001296 (GBE_HC648) |
PSS004570| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.66885 [0.62172, 0.71599] | R²: 0.04054 Incremental AUROC (full-covars): -0.01128 PGS R2 (no covariates): 0.00021 PGS AUROC (no covariates): 0.51906 [0.4689, 0.56923] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008979 | PGS001296 (GBE_HC648) |
PSS004571| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.89264 [0.80447, 0.98081] | R²: 0.19006 Incremental AUROC (full-covars): -0.01413 PGS R2 (no covariates): 0.00422 PGS AUROC (no covariates): 0.43531 [0.15162, 0.71901] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008980 | PGS001296 (GBE_HC648) |
PSS004572| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.70536 [0.66494, 0.74577] | R²: 0.0607 Incremental AUROC (full-covars): 0.12077 PGS R2 (no covariates): 0.05496 PGS AUROC (no covariates): 0.68941 [0.64672, 0.73209] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008981 | PGS001296 (GBE_HC648) |
PSS004573| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.67679 [0.6379, 0.71568] | R²: 0.04266 Incremental AUROC (full-covars): -0.01593 PGS R2 (no covariates): 0.0016 PGS AUROC (no covariates): 0.54249 [0.49552, 0.58946] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008982 | PGS001296 (GBE_HC648) |
PSS004574| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.65986 [0.63673, 0.68299] | R²: 0.03385 Incremental AUROC (full-covars): 0.06785 PGS R2 (no covariates): 0.02496 PGS AUROC (no covariates): 0.62694 [0.60131, 0.65256] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008983 | PGS001297 (GBE_HC337) |
PSS004457| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.78146 [0.64554, 0.91738] | R²: 0.08635 Incremental AUROC (full-covars): -0.05504 PGS R2 (no covariates): 0.00185 PGS AUROC (no covariates): 0.41884 [0.19064, 0.64704] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008984 | PGS001297 (GBE_HC337) |
PSS004458| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.79737 [0.708, 0.88674] | R²: 0.11683 Incremental AUROC (full-covars): 0.09636 PGS R2 (no covariates): 0.0912 PGS AUROC (no covariates): 0.77118 [0.67108, 0.87128] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008985 | PGS001297 (GBE_HC337) |
PSS004459| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.81031 [0.66359, 0.95703] | R²: 0.06825 Incremental AUROC (full-covars): -0.01908 PGS R2 (no covariates): 6e-05 PGS AUROC (no covariates): 0.53853 [0.37761, 0.69945] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008986 | PGS001297 (GBE_HC337) |
PSS004460| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7643 [0.7041, 0.8245] | R²: 0.06625 Incremental AUROC (full-covars): 0.19149 PGS R2 (no covariates): 0.06103 PGS AUROC (no covariates): 0.76543 [0.70744, 0.82342] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009122 | PGS001327 (GBE_HC221) |
PSS004359| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.68586 [0.66802, 0.7037] | R²: 0.09776 Incremental AUROC (full-covars): 0.00638 PGS R2 (no covariates): 0.00926 PGS AUROC (no covariates): 0.55541 [0.53643, 0.5744] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009123 | PGS001327 (GBE_HC221) |
PSS004360| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.69569 [0.64958, 0.7418] | R²: 0.08294 Incremental AUROC (full-covars): 0.01187 PGS R2 (no covariates): 0.01141 PGS AUROC (no covariates): 0.56178 [0.51127, 0.61228] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009124 | PGS001327 (GBE_HC221) |
PSS004361| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.70541 [0.69227, 0.71854] | R²: 0.08595 Incremental AUROC (full-covars): 0.04263 PGS R2 (no covariates): 0.03446 PGS AUROC (no covariates): 0.63125 [0.61738, 0.64511] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009125 | PGS001327 (GBE_HC221) |
PSS004362| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.68746 [0.67395, 0.70097] | R²: 0.11895 Incremental AUROC (full-covars): 0.02618 PGS R2 (no covariates): 0.03527 PGS AUROC (no covariates): 0.60108 [0.5865, 0.61565] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009126 | PGS001327 (GBE_HC221) |
PSS004363| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.69818 [0.69047, 0.70589] | R²: 0.08111 Incremental AUROC (full-covars): 0.04455 PGS R2 (no covariates): 0.03558 PGS AUROC (no covariates): 0.63112 [0.6228, 0.63945] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009132 | PGS001329 (GBE_HC652) |
PSS004580| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.69503 [0.67407, 0.716] | R²: 0.08972 Incremental AUROC (full-covars): 0.00332 PGS R2 (no covariates): 0.00713 PGS AUROC (no covariates): 0.55713 [0.53377, 0.58048] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009133 | PGS001329 (GBE_HC652) |
PSS004581| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.70891 [0.65305, 0.76477] | R²: 0.09058 Incremental AUROC (full-covars): 0.02211 PGS R2 (no covariates): 0.02321 PGS AUROC (no covariates): 0.60847 [0.55016, 0.66678] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009134 | PGS001329 (GBE_HC652) |
PSS004582| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.72437 [0.70887, 0.73987] | R²: 0.08424 Incremental AUROC (full-covars): 0.03715 PGS R2 (no covariates): 0.02619 PGS AUROC (no covariates): 0.62743 [0.60999, 0.64487] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009135 | PGS001329 (GBE_HC652) |
PSS004583| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.70359 [0.68854, 0.71865] | R²: 0.11885 Incremental AUROC (full-covars): 0.02262 PGS R2 (no covariates): 0.02671 PGS AUROC (no covariates): 0.59807 [0.58121, 0.61493] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009136 | PGS001329 (GBE_HC652) |
PSS004584| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.7046 [0.69521, 0.71399] | R²: 0.0749 Incremental AUROC (full-covars): 0.04078 PGS R2 (no covariates): 0.03024 PGS AUROC (no covariates): 0.63102 [0.62084, 0.64119] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM005178 | PGS001354 (PRS12_TC) |
PSS003603| European Ancestry| 2,370 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors | — | — | Relative Rate (RR): 1.57 [1.24, 1.98] | Attained age modeled by restricted cubic splines | — |
| PPM005179 | PGS001354 (PRS12_TC) |
PSS003603| European Ancestry| 2,370 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors who had received neck radiotherapy | — | — | Relative Rate (RR): 1.68 [1.29, 2.18] | Attained age modeled by restricted cubic splines | — |
| PPM005180 | PGS001354 (PRS12_TC) |
PSS003602| European Ancestry| 6,416 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors | — | — | Relative Rate (RR): 1.52 [1.25, 1.83] | Attained age modeled by restricted cubic splines | — |
| PPM005181 | PGS001354 (PRS12_TC) |
PSS003602| European Ancestry| 6,416 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors who had received neck radiotherapy | — | — | Relative Rate (RR): 1.42 [1.09, 1.85] | Attained age modeled by restricted cubic splines | — |
| PPM005182 | PGS001354 (PRS12_TC) |
PSS003602| European Ancestry| 6,416 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors who had not received neck radiotherapy | — | — | Relative Rate (RR): 1.66 [1.26, 2.2] | Attained age modeled by restricted cubic splines | — |
| PPM005183 | PGS001354 (PRS12_TC) |
PSS003603| European Ancestry| 2,370 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors aged 40 | — | AUROC: 0.83 C-index: 0.842 |
— | Clincial model (age at diagnosis, attained age modeled by restricted cubic splines, sex, combined treatment group) | — |
| PPM005184 | PGS001354 (PRS12_TC) |
PSS003602| European Ancestry| 6,416 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors aged 40 | — | AUROC: 0.73 C-index: 0.73 |
— | Clincial model (age at diagnosis, attained age modeled by restricted cubic splines, sex, combined treatment group) | — |
| PPM005185 | PGS001354 (PRS12_TC) |
PSS003603| European Ancestry| 2,370 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors aged 50 | — | AUROC: 0.82 C-index: 0.834 |
— | Clincial model (age at diagnosis, attained age modeled by restricted cubic splines, sex, combined treatment group) | — |
| PPM005186 | PGS001354 (PRS12_TC) |
PSS003602| European Ancestry| 6,416 individuals |
PGP000251 | Song N et al. Cancer Epidemiol Biomarkers Prev (2021) |
Reported Trait: Subsequent thyroid cancer in childhood cancer survivors aged 50 | — | AUROC: 0.72 C-index: 0.727 |
— | Clincial model (age at diagnosis, attained age modeled by restricted cubic splines, sex, combined treatment group) | — |
| PPM005189 | PGS001357 (T2D_AnnoPred_PRS) |
PSS003606| European Ancestry| 178,138 individuals |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6446 | — | Age, sex, PCs(1-10) | — |
| PPM007030 | PGS001371 (GBE_INI2976) |
PSS006886| African Ancestry| 673 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.28398 [0.26544, 0.30253] Incremental R2 (full-covars): -0.00362 PGS R2 (no covariates): 0.00112 [-0.0005, 0.00275] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007031 | PGS001371 (GBE_INI2976) |
PSS006887| East Asian Ancestry| 86 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.31131 [0.27489, 0.34772] Incremental R2 (full-covars): 0.00576 PGS R2 (no covariates): 0.00203 [-0.00223, 0.00629] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007032 | PGS001371 (GBE_INI2976) |
PSS006888| European Ancestry| 1,059 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.37828 [0.36879, 0.38778] Incremental R2 (full-covars): 0.02371 PGS R2 (no covariates): 0.04728 [0.04214, 0.05243] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007033 | PGS001371 (GBE_INI2976) |
PSS006889| South Asian Ancestry| 1,335 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.20384 [0.18792, 0.21975] Incremental R2 (full-covars): -0.00895 PGS R2 (no covariates): 0.00042 [-0.00049, 0.00133] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007034 | PGS001371 (GBE_INI2976) |
PSS006890| European Ancestry| 3,195 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.28031 [0.27455, 0.28606] Incremental R2 (full-covars): 0.02294 PGS R2 (no covariates): 0.03923 [0.03636, 0.0421] |
age, sex, UKB array type, Genotype PCs | — |
| PPM009254 | PGS001777 (3-SNP_cirr) |
PSS007668| European Ancestry| 1,766 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (females) | β: 0.897 (0.172) | AUROC: 0.635 (0.025) | Odds Ratio (OR, top 20% vs bottom 20%): 3.81 [2.05, 7.07] | — | — |
| PPM009255 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (males) | β: 0.8 (0.088) | AUROC: 0.635 (0.016) | Odds Ratio (OR, top 20% vs bottom 20%): 3.44 [2.48, 4.77] | — | — |
| PPM009256 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (females) | — | AUROC: 0.554 (0.036) | Odds Ratio (OR, top 20% vs bottom 20%): 2.08 [1.11, 3.89] | — | — |
| PPM009247 | PGS001777 (3-SNP_cirr) |
PSS007667| European Ancestry| 1,390 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis | β: 1.092 (0.099) | AUROC: 0.665 (0.014) | Odds Ratio (OR, top 20% vs bottom 20%): 5.99 [4.18, 8.6] | — | — |
| PPM009248 | PGS001777 (3-SNP_cirr) |
PSS007668| European Ancestry| 1,766 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis | β: 0.669 (0.09) | AUROC: 0.606 (0.014) | Odds Ratio (OR, top 20% vs bottom 20%): 2.81 [2.03, 3.89] | — | — |
| PPM009249 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis | β: 0.729 (0.08) | AUROC: 0.619 (0.014) | Odds Ratio (OR, top 20% vs bottom 20%): 3.1 [2.32, 4.14] | — | — |
| PPM009250 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis | β: 0.748 (0.073) | AUROC: 0.636 (0.015) | Odds Ratio (OR, top 20% vs bottom 20%): 3.37 [2.38, 4.78] | BMI, coffee | — |
| PPM009251 | PGS001777 (3-SNP_cirr) |
PSS007667| European Ancestry| 1,390 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (males) | β: 1.132 (0.116) | AUROC: 0.671 (0.016) | Odds Ratio (OR, top 20% vs bottom 20%): 6.18 [4.05, 9.41] | — | — |
| PPM009252 | PGS001777 (3-SNP_cirr) |
PSS007667| European Ancestry| 1,390 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (females) | β: 0.974 (0.192) | AUROC: 0.65 (0.027) | Odds Ratio (OR, top 20% vs bottom 20%): 5.4 [2.67, 10.92] | — | — |
| PPM009253 | PGS001777 (3-SNP_cirr) |
PSS007668| European Ancestry| 1,766 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis (males) | β: 0.575 (0.107) | AUROC: 0.592 (0.017) | Odds Ratio (OR, top 20% vs bottom 20%): 2.47 [1.68, 3.62] | — | — |
| PPM009257 | PGS001777 (3-SNP_cirr) |
PSS007667| European Ancestry| 1,390 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis in diabetics | — | — | Odds Ratio (OR, high vs. low PRS): 5.32 [2.06, 13.7] | — | PRS Thresholds: Low (<= 0), High( >0.70) |
| PPM009258 | PGS001777 (3-SNP_cirr) |
PSS007667| European Ancestry| 1,390 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis in non-diabetics | — | — | Odds Ratio (OR, high vs. low PRS): 4.77 [3.45, 6.58] | — | PRS Thresholds: Low (<= 0), High( >0.70) |
| PPM009259 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis in diabetics | — | — | Odds Ratio (OR, high vs. low PRS): 3.74 [2.16, 6.48] | — | PRS Thresholds: Low (<= 0), High( >0.70) |
| PPM009260 | PGS001777 (3-SNP_cirr) |
PSS007669| European Ancestry| 6,898 individuals |
PGP000258 | Whitfield JB et al. J Hepatol (2021) |
Reported Trait: Cirrhosis in non-diabetics | — | — | Odds Ratio (OR, high vs. low PRS): 2.37 [1.86, 3.03] | — | PRS Thresholds: Low (<= 0), High( >0.70) |
| PPM009277 | PGS001781 (T2D_PRSCS) |
PSS007684| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Type 2 diabetes (incident and prevalent) | OR: 1.59 [1.57, 1.61] | AUROC: 0.758 [0.756, 0.761] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009281 | PGS001781 (T2D_PRSCS) |
PSS007685| European Ancestry| 279,879 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.52 [1.49, 1.55] | AUROC: 0.852 [0.849, 0.855] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009287 | PGS001781 (T2D_PRSCS) |
PSS007692| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent type 2 diabetes | OR: 1.75 [1.72, 1.78] | AUROC: 0.725 [0.721, 0.729] | — | year of birth, sex | — |
| PPM009283 | PGS001781 (T2D_PRSCS) |
PSS007691| European Ancestry| 328,115 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.51 [1.48, 1.54] | AUROC: 0.669 [0.664, 0.675] | — | year of birth, sex | — |
| PPM009285 | PGS001781 (T2D_PRSCS) |
PSS007686| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent type 2 diabetes | OR: 1.59 [1.57, 1.61] | AUROC: 0.81 [0.808, 0.813] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009279 | PGS001781 (T2D_PRSCS) |
PSS007690| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Type 2 diabetes (incident and prevalent) | OR: 1.68 [1.65, 1.7] | AUROC: 0.708 [0.705, 0.711] | — | year of birth, sex | — |
| PPM009298 | PGS001794 (1kgeur_gbmi_leaveUKBBout_ThC_pst_eff_a1_b0.5_phiauto) |
PSS007717| European Ancestry| 358,476 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Thyroid cancer | — | AUROC: 0.676 | Nagelkerke's R2 (covariates regressed out): 0.01366 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009315 | PGS001799 (1kgeur_gbmi_ThC_pst_eff_a1_b0.5_phiauto) |
PSS007697| European Ancestry| 7,128 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Thyroid cancer | — | AUROC: 0.685 | Nagelkerke's R2 (covariates regressed out): 0.01036 | sex,age, 20PCs | — |
| PPM009374 | PGS001809 (portability-PLR_193) |
PSS009279| European Ancestry| 19,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0307 [0.0168, 0.0446] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009377 | PGS001809 (portability-PLR_193) |
PSS008383| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.0014 [-0.0586, 0.0557] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009378 | PGS001809 (portability-PLR_193) |
PSS008161| South Asian Ancestry| 6,305 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0052 [-0.0195, 0.0299] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009379 | PGS001809 (portability-PLR_193) |
PSS007948| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.0121 [-0.0585, 0.0344] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009380 | PGS001809 (portability-PLR_193) |
PSS007730| African Ancestry| 2,453 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0102 [-0.0296, 0.0499] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009381 | PGS001809 (portability-PLR_193) |
PSS008833| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0008 [-0.0307, 0.0323] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009375 | PGS001809 (portability-PLR_193) |
PSS009053| European Ancestry| 4,120 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.0082 [-0.0388, 0.0225] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009376 | PGS001809 (portability-PLR_193) |
PSS008607| European Ancestry| 6,640 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0196 [-0.0045, 0.0437] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009413 | PGS001814 (portability-PLR_241.2) |
PSS009058| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0146 [-0.0168, 0.0459] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009414 | PGS001814 (portability-PLR_241.2) |
PSS008612| European Ancestry| 6,363 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0205 [-0.0041, 0.0451] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009415 | PGS001814 (portability-PLR_241.2) |
PSS008388| Greater Middle Eastern Ancestry| 1,140 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0211 [-0.0375, 0.0796] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009416 | PGS001814 (portability-PLR_241.2) |
PSS008166| South Asian Ancestry| 5,927 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0654 [0.0399, 0.0907] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009417 | PGS001814 (portability-PLR_241.2) |
PSS007953| East Asian Ancestry| 1,744 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.025 [-0.0222, 0.0722] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009418 | PGS001814 (portability-PLR_241.2) |
PSS007734| African Ancestry| 2,378 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0403 [0.0, 0.0806] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009419 | PGS001814 (portability-PLR_241.2) |
PSS008837| African Ancestry| 3,830 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0442 [0.0125, 0.0759] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009412 | PGS001814 (portability-PLR_241.2) |
PSS009284| European Ancestry| 19,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0277 [0.0135, 0.0419] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009420 | PGS001815 (portability-PLR_242) |
PSS009285| European Ancestry| 19,108 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0191 [0.0049, 0.0332] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009421 | PGS001815 (portability-PLR_242) |
PSS009059| European Ancestry| 3,938 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0288 [-0.0025, 0.06] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009422 | PGS001815 (portability-PLR_242) |
PSS008613| European Ancestry| 6,381 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0232 [-0.0014, 0.0477] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009423 | PGS001815 (portability-PLR_242) |
PSS008389| Greater Middle Eastern Ancestry| 1,143 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): -0.0026 [-0.0611, 0.0559] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009424 | PGS001815 (portability-PLR_242) |
PSS008167| South Asian Ancestry| 5,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0473 [0.0219, 0.0726] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009425 | PGS001815 (portability-PLR_242) |
PSS007954| East Asian Ancestry| 1,754 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0177 [-0.0294, 0.0647] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009426 | PGS001815 (portability-PLR_242) |
PSS007735| African Ancestry| 2,410 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): -0.0007 [-0.0408, 0.0394] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009427 | PGS001815 (portability-PLR_242) |
PSS008838| African Ancestry| 3,836 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0182 [-0.0135, 0.0499] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009430 | PGS001816 (portability-PLR_244) |
PSS008614| European Ancestry| 6,601 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1003 [0.0763, 0.1241] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009428 | PGS001816 (portability-PLR_244) |
PSS009286| European Ancestry| 19,852 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1192 [0.1054, 0.1329] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009429 | PGS001816 (portability-PLR_244) |
PSS009060| European Ancestry| 4,100 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1349 [0.1047, 0.1649] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009431 | PGS001816 (portability-PLR_244) |
PSS008390| Greater Middle Eastern Ancestry| 1,186 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1247 [0.0677, 0.1808] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009432 | PGS001816 (portability-PLR_244) |
PSS008168| South Asian Ancestry| 6,272 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.11 [0.0854, 0.1344] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009433 | PGS001816 (portability-PLR_244) |
PSS007955| East Asian Ancestry| 1,782 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.044 [-0.0027, 0.0905] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009434 | PGS001816 (portability-PLR_244) |
PSS007736| African Ancestry| 2,434 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.0033 [-0.0366, 0.0432] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009435 | PGS001816 (portability-PLR_244) |
PSS008839| African Ancestry| 3,876 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.0419 [0.0104, 0.0734] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009436 | PGS001817 (portability-PLR_250.1) |
PSS009287| European Ancestry| 18,975 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0752 [0.061, 0.0893] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009437 | PGS001817 (portability-PLR_250.1) |
PSS009061| European Ancestry| 3,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0684 [0.0372, 0.0994] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009438 | PGS001817 (portability-PLR_250.1) |
PSS008615| European Ancestry| 6,300 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0739 [0.0493, 0.0985] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009439 | PGS001817 (portability-PLR_250.1) |
PSS008391| Greater Middle Eastern Ancestry| 1,107 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0349 [-0.0246, 0.0941] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009440 | PGS001817 (portability-PLR_250.1) |
PSS008169| South Asian Ancestry| 5,228 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0224 [-0.0047, 0.0496] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009441 | PGS001817 (portability-PLR_250.1) |
PSS007956| East Asian Ancestry| 1,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0001 [-0.0475, 0.0474] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009442 | PGS001817 (portability-PLR_250.1) |
PSS007737| African Ancestry| 2,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0006 [-0.0426, 0.0414] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009443 | PGS001817 (portability-PLR_250.1) |
PSS008840| African Ancestry| 3,490 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0187 [-0.052, 0.0146] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009444 | PGS001818 (portability-PLR_250.2) |
PSS009288| European Ancestry| 19,931 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1246 [0.1109, 0.1382] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009445 | PGS001818 (portability-PLR_250.2) |
PSS009062| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0862 [0.0557, 0.1165] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009447 | PGS001818 (portability-PLR_250.2) |
PSS008392| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1735 [0.1176, 0.2284] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009448 | PGS001818 (portability-PLR_250.2) |
PSS008170| South Asian Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1556 [0.1314, 0.1796] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009449 | PGS001818 (portability-PLR_250.2) |
PSS007957| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0665 [0.0202, 0.1125] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009450 | PGS001818 (portability-PLR_250.2) |
PSS007738| African Ancestry| 2,476 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0956 [0.0562, 0.1346] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009451 | PGS001818 (portability-PLR_250.2) |
PSS008841| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0522 [0.0208, 0.0836] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009446 | PGS001818 (portability-PLR_250.2) |
PSS008616| European Ancestry| 6,646 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.108 [0.0842, 0.1317] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009769 | PGS001860 (portability-PLR_571.5) |
PSS009335| European Ancestry| 19,586 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0413 [0.0273, 0.0553] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009770 | PGS001860 (portability-PLR_571.5) |
PSS009109| European Ancestry| 4,060 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.034 [0.0032, 0.0648] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009771 | PGS001860 (portability-PLR_571.5) |
PSS008663| European Ancestry| 6,543 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0281 [0.0038, 0.0523] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009772 | PGS001860 (portability-PLR_571.5) |
PSS008437| Greater Middle Eastern Ancestry| 1,185 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0168 [-0.0407, 0.0741] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009773 | PGS001860 (portability-PLR_571.5) |
PSS008217| South Asian Ancestry| 6,209 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0246 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009774 | PGS001860 (portability-PLR_571.5) |
PSS007998| East Asian Ancestry| 1,783 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0455 [-0.0012, 0.092] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009775 | PGS001860 (portability-PLR_571.5) |
PSS007782| African Ancestry| 2,429 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): -0.013 [-0.0529, 0.0269] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009776 | PGS001860 (portability-PLR_571.5) |
PSS008886| African Ancestry| 3,837 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): -0.0259 [-0.0576, 0.0058] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011018 | PGS002018 (portability-ldpred2_193) |
PSS009279| European Ancestry| 19,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0295 [0.0157, 0.0434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011019 | PGS002018 (portability-ldpred2_193) |
PSS009053| European Ancestry| 4,120 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.0056 [-0.0362, 0.0251] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011020 | PGS002018 (portability-ldpred2_193) |
PSS008607| European Ancestry| 6,640 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0208 [-0.0033, 0.0448] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011021 | PGS002018 (portability-ldpred2_193) |
PSS008383| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.0107 [-0.0677, 0.0465] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011022 | PGS002018 (portability-ldpred2_193) |
PSS008161| South Asian Ancestry| 6,305 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0149 [-0.0098, 0.0396] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011023 | PGS002018 (portability-ldpred2_193) |
PSS007948| East Asian Ancestry| 1,801 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): -0.004 [-0.0505, 0.0424] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011024 | PGS002018 (portability-ldpred2_193) |
PSS007730| African Ancestry| 2,453 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0184 [-0.0213, 0.0581] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011025 | PGS002018 (portability-ldpred2_193) |
PSS008833| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyroid cancer | — | — | Partial Correlation (partial-r): 0.0029 [-0.0286, 0.0343] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011050 | PGS002022 (portability-ldpred2_241.2) |
PSS009284| European Ancestry| 19,043 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.024 [0.0098, 0.0382] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011051 | PGS002022 (portability-ldpred2_241.2) |
PSS009058| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0213 [-0.01, 0.0527] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011052 | PGS002022 (portability-ldpred2_241.2) |
PSS008612| European Ancestry| 6,363 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.019 [-0.0056, 0.0436] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011053 | PGS002022 (portability-ldpred2_241.2) |
PSS008388| Greater Middle Eastern Ancestry| 1,140 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0214 [-0.0372, 0.0799] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011054 | PGS002022 (portability-ldpred2_241.2) |
PSS008166| South Asian Ancestry| 5,927 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0677 [0.0423, 0.0931] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011055 | PGS002022 (portability-ldpred2_241.2) |
PSS007953| East Asian Ancestry| 1,744 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0096 [-0.0376, 0.0568] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011056 | PGS002022 (portability-ldpred2_241.2) |
PSS007734| African Ancestry| 2,378 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0282 [-0.0122, 0.0685] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011057 | PGS002022 (portability-ldpred2_241.2) |
PSS008837| African Ancestry| 3,830 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Nontoxic multinodular goiter | — | — | Partial Correlation (partial-r): 0.0496 [0.0179, 0.0813] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011058 | PGS002023 (portability-ldpred2_242) |
PSS009285| European Ancestry| 19,108 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0199 [0.0057, 0.034] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011059 | PGS002023 (portability-ldpred2_242) |
PSS009059| European Ancestry| 3,938 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0345 [0.0032, 0.0658] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011060 | PGS002023 (portability-ldpred2_242) |
PSS008613| European Ancestry| 6,381 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0195 [-0.0051, 0.044] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011061 | PGS002023 (portability-ldpred2_242) |
PSS008389| Greater Middle Eastern Ancestry| 1,143 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): -0.0281 [-0.0864, 0.0305] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011062 | PGS002023 (portability-ldpred2_242) |
PSS008167| South Asian Ancestry| 5,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0457 [0.0203, 0.0711] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011063 | PGS002023 (portability-ldpred2_242) |
PSS007954| East Asian Ancestry| 1,754 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.039 [-0.0081, 0.0859] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011064 | PGS002023 (portability-ldpred2_242) |
PSS007735| African Ancestry| 2,410 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0027 [-0.0374, 0.0428] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011065 | PGS002023 (portability-ldpred2_242) |
PSS008838| African Ancestry| 3,836 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Thyrotoxicosis with or without goiter | — | — | Partial Correlation (partial-r): 0.0172 [-0.0146, 0.0489] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011066 | PGS002024 (portability-ldpred2_244) |
PSS009286| European Ancestry| 19,852 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.122 [0.1083, 0.1357] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011067 | PGS002024 (portability-ldpred2_244) |
PSS009060| European Ancestry| 4,100 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.143 [0.1128, 0.1729] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011068 | PGS002024 (portability-ldpred2_244) |
PSS008614| European Ancestry| 6,601 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1035 [0.0795, 0.1273] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011069 | PGS002024 (portability-ldpred2_244) |
PSS008390| Greater Middle Eastern Ancestry| 1,186 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.133 [0.0762, 0.189] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011070 | PGS002024 (portability-ldpred2_244) |
PSS008168| South Asian Ancestry| 6,272 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.1186 [0.094, 0.1429] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011071 | PGS002024 (portability-ldpred2_244) |
PSS007955| East Asian Ancestry| 1,782 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.047 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011072 | PGS002024 (portability-ldpred2_244) |
PSS007736| African Ancestry| 2,434 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.0093 [-0.0306, 0.0492] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011073 | PGS002024 (portability-ldpred2_244) |
PSS008839| African Ancestry| 3,876 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Partial Correlation (partial-r): 0.0396 [0.0081, 0.0711] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011074 | PGS002025 (portability-ldpred2_250.1) |
PSS009287| European Ancestry| 18,975 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0824 [0.0682, 0.0965] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011075 | PGS002025 (portability-ldpred2_250.1) |
PSS009061| European Ancestry| 3,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0666 [0.0354, 0.0976] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011076 | PGS002025 (portability-ldpred2_250.1) |
PSS008615| European Ancestry| 6,300 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0719 [0.0472, 0.0964] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011077 | PGS002025 (portability-ldpred2_250.1) |
PSS008391| Greater Middle Eastern Ancestry| 1,107 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0529 [-0.0066, 0.112] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011078 | PGS002025 (portability-ldpred2_250.1) |
PSS008169| South Asian Ancestry| 5,228 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0228 [-0.0044, 0.0499] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011079 | PGS002025 (portability-ldpred2_250.1) |
PSS007956| East Asian Ancestry| 1,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0048 [-0.0522, 0.0427] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011080 | PGS002025 (portability-ldpred2_250.1) |
PSS007737| African Ancestry| 2,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0089 [-0.0331, 0.0509] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011081 | PGS002025 (portability-ldpred2_250.1) |
PSS008840| African Ancestry| 3,490 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.013 [-0.0463, 0.0203] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011082 | PGS002026 (portability-ldpred2_250.2) |
PSS009288| European Ancestry| 19,931 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1304 [0.1168, 0.1441] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011083 | PGS002026 (portability-ldpred2_250.2) |
PSS009062| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0862 [0.0558, 0.1165] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011084 | PGS002026 (portability-ldpred2_250.2) |
PSS008616| European Ancestry| 6,646 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1134 [0.0896, 0.1371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011085 | PGS002026 (portability-ldpred2_250.2) |
PSS008392| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1764 [0.1205, 0.2312] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011087 | PGS002026 (portability-ldpred2_250.2) |
PSS007957| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0786 [0.0324, 0.1246] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011088 | PGS002026 (portability-ldpred2_250.2) |
PSS007738| African Ancestry| 2,476 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1001 [0.0607, 0.1391] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011089 | PGS002026 (portability-ldpred2_250.2) |
PSS008841| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0806 [0.0493, 0.1118] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011086 | PGS002026 (portability-ldpred2_250.2) |
PSS008170| South Asian Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.158 [0.1338, 0.182] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM020894 | PGS002026 (portability-ldpred2_250.2) |
PSS011441| African Ancestry| 504 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 1.1 [0.9, 1.35] | — | — | — | — |
| PPM020889 | PGS002026 (portability-ldpred2_250.2) |
PSS011442| European Ancestry| 564 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 0.96 [0.8, 1.16] | — | — | — | — |
| PPM011429 | PGS002071 (portability-ldpred2_571.5) |
PSS009335| European Ancestry| 19,586 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0415 [0.0275, 0.0555] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011430 | PGS002071 (portability-ldpred2_571.5) |
PSS009109| European Ancestry| 4,060 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.029 [-0.0018, 0.0598] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011431 | PGS002071 (portability-ldpred2_571.5) |
PSS008663| European Ancestry| 6,543 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0289 [0.0047, 0.0532] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011432 | PGS002071 (portability-ldpred2_571.5) |
PSS008437| Greater Middle Eastern Ancestry| 1,185 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0227 [-0.0348, 0.08] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011433 | PGS002071 (portability-ldpred2_571.5) |
PSS008217| South Asian Ancestry| 6,209 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.0224 [-0.0025, 0.0473] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011434 | PGS002071 (portability-ldpred2_571.5) |
PSS007998| East Asian Ancestry| 1,783 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): 0.043 [-0.0037, 0.0895] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011435 | PGS002071 (portability-ldpred2_571.5) |
PSS007782| African Ancestry| 2,429 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): -0.0077 [-0.0476, 0.0323] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011436 | PGS002071 (portability-ldpred2_571.5) |
PSS008886| African Ancestry| 3,837 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | — | — | Partial Correlation (partial-r): -0.0167 [-0.0484, 0.015] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012733 | PGS002243 (ldpred_t2d) |
PSS009522| European Ancestry| 258,402 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.58 [1.56, 1.6] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012737 | PGS002243 (ldpred_t2d) |
PSS009518| European Ancestry| 110,597 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.55 [1.51, 1.59] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012741 | PGS002243 (ldpred_t2d) |
PSS009514| East Asian Ancestry| 178,726 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.37 [1.36, 1.39] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012745 | PGS002243 (ldpred_t2d) |
PSS009526| European Ancestry| 69,422 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.64 [1.6, 1.69] | — | — | birth year, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012749 | PGS002243 (ldpred_t2d) |
PSS009534| European Ancestry| 25,696 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.46 [1.41, 1.51] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012753 | PGS002243 (ldpred_t2d) |
PSS009530| African Ancestry| 1,535 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.24 [1.09, 1.42] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012757 | PGS002243 (ldpred_t2d) |
PSS009542| European Ancestry| 343,676 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.78 [1.75, 1.81] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012762 | PGS002243 (ldpred_t2d) |
PSS009538| African Ancestry| 7,618 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.46 [1.32, 1.62] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012767 | PGS002243 (ldpred_t2d) |
PSS009546| South Asian Ancestry| 7,628 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.66 [1.55, 1.79] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM016269 | PGS002250 (PRS_S4) |
PSS010091| European Ancestry| 198,758 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.38 [1.28, 1.48] | AUROC: 0.588 | — | — | — |
| PPM016270 | PGS002250 (PRS_S4) |
PSS010087| European Ancestry| 18,915 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer in BRCA1 carriers | HR: 1.36 [1.29, 1.43] | AUROC: 0.592 | — | — | — |
| PPM016271 | PGS002250 (PRS_S4) |
PSS010088| European Ancestry| 12,337 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer in BRCA2 carriers | HR: 1.49 [1.35, 1.64] | AUROC: 0.624 | — | — | — |
| PPM016272 | PGS002250 (PRS_S4) |
PSS010090| East Asian Ancestry| 7,669 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.14 [1.08, 1.19] | AUROC: 0.538 | — | — | — |
| PPM016273 | PGS002250 (PRS_S4) |
PSS010089| African Ancestry| 1,072 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.38 [1.21, 1.58] | AUROC: 0.593 | — | — | — |
| PPM012834 | PGS002256 (GRS4_GDM) |
PSS009573| East Asian Ancestry| 985 individuals |
PGP000282 | Wu Q et al. Diabetol Metab Syndr (2022) |
Reported Trait: Gestational diabetes mellitus in early pregnancy | — | AUROC: 0.62 [0.573, 0.667] | — | — | — |
| PPM012888 | PGS002264 (PRS_Combined) |
PSS009595| Ancestry Not Reported| 11,462 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma | — | AUROC: 0.605 [0.587, 0.623] | Positive predictive values (PPV highest quintile): 14.4 [13, 15.9] | — | — |
| PPM012894 | PGS002264 (PRS_Combined) |
PSS009600| Ancestry Not Reported| 206 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with long-standing diabetes mellitus) | — | — | Positive predictive values (PPV highest quintile): 0.239 [0.181, 0.303] | — | — |
| PPM012892 | PGS002264 (PRS_Combined) |
PSS009598| Ancestry Not Reported| 10,259 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (without diabetes mellitus) | — | AUROC: 0.594 [0.573, 0.614] | Positive predictive values (PPV highest quintile): 0.119 [0.105, 0.134] | — | — |
| PPM012895 | PGS002264 (PRS_Combined) |
PSS009600| Ancestry Not Reported| 206 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with long-standing diabetes mellitus) | OR: 1.873 [1.53, 2.292] | — | — | principal components (PC 1-10) | — |
| PPM012896 | PGS002264 (PRS_Combined) |
PSS009601| Ancestry Not Reported| 998 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with new onset diabetes mellitus) | — | — | Positive predictive values (PPV highest quintile): 0.867 [0.732, 0.949] | — | — |
| PPM012897 | PGS002264 (PRS_Combined) |
PSS009601| Ancestry Not Reported| 998 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with new onset diabetes mellitus) | OR: 1.885 [1.279, 2.778] | — | — | principal components (PC 1-10) | — |
| PPM012898 | PGS002264 (PRS_Combined) |
PSS009596| Ancestry Not Reported| 1,203 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with diabetes mellitus) | OR: 1.674 [1.443, 1.942] | — | — | principal components (PC 1-10) | — |
| PPM012899 | PGS002264 (PRS_Combined) |
PSS009596| Ancestry Not Reported| 1,203 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (with diabetes mellitus) | — | AUROC: 0.645 | — | — | — |
| PPM012900 | PGS002264 (PRS_Combined) |
PSS009597| Ancestry Not Reported| 242 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (< 60 years) | OR: 1.633 [1.292, 2.064] | — | — | principal components (PC 1-10) | — |
| PPM012901 | PGS002264 (PRS_Combined) |
PSS009599| Ancestry Not Reported| 274 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (60 years) | OR: 1.538 [1.287, 1.837] | — | — | principal components (PC 1-10) | — |
| PPM012893 | PGS002264 (PRS_Combined) |
PSS009598| Ancestry Not Reported| 10,259 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma (without diabetes mellitus) | OR: 1.386 [1.288, 1.492] | — | — | principal components (PC 1-10) | — |
| PPM012889 | PGS002264 (PRS_Combined) |
PSS009595| Ancestry Not Reported| 11,462 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma | — | — | HR (highest vs lowest quintile): 2.738 [2.227, 3.365] | Smoking (never, current and previous), waist circumference (cm), DM onset (No DM, NODM, LSDM) and first-degree family history of digestive cancer (yes/no) | — |
| PPM012890 | PGS002264 (PRS_Combined) |
PSS009595| Ancestry Not Reported| 11,462 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma | — | AUROC: 0.83 [0.8, 0.86] | — | Age of participants at recruitment, age when DM diagnosed, DM onset (No DM, NODM, LSDM), waist circumference (cm), and first-degree family history of digestive cancer (yes/no)., clinical risk | — |
| PPM012891 | PGS002264 (PRS_Combined) |
PSS009595| Ancestry Not Reported| 11,462 individuals |
PGP000293 | Sharma S et al. Gastroenterology (2022) |
Reported Trait: Incident pancreatic ductal adenocarcinoma | OR: 1.43 | — | — | principal components (PC 1-10) | — |
| PPM012948 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (normal BMI) | β: 37.31 (16.7) | — | R²: 0.012 | — | — |
| PPM012947 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis | — | — | Z: 5.2 | — | Z-score p-value < 0.0001 |
| PPM012949 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (overweight BMI) | β: 32.68 (20.7) | — | R²: 0.0097 | — | — |
| PPM012950 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (obese BMI) | β: 18.9 (10.76) | — | R²: 0.0036 | — | — |
| PPM012973 | PGS002282 (GRS68_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels | β: 0.13 (0.002) | — | — | — | — |
| PPM012975 | PGS002282 (GRS68_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x physical activity interaction | β: -0.28 (0.053) | — | — | — | — |
| PPM012976 | PGS002282 (GRS68_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x grip strength interaction | β: -0.0067 (0.002) | — | — | — | — |
| PPM012977 | PGS002282 (GRS68_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x BMI interaction | β: 0.037 (0.002) | — | — | — | — |
| PPM012981 | PGS002282 (GRS68_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: Nonalcoholic fatty liver disease in those with normal weight and high level of physical activity | — | — | Odds Ratio (OR, high vs. low GRS): 1.6 | Sex, age, socioeconomic status, assessment center, genotyping array, and the first 10 principal components | — |
| PPM012974 | PGS002283 (GRS15_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels | β: 0.094 (0.002) | — | — | — | — |
| PPM012978 | PGS002283 (GRS15_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x physical activity interaction | β: -0.3 (0.053) | — | — | — | — |
| PPM012979 | PGS002283 (GRS15_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x grip strength interaction | β: -0.011 (0.002) | — | — | — | — |
| PPM012980 | PGS002283 (GRS15_NAFLD) |
PSS009638| European Ancestry| 25,716 individuals |
PGP000312 | Schnurr TM et al. Hepatol Commun (2022) |
Reported Trait: ALT levels x BMI interaction | β: 0.039 (0.002) | — | — | — | — |
| PPM013067 | PGS002308 (PRScsx_T2D) |
PSS009671| African Ancestry| 6,745 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.7 [1.58, 1.84] | AUROC: 0.631 | R²: 0.046 | age, sex, top 10 PCs | — |
| PPM013064 | PGS002308 (PRScsx_T2D) |
PSS009677| European Ancestry| 54,793 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.96 [1.91, 2.02] | AUROC: 0.793 | R²: 0.092 | age, sex, top 10 PCs, study site | — |
| PPM013065 | PGS002308 (PRScsx_T2D) |
PSS009676| African Ancestry| 12,472 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.54 [1.46, 1.64] | AUROC: 0.848 | R²: 0.028 | age, sex, top 10 PCs, study site | — |
| PPM013066 | PGS002308 (PRScsx_T2D) |
PSS009678| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.08 [1.84, 2.35] | AUROC: 0.851 | R²: 0.08 | age, sex, top 10 PCs, study site | — |
| PPM013068 | PGS002308 (PRScsx_T2D) |
PSS009669| African Ancestry| 5,498 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.85 [1.7, 2.01] | AUROC: 0.633 | R²: 0.036 | age, sex, top 10 PCs | — |
| PPM013069 | PGS002308 (PRScsx_T2D) |
PSS009670| African Ancestry| 1,896 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.75 [1.52, 2.02] | AUROC: 0.757 | R²: 0.062 | age, sex, top 10 PCs | — |
| PPM013070 | PGS002308 (PRScsx_T2D) |
PSS009675| African Ancestry| 655 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.37 [1.13, 1.65] | AUROC: 0.631 | R²: 0.015 | age, sex, top 10 PCs | — |
| PPM013071 | PGS002308 (PRScsx_T2D) |
PSS009672| East Asian Ancestry| 25,110 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.19 [2.05, 2.33] | AUROC: 0.81 | R²: 0.151 | age, sex, top 10 PCs | — |
| PPM013072 | PGS002308 (PRScsx_T2D) |
PSS009673| East Asian Ancestry| 54,078 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.01 [1.93, 2.1] | AUROC: 0.781 | R²: 0.129 | age, sex, top 10 PCs | — |
| PPM013073 | PGS002308 (PRScsx_T2D) |
PSS009674| East Asian Ancestry| 10,378 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.16 [1.96, 2.38] | AUROC: 0.802 | R²: 0.153 | age, sex, top 10 PCs | — |
| PPM013086 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013135 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013184 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0159 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013233 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.028 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013089 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013138 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0029 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013187 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0101 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013236 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0219 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013101 | PGS002336 (disease_HYPOTHYROIDISM_SELF_REP.BOLT-LMM) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0045 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013150 | PGS002336 (disease_HYPOTHYROIDISM_SELF_REP.BOLT-LMM) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0111 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013248 | PGS002336 (disease_HYPOTHYROIDISM_SELF_REP.BOLT-LMM) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0173 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013199 | PGS002336 (disease_HYPOTHYROIDISM_SELF_REP.BOLT-LMM) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0247 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013116 | PGS002351 (disease_THYROID_ANY_SELF_REP.BOLT-LMM) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0032 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013165 | PGS002351 (disease_THYROID_ANY_SELF_REP.BOLT-LMM) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0016 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013214 | PGS002351 (disease_THYROID_ANY_SELF_REP.BOLT-LMM) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0236 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013263 | PGS002351 (disease_THYROID_ANY_SELF_REP.BOLT-LMM) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0191 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013119 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013168 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013217 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0135 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013266 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0218 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013291 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013314 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0148 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013360 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0091 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013337 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013374 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013423 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0017 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013472 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013521 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013377 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013426 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013475 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013524 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013389 | PGS002408 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.0001) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013438 | PGS002408 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.0001) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013487 | PGS002408 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.0001) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0003 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013536 | PGS002408 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.0001) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013404 | PGS002423 (disease_THYROID_ANY_SELF_REP.P+T.0.0001) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013453 | PGS002423 (disease_THYROID_ANY_SELF_REP.P+T.0.0001) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0004 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013502 | PGS002423 (disease_THYROID_ANY_SELF_REP.P+T.0.0001) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013551 | PGS002423 (disease_THYROID_ANY_SELF_REP.P+T.0.0001) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013407 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013505 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013554 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013456 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0032 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013570 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013619 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0056 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013717 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013668 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013622 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013671 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013720 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013573 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013585 | PGS002457 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.001) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013634 | PGS002457 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.001) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013683 | PGS002457 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.001) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013732 | PGS002457 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.001) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013600 | PGS002472 (disease_THYROID_ANY_SELF_REP.P+T.0.001) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013649 | PGS002472 (disease_THYROID_ANY_SELF_REP.P+T.0.001) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013698 | PGS002472 (disease_THYROID_ANY_SELF_REP.P+T.0.001) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013747 | PGS002472 (disease_THYROID_ANY_SELF_REP.P+T.0.001) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013603 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013652 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0041 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013701 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013750 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013766 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013815 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013864 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013913 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013769 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013867 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013916 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013818 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013781 | PGS002506 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.01) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013830 | PGS002506 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.01) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013879 | PGS002506 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.01) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013928 | PGS002506 (disease_HYPOTHYROIDISM_SELF_REP.P+T.0.01) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013796 | PGS002521 (disease_THYROID_ANY_SELF_REP.P+T.0.01) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013845 | PGS002521 (disease_THYROID_ANY_SELF_REP.P+T.0.01) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013894 | PGS002521 (disease_THYROID_ANY_SELF_REP.P+T.0.01) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013943 | PGS002521 (disease_THYROID_ANY_SELF_REP.P+T.0.01) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013799 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013848 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0033 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013897 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013946 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013962 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014011 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014060 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014109 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013965 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014014 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014063 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014112 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0003 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014026 | PGS002555 (disease_HYPOTHYROIDISM_SELF_REP.P+T.1e-06) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014075 | PGS002555 (disease_HYPOTHYROIDISM_SELF_REP.P+T.1e-06) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0012 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014124 | PGS002555 (disease_HYPOTHYROIDISM_SELF_REP.P+T.1e-06) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013977 | PGS002555 (disease_HYPOTHYROIDISM_SELF_REP.P+T.1e-06) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013992 | PGS002570 (disease_THYROID_ANY_SELF_REP.P+T.1e-06) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014041 | PGS002570 (disease_THYROID_ANY_SELF_REP.P+T.1e-06) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014090 | PGS002570 (disease_THYROID_ANY_SELF_REP.P+T.1e-06) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014139 | PGS002570 (disease_THYROID_ANY_SELF_REP.P+T.1e-06) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014093 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013995 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014044 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014142 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014305 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014158 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014207 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014256 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014161 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014210 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014308 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014259 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014173 | PGS002604 (disease_HYPOTHYROIDISM_SELF_REP.P+T.5e-08) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014222 | PGS002604 (disease_HYPOTHYROIDISM_SELF_REP.P+T.5e-08) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014271 | PGS002604 (disease_HYPOTHYROIDISM_SELF_REP.P+T.5e-08) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0015 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014320 | PGS002604 (disease_HYPOTHYROIDISM_SELF_REP.P+T.5e-08) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014188 | PGS002619 (disease_THYROID_ANY_SELF_REP.P+T.5e-08) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014237 | PGS002619 (disease_THYROID_ANY_SELF_REP.P+T.5e-08) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014286 | PGS002619 (disease_THYROID_ANY_SELF_REP.P+T.5e-08) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0012 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014335 | PGS002619 (disease_THYROID_ANY_SELF_REP.P+T.5e-08) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0003 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014191 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014240 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014289 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014338 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014354 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014403 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0097 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014452 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0136 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014501 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0339 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014357 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014455 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0105 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014504 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0244 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014406 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0029 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014369 | PGS002653 (disease_HYPOTHYROIDISM_SELF_REP.PolyFun-pred) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0046 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPOTHYROIDISM_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014418 | PGS002653 (disease_HYPOTHYROIDISM_SELF_REP.PolyFun-pred) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0129 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPOTHYROIDISM_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014467 | PGS002653 (disease_HYPOTHYROIDISM_SELF_REP.PolyFun-pred) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0262 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPOTHYROIDISM_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014516 | PGS002653 (disease_HYPOTHYROIDISM_SELF_REP.PolyFun-pred) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0183 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPOTHYROIDISM_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014384 | PGS002668 (disease_THYROID_ANY_SELF_REP.PolyFun-pred) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0034 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_THYROID_ANY_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014433 | PGS002668 (disease_THYROID_ANY_SELF_REP.PolyFun-pred) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0034 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_THYROID_ANY_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014482 | PGS002668 (disease_THYROID_ANY_SELF_REP.PolyFun-pred) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0254 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_THYROID_ANY_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014531 | PGS002668 (disease_THYROID_ANY_SELF_REP.PolyFun-pred) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0186 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_THYROID_ANY_SELF_REP.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014387 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014436 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0072 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014485 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0128 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014534 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0251 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014599 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014648 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0145 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014697 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0281 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014550 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0057 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014602 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0034 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014553 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0046 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014651 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0094 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014700 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0221 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014565 | PGS002702 (disease_HYPOTHYROIDISM_SELF_REP.SBayesR) |
PSS009787| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0043 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014614 | PGS002702 (disease_HYPOTHYROIDISM_SELF_REP.SBayesR) |
PSS009788| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0117 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014663 | PGS002702 (disease_HYPOTHYROIDISM_SELF_REP.SBayesR) |
PSS009789| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0206 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014712 | PGS002702 (disease_HYPOTHYROIDISM_SELF_REP.SBayesR) |
PSS009790| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (full model vs. covariates alone): 0.0139 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014580 | PGS002717 (disease_THYROID_ANY_SELF_REP.SBayesR) |
PSS009847| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0031 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014629 | PGS002717 (disease_THYROID_ANY_SELF_REP.SBayesR) |
PSS009848| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.003 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014678 | PGS002717 (disease_THYROID_ANY_SELF_REP.SBayesR) |
PSS009849| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0192 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014727 | PGS002717 (disease_THYROID_ANY_SELF_REP.SBayesR) |
PSS009850| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Thyroid | — | — | Incremental R2 (full model vs. covariates alone): 0.0155 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014583 | PGS002720 (disease_T2D.SBayesR) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014632 | PGS002720 (disease_T2D.SBayesR) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0021 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014681 | PGS002720 (disease_T2D.SBayesR) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0129 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014730 | PGS002720 (disease_T2D.SBayesR) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0207 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014821 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes | OR: 1.09 [1.01, 1.18] | — | — | — | — |
| PPM014822 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes in rare variant carriers | OR: 1.45 [1.15, 1.57] | — | — | — | — |
| PPM014823 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes in rare variant non-carriers | OR: 1.06 [1.01, 1.13] | — | — | — | — |
| PPM014844 | PGS002740 (PRS22_PC) |
PSS009913| European Ancestry| 13,952 individuals |
PGP000347 | Yuan C et al. Ann Oncol (2022) |
Reported Trait: Pancreatic cancer in those aged <= 60 years | — | — | Odds ratio (OR, top vs bottom 10%): 6.91 [4.6, 10.4] | — | — |
| PPM014843 | PGS002740 (PRS22_PC) |
PSS009913| European Ancestry| 13,952 individuals |
PGP000347 | Yuan C et al. Ann Oncol (2022) |
Reported Trait: Pancreatic cancer in those aged >70 years | — | — | Odds ratio (OR, top vs bottom 10%): 4.12 [3.08, 5.52] | — | — |
| PPM014966 | PGS002766 (Hypothyroidism_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Hypothyroidism | OR: 1.47 [1.43, 1.52] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014971 | PGS002771 (Type_2_diabetes_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | OR: 1.88 [1.82, 1.95] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014979 | PGS002779 (GTG_T2D_maxCT) |
PSS009943| European Ancestry| 5,472 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.35 [1.25, 1.45] | AUROC: 0.585 [0.564, 0.605] | — | — | — |
| PPM014980 | PGS002780 (GTG_T2D_SCT) |
PSS009943| European Ancestry| 5,472 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.41 [1.31, 1.51] | AUROC: 0.595 [0.575, 0.615] | — | — | — |
| PPM015993 | PGS003089 (ExPRSweb_T2D_2443_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.524 [1.468, 1.583] β: 0.422 (0.0191) |
AUROC: 0.616 [0.6, 0.63] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015996 | PGS003090 (ExPRSweb_T2D_2443_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.425 [1.373, 1.479] β: 0.354 (0.0191) |
AUROC: 0.599 [0.582, 0.615] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015994 | PGS003091 (ExPRSweb_T2D_2443_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.379 [1.329, 1.431] β: 0.321 (0.0189) |
AUROC: 0.591 [0.574, 0.606] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015992 | PGS003092 (ExPRSweb_T2D_2443_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.275 [1.23, 1.321] β: 0.243 (0.0184) |
AUROC: 0.563 [0.546, 0.58] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015995 | PGS003093 (ExPRSweb_T2D_2443_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.6 [1.539, 1.664] β: 0.47 (0.0199) |
AUROC: 0.625 [0.608, 0.639] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015999 | PGS003094 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.333 [1.286, 1.382] β: 0.287 (0.0184) |
AUROC: 0.589 [0.572, 0.604] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016005 | PGS003095 (ExPRSweb_T2D_29358691-GCST005413_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.239 [1.196, 1.284] β: 0.214 (0.0181) |
AUROC: 0.562 [0.546, 0.578] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016001 | PGS003096 (ExPRSweb_T2D_29358691-GCST005413_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.232 [1.189, 1.277] β: 0.209 (0.0181) |
AUROC: 0.56 [0.545, 0.576] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015997 | PGS003097 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.011 [0.976, 1.047] β: 0.011 (0.0181) |
AUROC: 0.5 [0.484, 0.517] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016003 | PGS003098 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.358 [1.31, 1.408] β: 0.306 (0.0183) |
AUROC: 0.593 [0.577, 0.608] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016009 | PGS003099 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.657 [1.595, 1.722] β: 0.505 (0.0196) |
AUROC: 0.626 [0.609, 0.641] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016015 | PGS003100 (ExPRSweb_T2D_30054458-GCST006867_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.531 [1.474, 1.591] β: 0.426 (0.0193) |
AUROC: 0.6 [0.585, 0.616] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016011 | PGS003101 (ExPRSweb_T2D_30054458-GCST006867_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.531 [1.474, 1.591] β: 0.426 (0.0193) |
AUROC: 0.6 [0.585, 0.616] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016007 | PGS003102 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.639 [1.577, 1.703] β: 0.494 (0.0196) |
AUROC: 0.628 [0.611, 0.643] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016013 | PGS003103 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.704 [1.639, 1.772] β: 0.533 (0.0198) |
AUROC: 0.637 [0.621, 0.653] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016019 | PGS003104 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.536 [1.479, 1.596] β: 0.429 (0.0195) |
AUROC: 0.611 [0.595, 0.626] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016025 | PGS003105 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.33 [1.283, 1.379] β: 0.285 (0.0184) |
AUROC: 0.572 [0.555, 0.588] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016021 | PGS003106 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.33 [1.283, 1.379] β: 0.285 (0.0184) |
AUROC: 0.572 [0.555, 0.588] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016017 | PGS003107 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.028 [0.992, 1.065] β: 0.0276 (0.0182) |
AUROC: 0.541 [0.523, 0.557] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016023 | PGS003108 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.563 [1.504, 1.624] β: 0.446 (0.0195) |
AUROC: 0.61 [0.594, 0.625] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016000 | PGS003109 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.522 [1.491, 1.554] β: 0.42 (0.0106) |
AUROC: 0.616 [0.61, 0.622] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016006 | PGS003110 (ExPRSweb_T2D_29358691-GCST005413_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.406 [1.378, 1.435] β: 0.341 (0.0103) |
AUROC: 0.594 [0.588, 0.6] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016002 | PGS003111 (ExPRSweb_T2D_29358691-GCST005413_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.392 [1.364, 1.42] β: 0.331 (0.0103) |
AUROC: 0.59 [0.584, 0.596] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015998 | PGS003112 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.01 [0.989, 1.031] β: 0.00976 (0.0104) |
AUROC: 0.501 [0.495, 0.507] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016004 | PGS003113 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.522 [1.491, 1.554] β: 0.42 (0.0106) |
AUROC: 0.616 [0.611, 0.622] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016010 | PGS003114 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.959 [3.866, 4.055] β: 1.38 (0.0121) |
AUROC: 0.825 [0.82, 0.829] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016016 | PGS003115 (ExPRSweb_T2D_30054458-GCST006867_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.755 [3.669, 3.844] β: 1.32 (0.0119) |
AUROC: 0.816 [0.811, 0.82] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016012 | PGS003116 (ExPRSweb_T2D_30054458-GCST006867_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.755 [3.669, 3.844] β: 1.32 (0.0119) |
AUROC: 0.816 [0.811, 0.82] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016008 | PGS003117 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.061 [2.992, 3.132] β: 1.12 (0.0116) |
AUROC: 0.778 [0.774, 0.783] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016014 | PGS003118 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.193 [3.12, 3.268] β: 1.16 (0.0118) |
AUROC: 0.786 [0.782, 0.791] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016020 | PGS003119 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.662 [1.628, 1.698] β: 0.508 (0.0107) |
AUROC: 0.639 [0.634, 0.645] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016026 | PGS003120 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.451 [1.421, 1.48] β: 0.372 (0.0104) |
AUROC: 0.603 [0.597, 0.609] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016022 | PGS003121 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.451 [1.421, 1.48] β: 0.372 (0.0104) |
AUROC: 0.603 [0.597, 0.609] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016018 | PGS003122 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.009 [0.988, 1.03] β: 0.00858 (0.0105) |
AUROC: 0.547 [0.541, 0.552] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016024 | PGS003123 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.715 [1.679, 1.752] β: 0.539 (0.0107) |
AUROC: 0.648 [0.642, 0.654] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016201 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Fasting plasma glucose | OR: 1.83 [1.59, 2.11] | — | — | — | — |
| PPM016202 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Hemoglobin A1c level | OR: 1.68 [1.46, 1.93] | — | — | — | — |
| PPM016203 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Type 2 diabetes | OR: 2.99 [2.61, 3.44] | — | — | — | — |
| PPM016204 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Fasting plasma glucose and Type 2 diabetes | OR: 3.52 [2.69, 4.61] | — | — | — | — |
| PPM016260 | PGS003385 (best_OV) |
PSS010083| European Ancestry| 143,259 individuals |
PGP000413 | Namba S et al. Cancer Res (2022) |
Reported Trait: ovarian serous carcinoma | — | AUROC: 0.717 | R²: 0.0142 | age, top 20 genetic principal components | — |
| PPM016274 | PGS003394 (PRS_Stepwise) |
PSS010091| European Ancestry| 198,758 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.39 [1.29, 1.5] | AUROC: 0.595 | — | — | — |
| PPM016275 | PGS003394 (PRS_Stepwise) |
PSS010090| East Asian Ancestry| 7,669 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.17 [1.11, 1.23] | AUROC: 0.542 | — | — | — |
| PPM017029 | PGS003394 (PRS_Stepwise) |
PSS010098| European Ancestry| 189,171 individuals |
PGP000417 | Dite GS et al. Eur J Cancer Prev (2022) |Ext. |
Reported Trait: 10-year ovarian cancer risks | — | C-index: 0.623 [0.603, 0.642] | — | — | — |
| PPM016276 | PGS003394 (PRS_Stepwise) |
PSS010089| African Ancestry| 1,072 individuals |
PGP000277 | Dareng EO et al. Eur J Hum Genet (2022) |
Reported Trait: Epithelial non-mucinous ovarian cancer | OR: 1.37 [1.2, 1.56] | AUROC: 0.594 | — | — | — |
| PPM017036 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x BMI interaction | β: 89.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017037 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x Born in South Asia interaction | β: 84.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017038 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x Low diet quality interaction (only in START cohort) | β: 0.141 [0.053, 0.228] | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017039 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: AUC glucose x BMI interaction | β: 77.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017040 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: GDM (IADPSG criteria) x BMI interaction | OR: 0.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017032 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose | β: 0.085 [0.067, 0.103] | — | — | first five principal components (PCs) | — |
| PPM017033 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: 2h postload glucose | β: 0.207 [0.157, 0.257] | — | — | first five principal components (PCs) | — |
| PPM017034 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: AUC glucose | β: 0.155 [0.125, 0.184] | — | — | first five principal components (PCs) | — |
| PPM017035 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: GDM (IADPSG criteria) | OR: 1.45 [1.32, 1.6] | — | — | first five principal components (PCs) | — |
| PPM017148 | PGS003437 (PRS23_TC) |
PSS010136| European Ancestry| 264,956 individuals |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |
Reported Trait: Incident thyroid cancer x total moderate to vigorous physical activity interaction | HR: 0.74 [0.57, 0.97] | — | — | age, sex, and genetic composition, townsend deprivation index at recruitment, qualifications and average total household income before tax | — |
| PPM017149 | PGS003437 (PRS23_TC) |
PSS010136| European Ancestry| 264,956 individuals |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |
Reported Trait: Incident thyroid cancer x smoke intake interaction | HR: 0.48 [0.32, 0.72] | — | — | age, sex, and genetic composition, townsend deprivation index at recruitment, qualifications and average total household income before tax | — |
| PPM017145 | PGS003437 (PRS23_TC) |
PSS010136| European Ancestry| 264,956 individuals |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |
Reported Trait: Thyroid cancer | HR: 1.95 [1.68, 2.26] | AUROC: 0.64 [0.61, 66.0] | — | age, sex, and genetic composition, townsend deprivation index at recruitment, qualifications and average total household income before tax | — |
| PPM017147 | PGS003437 (PRS23_TC) |
PSS010136| European Ancestry| 264,956 individuals |
PGP000439 | Feng X et al. JAMA Netw Open (2022) |
Reported Trait: Incident thyroid cancer x healthy lifestyle interaction | HR: 0.52 [0.37, 0.73] | — | — | age, sex, and genetic composition, townsend deprivation index at recruitment, qualifications and average total household income before tax | — |
| PPM017182 | PGS003443 (PRScsx_T2D_LAT_EURweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EASweights, PRScsx_T2D_LAT_LATweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM017183 | PGS003444 (PRScsx_T2D_LAT_EASweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_LATweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM017184 | PGS003445 (PRScsx_T2D_LAT_LATweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_EASweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM018476 | PGS003728 (PS_T2D_183-AGEN) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.28 [1.12, 1.46] | — | Net reclassification improvement: 0.331 [0.141, 0.521] ∆AUC: 0.005 [-0.003, 0.012] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018484 | PGS003728 (PS_T2D_183-AGEN) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.27 [1.15, 1.39] | — | Net reclassification improvement: 0.164 [0.025, 0.303] ∆AUC: 0.037 [0.013, 0.06] |
sex, parental diabetes, and birth weight | — |
| PPM018468 | PGS003728 (PS_T2D_183-AGEN) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.14 [1.06, 1.24] | — | Net reclassification improvement: 0.115 [-0.014, 0.244] ∆AUC: 0.001 [-0.003, 0.005] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018469 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.27 [1.17, 1.38] | AUROC: 0.735 | Net reclassification improvement: 0.27 [0.149, 0.392] ∆AUC: 0.007 [0.001, 0.014] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018477 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.49 [1.29, 1.72] | AUROC: 0.812 | Net reclassification improvement: 0.268 [0.072, 0.464] ∆AUC: 0.007 [-0.003, 0.017] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018485 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.48 [1.35, 1.63] | AUROC: 0.685 | Net reclassification improvement: 0.362 [0.222, 0.502] ∆AUC: 0.072 [0.045, 0.099] |
sex, parental diabetes, and birth weight | — |
| PPM018471 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.2 [1.1, 1.3] | — | Net reclassification improvement: 0.216 [0.094, 0.338] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018479 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.34 [1.17, 1.54] | — | Net reclassification improvement: 0.314 [0.116, 0.512] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018487 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.45 [1.32, 1.6] | — | Net reclassification improvement: 0.259 [0.115, 0.403] ∆AUC: 0.073 |
sex, parental diabetes, and birth weight | — |
| PPM018475 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.19 [1.09, 1.29] | — | Net reclassification improvement: 0.181 [0.054, 0.308] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018483 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.35 [1.18, 1.56] | — | Net reclassification improvement: 0.302 [0.089, 0.515] ∆AUC: 0.002 [-0.007, 0.012] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018491 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.32 [1.2, 1.45] | — | Net reclassification improvement: 0.201 [0.057, 0.306] ∆AUC: 0.054 [0.031, 0.077] |
sex, parental diabetes, and birth weight | — |
| PPM018474 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.18 [1.09, 1.29] | — | Net reclassification improvement: 0.219 [0.097, 0.34] ∆AUC: 0.004 [-0.001, 0.008] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018482 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.32 [1.15, 1.51] | — | Net reclassification improvement: 0.15 [-0.054, 0.354] ∆AUC: 0.006 [-0.001, 0.014] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018490 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.4 [1.28, 1.55] | — | Net reclassification improvement: 0.277 [0.125, 0.428] ∆AUC: 0.072 [0.046, 0.099] |
sex, parental diabetes, and birth weight | — |
| PPM018473 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.21 [1.12, 1.32] | — | Net reclassification improvement: 0.277 [0.156, 0.397] ∆AUC: 0.005 [0.0, 0.011] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018481 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.37 [1.19, 1.58] | — | Net reclassification improvement: 0.296 [0.09, 0.502] ∆AUC: 0.008 [-0.001, 0.017] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018489 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.47 [1.33, 1.62] | — | Net reclassification improvement: 0.328 [0.183, 0.474] ∆AUC: 0.075 [0.048, 0.102] |
sex, parental diabetes, and birth weight | — |
| PPM018472 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.13 [1.04, 1.23] | — | Net reclassification improvement: 0.115 [-0.014, 0.244] ∆AUC: 0.001 [-0.002, 0.005] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018480 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.19 [1.04, 1.36] | — | Net reclassification improvement: 0.182 [-0.019, 0.383] ∆AUC: 0.001 [-0.004, 0.007] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018488 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.33 [1.22, 1.46] | — | Net reclassification improvement: 0.176 [0.029, 0.323] ∆AUC: 0.052 [0.026, 0.077] |
sex, parental diabetes, and birth weight | — |
| PPM018470 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.13 [1.04, 1.22] | — | ∆AUC: 0.003 [0.0, 0.007] Net reclassification improvement: 0.181 [0.047, 0.316] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018478 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.21 [1.06, 1.38] | — | Net reclassification improvement: 0.185 [-0.017, 0.388] ∆AUC: 0.005 [-0.001, 0.01] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018486 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.28 [1.16, 1.41] | — | Net reclassification improvement: 0.231 [0.091, 0.376] ∆AUC: 0.042 [0.019, 0.065] |
sex, parental diabetes, and birth weight | — |
| PPM018497 | PGS003741 (PRS28_OC) |
PSS010991| European Ancestry| 501 individuals |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Reported Trait: Ovarian cancer | OR: 1.15 [1.04, 1.28] | — | — | — | — |
| PPM018498 | PGS003742 (PRS19_PC) |
PSS010993| European Ancestry| 153 individuals |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Reported Trait: Pancreatic cancer | OR: 1.33 [1.13, 1.57] | — | — | — | — |
| PPM018502 | PGS003746 (PRS11_TC) |
PSS010996| European Ancestry| 360 individuals |
PGP000470 | Xin J et al. EBioMedicine (2023) |
Reported Trait: Thyroid cancer | OR: 1.63 [1.44, 1.85] | — | — | — | — |
| PPM018508 | PGS003749 (ModelT1D_under25) |
PSS011001| European Ancestry| 119,273 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 1 diabetes with age of diagnosis under 25 | — | AUROC: 0.797 | Nagelkerke R2: 0.099 | — | — |
| PPM018512 | PGS003749 (ModelT1D_under25) |
PSS011000| European Ancestry| 7,067 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.792 | — | — | — |
| PPM018514 | PGS003749 (ModelT1D_under25) |
PSS010998| European Ancestry| 2,494 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.686 | — | — | — |
| PPM018509 | PGS003750 (ModelT1D) |
PSS010999| European Ancestry| 120,028 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.64 | Nagelkerke R2: 0.014 | — | — |
| PPM018510 | PGS003751 (ModelT2D_over45) |
PSS011003| European Ancestry| 122,144 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 2 diabetes with age of diagnosis over 45 | — | AUROC: 0.596 | Nagelkerke R2: 0.016 | — | — |
| PPM018513 | PGS003751 (ModelT2D_over45) |
PSS011000| European Ancestry| 7,067 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.527 | — | — | — |
| PPM018511 | PGS003752 (ModelT2D) |
PSS011002| European Ancestry| 125,189 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.578 | Nagelkerke R2: 0.014 | — | — |
| PPM018518 | PGS003754 (PRS22_OCstepwise) |
PSS011005| Multi-ancestry (including European)| 11,135 individuals |
PGP000474 | Hurwitz LM et al. JAMA Netw Open (2023) |
Reported Trait: Nonmucinous Epithelial Ovarian Cancer x aspirin use interaction | — | — | Odds ratio (OR, <median): 0.85 [0.7, 1.02] Odds ratio (OR, >=median): 0.86 [0.74, 1.01] |
— | — |
| PPM018759 | PGS003867 (T2D_PRScs_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Type 2 diabetes | OR: 1.83 [1.74, 1.92] | AUROC: 0.7384 [0.7194, 0.7574] | — | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM019312 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50796 β: 0.41076 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019313 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.26658 β: 0.23632 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019314 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53274 β: 0.42705 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019315 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.40966 β: 0.34335 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019316 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.6067 β: 0.47419 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019311 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48531 β: 0.39562 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019950 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.95715 β: 0.67149 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019951 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.37817 β: 0.86633 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019952 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02806 β: 0.02768 |
AUROC: 0.49 | — | 0 | beta = log(or)/sd_pgs |
| PPM019953 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.35954 β: 0.30715 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019954 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.40714 β: 0.87844 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019353 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.42404 β: 0.3535 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019354 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.43926 β: 0.36413 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019355 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2647 β: 0.23483 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019356 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.47667 β: 0.38979 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019357 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.36032 β: 0.30772 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019358 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53698 β: 0.42982 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019995 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.95016 β: 0.66791 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019996 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.41964 β: 0.88362 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019997 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02716 β: 0.0268 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019998 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.41112 β: 0.34438 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019999 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32891 β: 0.8454 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019359 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48322 β: 0.39422 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019360 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.47356 β: 0.38768 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019361 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25868 β: 0.23007 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019362 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49153 β: 0.3998 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019364 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.57088 β: 0.45164 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019363 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.34108 β: 0.29348 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019990 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96291 β: 0.67443 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019991 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.44728 β: 0.89498 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019992 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02458 β: 0.02428 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019993 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42499 β: 0.35417 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019994 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.34601 β: 0.85271 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019329 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48498 β: 0.3954 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019330 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50219 β: 0.40693 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019331 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2876 β: 0.25278 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019332 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53513 β: 0.42861 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019333 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.39993 β: 0.33642 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019334 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.608 β: 0.47499 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019965 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32281 β: 0.84278 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019966 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.04799 β: 0.71686 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019967 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.00124 β: 0.00124 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019968 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.41811 β: 0.34932 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019969 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.67223 β: 0.98291 |
AUROC: 0.75 | — | 0 | beta = log(or)/sd_pgs |
| PPM019293 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51531 β: 0.41562 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019294 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.52599 β: 0.42265 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019295 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.29096 β: 0.25538 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019296 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.55991 β: 0.44463 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019297 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.41025 β: 0.34376 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019298 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.6442 β: 0.49725 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019335 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51227 β: 0.41361 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019337 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2863 β: 0.25177 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019338 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.5456 β: 0.43541 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019339 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.4232 β: 0.35291 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019340 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.64766 β: 0.49936 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019336 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53613 β: 0.42927 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019970 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96796 β: 0.677 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019971 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.98877 β: 0.68752 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019972 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.99583 β: -0.00418 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019973 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.34209 β: 0.29422 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019974 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32027 β: 0.84168 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019341 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51406 β: 0.41479 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019342 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.54026 β: 0.43195 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019343 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28668 β: 0.25206 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019344 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.55065 β: 0.43868 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019345 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.42683 β: 0.35546 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019346 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.65089 β: 0.50131 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019975 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.10311 β: 0.74342 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019976 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.14067 β: 0.76112 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019977 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.00042 β: 0.00042 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019979 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.67623 β: 0.98441 |
AUROC: 0.76 | — | 0 | beta = log(or)/sd_pgs |
| PPM019978 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.39887 β: 0.33567 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019347 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49969 β: 0.40526 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019348 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49743 β: 0.40375 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019349 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.26384 β: 0.23416 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019350 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.52107 β: 0.41942 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019351 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.37392 β: 0.31767 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019352 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.61184 β: 0.47737 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019985 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96153 β: 0.67372 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019986 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.44508 β: 0.89408 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019987 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.0158 β: 0.01568 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019988 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42395 β: 0.35343 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019989 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.39116 β: 0.87178 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019980 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.98839 β: 0.68733 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019981 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.45742 β: 0.89911 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019982 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.99231 β: -0.00772 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019983 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42533 β: 0.3544 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019984 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.43145 β: 0.88849 |
AUROC: 0.75 | — | 0 | beta = log(or)/sd_pgs |
| PPM019299 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25413 β: 0.22644 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019300 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2706 β: 0.23949 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019301 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.1856 β: 0.17025 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019302 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.30688 β: 0.26765 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019303 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25033 β: 0.22341 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019304 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.32877 β: 0.28426 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019940 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.50723 β: 0.41027 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019941 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.76472 β: 0.56799 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019942 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.06976 β: 0.06744 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019943 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.21972 β: 0.19862 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019944 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.8907 β: 0.63695 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019305 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.32208 β: 0.2792 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019306 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.34756 β: 0.29829 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019307 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.21072 β: 0.19122 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019308 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.36428 β: 0.31063 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019309 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28905 β: 0.2539 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019310 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.41752 β: 0.34891 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019945 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.53997 β: 0.43176 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019946 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.83108 β: 0.6049 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019947 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.10378 β: 0.09874 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019948 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.23285 β: 0.20933 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019949 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.87052 β: 0.62622 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019317 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48356 β: 0.39444 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019319 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28557 β: 0.2512 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019320 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.54343 β: 0.43401 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019321 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.4041 β: 0.3394 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019322 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.60963 β: 0.476 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019318 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50666 β: 0.40989 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019956 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.08691 β: 0.73568 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019957 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.97765 β: -0.0226 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019958 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.32037 β: 0.27791 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019959 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.73561 β: 0.55136 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019955 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.62883 β: 0.48786 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019323 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53171 β: 0.42638 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019324 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.5534 β: 0.44045 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019325 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.29976 β: 0.26218 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019326 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.57552 β: 0.45459 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019327 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.44083 β: 0.36522 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019328 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.66922 β: 0.51236 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019960 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.35332 β: 0.85583 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019961 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.27887 β: 0.82368 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019962 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.0051 β: 0.00509 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019963 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.43168 β: 0.35885 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019964 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.88687 β: 1.06017 |
AUROC: 0.77 | — | 0 | beta = log(or)/sd_pgs |
| PPM020104 | PGS004171 (t1d_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7 | — | year of birth, sex | — |
| PPM020105 | PGS004172 (t1d_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020106 | PGS004173 (t1d_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020107 | PGS004174 (t1d_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020108 | PGS004175 (t1d_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7 | — | year of birth, sex | — |
| PPM020114 | PGS004181 (t2d_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69418 | — | year of birth, sex | — |
| PPM020115 | PGS004182 (t2d_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69491 | — | year of birth, sex | — |
| PPM020116 | PGS004183 (t2d_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69959 | — | year of birth, sex | — |
| PPM020117 | PGS004184 (t2d_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69539 | — | year of birth, sex | — |
| PPM020118 | PGS004185 (t2d_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69924 | — | year of birth, sex | — |
| PPM020158 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes | HR: 1.5 [1.48, 1.52] | — | — | age, gender, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, total physical activity, dietary pattern, vitamin D supplement, use of sun/UV protection, PM2.5, hypertension, cardiovascular disease, antihypertensive medications use, cholesterol-lowering medications use, and average outdoor light time | — |
| PPM020159 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time in summer | — | — | Hazard ratio (HR, outdoor light time in summer >3h/day and PRS in top tertile vs. outdoor light time in summer <2-3 h/day and PRS in bottom tertile): 2.53 [2.39, 2.69] | Hb1Ac concentrations at baseline | — |
| PPM020160 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time in winter | — | — | Hazard ratio (HR, outdoor light time in winter >2 h/day and PRS in top tertile vs. outdoor light time in winter <1-2 h/day and PRS in bottom tertile): 2.56 [2.42, 2.71] | Hb1Ac concentrations at baseline | — |
| PPM020161 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time on average | — | — | Hazard ratio (HR, outdoor light time on average >2.5 h/day and PRS in top tertile vs. outdoor light time on average 1.5-2.5 h/day and PRS in bottom tertile): 2.52 [2.37, 2.67] | Hb1Ac concentrations at baseline | — |
| PPM020217 | PGS004225 (PRS46_T2DEastAsia) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes with lifestyle group | — | — | Hazard ratio (HR, poor lifestyle and high PRS vs. ideal lifestyle and low PRS): 3.93 [2.07, 7.44] | — | — |
| PPM020215 | PGS004225 (PRS46_T2DEastAsia) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes | — | — | Hazard ratio (HR, high vs low quintile): 2.06 [1.42, 2.97] | age, gender, SBP, DBP, FBG, TC, TG, HDLC, and diabetes family history | — |
| PPM020216 | PGS004226 (PRS50_T2DEur) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes | — | — | Hazard ratio (HR, high vs low quintile): 1.69 [1.17, 2.44] | age, gender, SBP, DBP, FBG, TC, TG, HDLC, and diabetes family history | — |
| PPM020281 | PGS004239 (PRS14AAD) |
PSS011323| Ancestry Not Reported| 1,500 individuals |
PGP000538 | Aranda-Guillén M et al. J Intern Med (2023) |
Reported Trait: Autoimmune Addison's disease | OR: 6.4 [5.2, 8.0] | AUROC: 0.88 | — | — | — |
| PPM020282 | PGS004239 (PRS14AAD) |
PSS011323| Ancestry Not Reported| 1,500 individuals |
PGP000538 | Aranda-Guillén M et al. J Intern Med (2023) |
Reported Trait: Age of onset of autoimmune Addison's disease | β: -3.8 [-4.7, -2.8] | — | — | — | — |
| PPM020306 | PGS004249 (PRS25_ovary) |
PSS011328| European Ancestry| 133,830 individuals |
PGP000542 | Kim ES et al. NPJ Precis Oncol (2023) |
Reported Trait: Ovarian cancer | HR: 1.16 [1.03, 1.31] | — | — | first 10 genetic principal components | — |
| PPM020307 | PGS004250 (PRS19_pancreas) |
PSS011328| European Ancestry| 133,830 individuals |
PGP000542 | Kim ES et al. NPJ Precis Oncol (2023) |
Reported Trait: Pancreatic cancer | HR: 1.37 [1.16, 1.61] | — | — | first 10 genetic principal components | — |
| PPM020314 | PGS004250 (PRS19_pancreas) |
PSS011329| European Ancestry| 115,207 individuals |
PGP000542 | Kim ES et al. NPJ Precis Oncol (2023) |
Reported Trait: Pancreatic cancer | HR: 1.39 [1.2, 1.61] | — | — | first 10 genetic principal components | — |
| PPM020433 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Fasting plasma glucose | β: 0.292 [0.181, 0.404] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020434 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: HOMA-beta | β: -0.143 [-0.212, -0.073] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020435 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Impaired fasting glucose | β: 1.809 [1.362, 2.402] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020436 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Type 2 diabetes | β: 2.263 [1.72, 2.977] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020561 | PGS004446 (disease.E03.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E03 (Other hypothyroidism) | OR: 1.47851 | — | — | — | — |
| PPM020614 | PGS004499 (disease.T2D.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Type 2 diabetes (T2D) | OR: 1.51252 | — | — | — | — |
| PPM020631 | PGS004516 (meta.E03.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E03 (Other hypothyroidism) | OR: 1.49623 | — | — | — | — |
| PPM020684 | PGS004569 (meta.T2D.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Type 2 diabetes (T2D) | OR: 1.63182 | — | — | — | — |
| PPM020759 | PGS004602 (PRS424_T2D) |
PSS011395| European Ancestry| 357,419 individuals |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Reported Trait: Type 2 diabetes | HR: 1.54 [1.5, 1.58] β: 0.431 (0.014) |
— | — | Age, sex, center, BMI, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, history of hypertension, history of high cholesterol, vitamin supplement use, mineral supplement use, aspirin use, and lipid-lowering medication | — |
| PPM020760 | PGS004602 (PRS424_T2D) |
PSS011395| European Ancestry| 357,419 individuals |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Reported Trait: HbA1c | β: 0.544 (0.007) | — | — | Age, sex, center, BMI, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, history of hypertension, history of high cholesterol, vitamin supplement use, mineral supplement use, aspirin use, and lipid-lowering medication | — |
| PPM020779 | PGS004602 (PRS424_T2D) |
PSS011407| Multi-ancestry (including European)| 59,325 individuals |
PGP000587 | Luo M et al. Br J Sports Med (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | — | — | Hazard ratio (HR, high vs low PRS tertile): 2.43 [2.04, 2.9] | Age as the underlying timescale, gender, genotyping array, the first 10 principal components of ancestry, ethnicity, educational attainment, household income, Townsend deprivation index, employment status, assessment center, moking status, alcohol consumption, healthy diet score, hypertension, dyslipidemia, depression, total wear time, seasonality, and total volume of physical activity | — |
| PPM020877 | PGS004692 (ovarian_cancer) |
PSS011436| European Ancestry| 22,025 individuals |
PGP000596 | Hu J et al. JNCI Cancer Spectr (2024) |
Reported Trait: Ovarian cancer | — | AUROC: 0.5298 | — | — | — |
| PPM020878 | PGS004693 (pancreatic_cancer) |
PSS011437| European Ancestry| 40,877 individuals |
PGP000596 | Hu J et al. JNCI Cancer Spectr (2024) |
Reported Trait: Pancreatic cancer | — | AUROC: 0.5426 | — | — | — |
| PPM021014 | PGS004789 (hypothyroid_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (Full model versus model with only covariates): 0.041 [0.033, 0.049] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021015 | PGS004790 (hypothyroid_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypothyroidism | — | — | Incremental R2 (Full model versus model with only covariates): 0.042 [0.034, 0.05] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021062 | PGS004837 (t2d_PRSmix_eur) |
PSS011507| European Ancestry| 7,879 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.099 [0.087, 0.112] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021063 | PGS004838 (t2d_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.061 [0.051, 0.07] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021064 | PGS004839 (t2d_PRSmixPlus_eur) |
PSS011507| European Ancestry| 7,879 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.129 [0.115, 0.143] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021065 | PGS004840 (t2d_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.065 [0.055, 0.075] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021085 | PGS004859 (T2D_PRS_CS) |
PSS011514| African Ancestry| 7,010 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.43 [1.35, 1.52] | AUROC: 0.76 [0.74, 0.77] | — | age, sex, 10 principal components | — |
| PPM021086 | PGS004859 (T2D_PRS_CS) |
PSS011516| Hispanic or Latin American Ancestry| 5,382 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.09 [1.92, 2.27] | AUROC: 0.84 [0.82, 0.86] | — | age, sex, 10 principal components | — |
| PPM021087 | PGS004859 (T2D_PRS_CS) |
PSS011517| East Asian Ancestry| 663 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.8 [1.4, 2.32] | AUROC: 0.84 [0.79, 0.9] | — | age, sex, 10 principal components | — |
| PPM021088 | PGS004859 (T2D_PRS_CS) |
PSS011518| European Ancestry| 22,306 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.33 [2.23, 2.43] | AUROC: 0.77 [0.76, 0.78] | — | age, sex, 10 principal components | — |
| PPM021089 | PGS004859 (T2D_PRS_CS) |
PSS011519| South Asian Ancestry| 323 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.28 [1.64, 3.16] | AUROC: 0.88 [0.81, 0.95] | — | age, sex, 10 principal components | — |
| PPM021090 | PGS004859 (T2D_PRS_CS) |
PSS011515| Multi-ancestry (including European)| 35,684 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.93 [1.87, 1.99] | AUROC: 0.75 [0.74, 0.75] | — | age, sex, 10 principal components | — |
| PPM021084 | PGS004859 (T2D_PRS_CS) |
PSS011513| Multi-ancestry (including European)| 546 individuals |
PGP000605 | Deutsch AJ et al. Diabetes Care (2023) |
Reported Trait: Glucocorticoid-induced hyperglycemia | OR: 1.44 [1.02, 2.04] | AUROC: 0.68 | — | eGFR, glucocorticoid dose | — |
| PPM021133 | PGS004868 (T2DPGS) |
PSS011537| European Ancestry| 345,217 individuals |
PGP000617 | Yun JS et al. Cardiovasc Diabetol (2022) |
Reported Trait: Incident cardiovascular disease | HR: 1.06 [1.04, 1.07] | — | Hazard ratio (HR, top PRS percentile vs bottom quintile): 1.35 [1.19, 1.53] | Age, sex, genotyping array, 10 PCs | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS011436 | — | — | [ ,
0.0 % Male samples |
— | European | — | UKB | — |
| PSS011437 | — | — | [
|
— | European | — | UKB | — |
| PSS011441 | — | — | [ ,
82.0 % Male samples |
Mean = 27.5 years | African unspecified | — | PDAY | — |
| PSS011442 | — | — | [ ,
77.0 % Male samples |
Mean = 26.7 years | European | — | PDAY | — |
| PSS000017 | Type 2 diabetes ascertainment was based on self-report in an interview with a trained nurse or an ICD-10 code of E11.X in hospitalization records. | — | [
|
— | European | — | UKB | UKB Phase 2 |
| PSS000025 | Incident cases of Type 2 Diabetes in 5.63 years follow-up | — | [ ,
55.0 % Male samples |
— | European (Estonian) |
— | EB | — |
| PSS000026 | Cases were defined on the presence or absence of severe insulin deficiency (requiring insulin treatment at 3 years after diagnosis). We cate- gorized people as severely insulin defi- cient if they received continuous insulin treatment at ,3 years from the time of diagnosis and had a low measured C-peptide level (nonfasting measured ,0.6 nmol/L or equivalent fasting blood glucose level or posthome meal urine C-peptide–to–creatinine ratio) | — | [ ,
46.3 % Male samples |
— | European | — | P2ID | A cross-sectional cohort of people in whom diabetes was diagnosed between the ages of 20 and 40 years (n = 223), who had had diabetes for .3 years, and who had self-reported as white European from Devon and Cornwall in South West England. Known monogenic diabetes and secondary diabetes pa- tients were excluded. |
| PSS000027 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
33.78 % Male samples |
— | African American or Afro-Caribbean | — | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000028 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
44.84 % Male samples |
— | Hispanic or Latin American | Samples labeled Caucasian (Hispanic ethnicity) in the original publication. | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000029 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
47.34 % Male samples |
— | European | Samples labeled Caucasian (non-Hispanic) in the original publication. | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000030 | — | — | [
|
— | African unspecified | — | 7 cohorts
|
— |
| PSS000031 | Cases are diagnosed with type 1 diabetes. | — | [
|
— | African unspecified | — | UOF | — |
| PSS000032 | Type 1 Diabetes Case Definition = Clinical diagnosis of diabetes at less than or equal to 20 years of age; On insulin within 1 year from the time of diagnosis; Still on insulin at the time of recruit- ment; Not using oral antihyperglycemic agents; Did not ever self-report as having type 2 diabetes (T2D) | — | [
|
— | European | — | UKB | — |
| PSS009279 | — | — | 19,923 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009284 | — | — | 19,043 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009285 | — | — | 19,108 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009286 | — | — | 19,852 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009287 | — | — | 18,975 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009288 | — | — | 19,931 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000042 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
38.8 % Male samples |
— | African American or Afro-Caribbean | — | CARDIA | — |
| PSS000043 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
46.5 % Male samples |
— | European | — | CARDIA | — |
| PSS000044 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
46.6 % Male samples |
— | European | — | FOS | — |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS011474 | — | — | 8,837 individuals | — | South Asian | — | G&H | — |
| PSS000054 | Prevalent T2D status was defined using self-reported medical history and medication | — | [
|
— | European | — | UKB | — |
| PSS009335 | — | — | 19,586 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011507 | — | — | 7,879 individuals | — | European | — | AllofUs | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | Asian unspecified | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | European | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | Not reported | — | MGBB | — |
| PSS011514 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | East Asian | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | South Asian | — | AllofUs | — |
| PSS011516 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011517 | — | — | [
|
— | East Asian | — | AllofUs | — |
| PSS011518 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011519 | — | — | [
|
— | South Asian | — | AllofUs | — |
| PSS011527 | — | — | 245 individuals | — | European | — | TCGA | — |
| PSS011527 | — | — | 30 individuals | — | Asian unspecified | — | TCGA | — |
| PSS011527 | — | — | 13 individuals | — | African American or Afro-Caribbean | — | TCGA | — |
| PSS011527 | — | — | 71 individuals | — | Not reported | — | TCGA | — |
| PSS000072 | BRCA1 mutation carriers were followed until the age of ovarian cancer diagnosis, age at risk-reducing salpingo-oophorectomy (RRSO) or age at last observation. Breast cancer diagnosis was not considered as a censoring event in the ovarian cancer analysis | — | [ ,
0.0 % Male samples |
— | European | Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry | CIMBA | Median censoring age (cases) = 50 |
| PSS000073 | BRCA2 mutation carriers were followed until the age of ovarian cancer diagnosis, age at risk-reducing salpingo-oophorectomy (RRSO) or age at last observation. Breast cancer diagnosis was not considered as a censoring event in the ovarian cancer analysis | — | [ ,
0.0 % Male samples |
— | European | Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry | CIMBA | Median censoring age (cases) = 57 |
| PSS000550 | PheCode:184.11; ICD9CM:183.0, V10.43; ICD10CM:C56, C56.1, C56.2, C56.9 | — | [
|
— | European | — | MGI | — |
| PSS000553 | PheCode:187.2; ICD9CM:186.0, 186.9, V10.47; ICD10CM:C62, C62.0, C62.00, C62.01, C62.02, C62.1, C62.10, C62.11, C62.12, C62.9, C62.90, C62.91, C62.92 | — | [
|
— | European | — | MGI | — |
| PSS000558 | PheCode:193; ICD9CM:193, V10.87; ICD10CM:C73 | — | [
|
— | European | — | MGI | — |
| PSS000565 | PheCode:157; ICD9:157, 157.0, 157.1, 157.2, 157.3, 157.4, 157.8, 157.9; ICD10:C25.0, C25.1, C25.2, C25.3, C25.4, C25.7, C25.8, C25.9 | — | [
|
— | European | — | UKB | — |
| PSS000083 | Cases were clinically diagnosed with T1D before 17 years of age and treated with insulin from diagnosis. Patients with known MODY or NDM were excluded. | — | [
|
— | European | — | WTCCC | Cases with Type 1 Diabetes |
| PSS000083 | MODY patients with a confirmed monogenic etiology on genetic testing (415 patients with HNF1A MODY, 346 with GCK MODY, 42 with HNF4A MODY, and 2 with HNF1B MODY). The median age of diagnosis was 20 years (interquartile range 15, 30), and 532 patients were female. | — | [ ,
33.91 % Male samples |
— | European | — | NR | Maturity-onset diabetes of young (MODY) cases ascertained from the Genetic Βeta Cell Research Bank, Exeter, U.K. |
| PSS000572 | PheCode:184.11; ICD9:183.0; ICD10:C56 | — | [
|
— | European | — | UKB | — |
| PSS000574 | PheCode:187.2; ICD9:186, 186.0, 186.9; ICD10:C62.0, C62.1, C62.9 | — | [
|
— | European | — | UKB | — |
| PSS011531 | Cases were individuals with T1D | — | [ ,
53.51 % Male samples |
— | European | — | NR | — |
| PSS011532 | Cases were individuals with T1D | — | [ ,
53.79 % Male samples |
— | European | — | NR | — |
| PSS000579 | PheCode:193; ICD9:193; ICD10:C73 | — | [
|
— | European | — | UKB | — |
| PSS000583 | Case inclusion ICD codes: ICD9=571.5, ICD9=571.8, ICD9=571.9, ICD10=K75.81, ICD10=K76.0, ICD10=K76.9 | — | [ ,
42.6 % Male samples |
— | European | — | eMERGE | — |
| PSS000584 | Controls are cases with Nonalcoholic fatty liver disease activity score <5 and cases are those with a score >5. Case inclusion ICD codes: ICD9=571.5, ICD9=571.8, ICD9=571.9, ICD10=K75.81, ICD10=K76.0, ICD10=K76.9 | — | [
|
— | European | — | eMERGE | — |
| PSS011537 | — | Median = 8.9 years IQR = [8.3, 9.5] years |
[ ,
44.6 % Male samples |
Mean = 56.1 years Sd = 8.0 years |
European (White British) |
— | UKB | — |
| PSS000597 | In this study, cases were incident patients with primary pancreatic adenocarcinoma ascertained between 1984 and 2010 through self- report, report of next-of-kin, or death certificates and confirmed by medical record review and tumor registry data. Cases Diagnosed within 10 years of blood collection. | Mean = 10.0 years | [ ,
28.1 % Male samples |
— | European | — | HPFS, NHS, PHS, WHI | Overlap with GWAS samples (percentage unknown). Cross validation approach used (20% as testing sample) |
| PSS000598 | In this study, cases were incident patients with primary pancreatic adenocarcinoma ascertained between 1984 and 2010 through self- report, report of next-of-kin, or death certificates and confirmed by medical record review and tumor registry data. | — | [ ,
33.4 % Male samples |
— | European | — | HPFS, NHS, PHS, WHI | Overlap with GWAS samples (percentage unknown). Cross validation approach used (20% as testing sample) |
| PSS000108 | Adjudicated endpoint determined from medical notes by an outcome review committee | Mean = 11.1 years IQR = [10.0, 12.0] years |
[ ,
0.0 % Male samples |
Mean = 63.0 years Range = [50.0, 74.0] years |
European | — | UKCTOCS | — |
| PSS000108 | Adjudicated endpoint determined from medical notes by an outcome review committee | Mean = 11.1 years IQR = [10.0, 12.0] years |
[ ,
0.0 % Male samples |
Mean = 63.0 years Range = [50.0, 74.0] years |
European | — | UKCTOCS | — |
| PSS003602 | All individuals were childhood cancer survivors. Of the 6,414 childhood cancer survivors, 1,374 had received neck radiotherapy (neck-RT) as a form of treatment. Cases were individuals who developed subsequent thyroid cancer (STC). Cases of STC were ascertained by self-report questionnaires and subsequently confirmed by pathology reports. 73 of the 121 STC cases had received neck-RT as a form of childhood cancer treatment, whilst 48 had not. Of the controls, 1,301 had received neck-RT as a form of childhood cancer treatment. | Median = 36.5 years | [ ,
47.7 % Male samples |
— | European | — | NR | — |
| PSS003603 | All individuals were childhood cancer survivors. Of the 2,370 childhood cancer survivors, 476 had received neck radiotherapy (neck-RT) as a form of treatment. Cases were individuals who developed subsequent thyroid cancer (STC). Cases of STC were clinically ascertained. 47 of the 65 STC cases had received neck-RT as a form of childhood cancer treatment, whilst 18 had not. | Median = 36.6 years IQR = [30.3, 44.1] years |
[ ,
53.4 % Male samples |
— | European | — | SJCRH | — |
| PSS009514 | — | — | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS009518 | — | — | [
|
— | European (Estonian) |
— | EB | — |
| PSS009522 | — | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS003606 | — | — | [
|
Mean = 56.81 years | European | — | UKB | — |
| PSS009526 | — | — | [
|
— | European | Norwegian | HUNT | — |
| PSS009530 | — | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS007643 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS007644 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS007645 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009534 | — | — | [
|
— | European | — | MGBB | — |
| PSS009538 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS009542 | — | — | [
|
— | European | British | UKB | — |
| PSS007656 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS007657 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS009546 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS007658 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS007659 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS007660 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS007667 | — | — | [ ,
72.3 % Male samples |
— | European | — | GenomALC | — |
| PSS007668 | — | — | [ ,
62.06 % Male samples |
— | European | — | GenomALC | — |
| PSS007669 | — | — | [ ,
77.02 % Male samples |
— | European | — | UKB | — |
| PSS007684 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | Median = 13.0 years IQR = [7.5, 19.7] years |
[ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007685 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
42.9 % Male samples |
Mean (Age At Baseline) = 51.8 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007686 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS009573 | — | — | [ ,
0.0 % Male samples |
— | East Asian (Chinese) |
— | NR | — |
| PSS007690 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | Median = 10.4 years IQR = [8.3, 11.3] years |
[ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007691 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
45.5 % Male samples |
Mean (Age At Baseline) = 57.2 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007692 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS000121 | Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 27040 | — | [ ,
0.0 % Male samples |
— | European | — | GERA, UKB | — |
| PSS000122 | Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 21100 | — | [ ,
46.0 % Male samples |
Mean = 58.0 years | European | — | GERA, UKB | — |
| PSS000125 | Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 28020 | — | [ ,
100.0 % Male samples |
— | European | — | UKB | — |
| PSS000126 | Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 32010 | — | [ ,
46.0 % Male samples |
Mean = 58.0 years | European | — | GERA, UKB | — |
| PSS007697 | — | — | [
|
— | European | — | CanPath | — |
| PSS009595 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. | Median = 109.0 months | [ ,
52.0 % Male samples |
Mean = 61.3 years | Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — |
| PSS009596 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. | — | [
|
— | Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — |
| PSS009597 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. | — | [
|
Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — | |
| PSS009598 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. | — | [
|
— | Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — |
| PSS009599 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. | — | [
|
Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — | |
| PSS009600 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. LSDM is defined in cases as type 2 diabetes diagnosed more than 24 months before PDAC diagnosis. Defined in controls as type 2 diabetes diagnosed more than 24 months before date of death or date of last follow up. | — | [
|
— | Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — |
| PSS009601 | PDAC cases were considered incident if diagnosed after study entry or without a date of diagnosis if identified by mortality alone. NODM is defined in cases as type 2 diabetes diagnosed within 24 months before or after diagnosis of PDAC. Defined in controls as type 2 diabetes diagnosed 24 months before death or last follow up. | — | [
|
— | Not reported | European, African American or Afro-Caribbean, South Asian, East Asian, African unspecified | UKB | — |
| PSS000754 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000755 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000756 | ICD-10 E11.0 - E11.9 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS007717 | — | — | [
|
— | European | — | UKB | — |
| PSS007730 | — | — | 2,453 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000792 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000793 | ICD-10 K70 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS007734 | — | — | 2,378 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007735 | — | — | 2,410 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007736 | — | — | 2,434 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007737 | — | — | 2,200 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007738 | — | — | 2,476 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009629 | — | — | 5,806 individuals | — | South Asian (Indian) |
— | INSPIRED | Dr. Mohan’s Diabetes Specialities Centre (INSPIRED - DMDSC) |
| PSS007782 | — | — | 2,429 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009638 | — | — | 25,716 individuals, 41.5 % Male samples |
Mean = 56.0 years Sd = 7.7 years |
European | — | UKB | — |
| PSS000858 | Data and diagnoses on site-specific incident cancers were provided by the National Health Service Information Centre for participants from England and Wales (follow-up through March 31, 2016) and by the NHS Central Register Scotland for participants from Scotland (follow-up through October 31, 2015). Cancers were coded by the International Classification of Diseases, Ninth Revision (ICD-9) or the International Classification of Diseases, Tenth Revision (ICD-10). Ovarian cancer=(ICD-9 = 183.0 or ICD-10 = C56; ICD-O: 8441, 8460, 8462, 8380, 8381, 8470, 8471, 8472, 8473, 8480, 8310, 8140, 8260, 8440, 8450, 9000, 8000, and 8010) | Median = 5.8 years | [ ,
46.5 % Male samples |
— | European | — | UKB | — |
| PSS000232 | Individuals with T2D were defined as those with fasting time >8 h and fasting glucose levels ≥126 mg/dL, fasting ≤8 h and fasting glucose ≥200 mg/dL, post–oral glucose tolerance test glucose ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or on current treatment with antihyperglycemia medications. | — | [ ,
39.65 % Male samples |
— | Hispanic or Latin American (Central American, Cuban, Dominican, Mexican, Puerto Rican, South American) |
Ancestry groups were defined based on a combination of self-identified Hispanic/Latino background and genetic similarity | HCHS, SOL | — |
| PSS000859 | Data and diagnoses on site-specific incident cancers were provided by the National Health Service Information Centre for participants from England and Wales (follow-up through March 31, 2016) and by the NHS Central Register Scotland for participants from Scotland (follow-up through October 31, 2015). Cancers were coded by the International Classification of Diseases, Ninth Revision (ICD-9) or the International Classification of Diseases, Tenth Revision (ICD-10). Pancreatic Cancer=(ICD-9 = 157 or ICD-10 = C25) | Median = 5.8 years | [ ,
46.5 % Male samples |
— | European | — | UKB | — |
| PSS000861 | Cases included individuals with cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | European | — | PHB | — |
| PSS000862 | Cases included individuals with cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | NR | — | PHB | — |
| PSS000863 | Cases included individuals with cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | NR | — | PHB | — |
| PSS000864 | All individuals had hepatitis B. Cases included individuals cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | European | — | PHB | — |
| PSS000865 | All individuals had hepatitis B. Cases included individuals cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | European | — | PHB | — |
| PSS000866 | Cases included individuals with cirrhosis, biopsy confirmed cirrhosis and/or cirrhosis ascertained through ICD codes:Hospitalization or death due to physician diagnosed cirrhosis: K70.2 (alcoholic fibrosis and sclerosis of the liver), K70.3 (alcoholic cirrhosis), K70.4 (alcoholic hepatic failure), K74.0 (hepatic fibrosis), K74.1 (hepatic sclerosis), K74.2 (hepatic fibrosis with hepatic sclerosis), K74.6 (other and unspecific cirrhosis of liver), K76.6 (portal hypertension), or I85 (esophageal varices). | — | [
|
— | African unspecified | — | PHB | — |
| PSS000869 | CALIBER rule-based phenotyping algorithms (https://github.com/spiros/chronological-map-phenotypes#diabetes) | Median = 6.9 years | [ ,
51.0 % Male samples |
Median = 44.0 years IQR = [30.5, 54.7] years |
European | — | INTERVAL | — |
| PSS009669 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | GenHAT | — |
| PSS009670 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | HYPERGEN | — |
| PSS009671 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | REGARDS | — |
| PSS009672 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009673 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009674 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009675 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | WPC | — |
| PSS009676 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | African American or Afro-Caribbean (African) |
— | eMERGE | — |
| PSS009677 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | European (European) |
— | eMERGE | — |
| PSS009678 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | Hispanic or Latin American (Hispanic/Latino) |
— | eMERGE | — |
| PSS007948 | — | — | 1,801 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007953 | — | — | 1,744 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007954 | — | — | 1,754 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007955 | — | — | 1,782 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007956 | — | — | 1,729 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007957 | — | — | 1,808 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS009727 | — | — | 6,430 individuals | — | African unspecified | — | UKB | — |
| PSS009728 | — | — | 898 individuals | — | East Asian | — | UKB | — |
| PSS009729 | — | — | 43,355 individuals | — | European | Non-British European | UKB | — |
| PSS009730 | — | — | 7,926 individuals | — | South Asian | — | UKB | — |
| PSS010982 | — | Mean = 7.15 years | [
|
Mean = 31.04 years Sd = 10.43 years |
Native American | — | NR | — |
| PSS010983 | — | Mean = 21.28 years | [
|
— | Native American | — | NR | — |
| PSS010984 | — | Mean = 7.99 years | [
|
Mean = 12.05 years Sd = 3.73 years |
Native American | — | NR | — |
| PSS007998 | — | — | 1,783 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS009739 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009740 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009741 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009742 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS010991 | — | — | 501 individuals | Mean = 60.09 years | European | — | TCGA | — |
| PSS010993 | — | — | 153 individuals | Mean = 65.63 years | European | — | TCGA | — |
| PSS010996 | — | — | 360 individuals | Mean = 48.04 years | European | — | TCGA | — |
| PSS010998 | — | — | [
|
— | European | — | MGI | — |
| PSS010999 | — | — | [
|
— | European | — | UKB | — |
| PSS011000 | — | — | [
|
— | European | — | UKB | — |
| PSS011001 | — | — | [
|
— | European | — | UKB | — |
| PSS011002 | — | — | [
|
— | European | — | UKB | — |
| PSS011003 | — | — | [
|
— | European | — | UKB | — |
| PSS011005 | — | — | [
|
— | African American or Afro-Caribbean (Black) |
— | OCAC | — |
| PSS011005 | — | — | [
|
— | European | — | OCAC | — |
| PSS011005 | — | — | [
|
— | Not reported | — | OCAC | — |
| PSS009787 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009788 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009789 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009790 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 16,663 individuals, 48.0 % Male samples |
Mean = 51.9 years Sd = 14.8 years |
European | Self-identified race = White | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 11,443 individuals, 39.0 % Male samples |
Mean = 48.4 years Sd = 14.1 years |
African American or Afro-Caribbean | Self-identified race = Black | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 19,524 individuals, 37.0 % Male samples |
Mean = 50.3 years Sd = 15.3 years |
Hispanic or Latin American | Self-identified race = Hispanic | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 10,013 individuals, 46.0 % Male samples |
Mean = 55.9 years Sd = 13.9 years |
East Asian, South East Asian, Native American, South Asian, Other | Self-identified race = Other | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 11,443 individuals, 39.0 % Male samples |
Mean = 48.4 years Sd = 14.1 years |
African American or Afro-Caribbean | Self-identified race = Black | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 19,524 individuals, 37.0 % Male samples |
Mean = 50.3 years Sd = 15.3 years |
Hispanic or Latin American | Self-identified race = Hispanic | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 10,013 individuals, 46.0 % Male samples |
Mean = 55.9 years Sd = 13.9 years |
East Asian, South East Asian, Native American, South Asian, Other | Self-identified race = Other | BioMe | — |
| PSS011011 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 16,663 individuals, 48.0 % Male samples |
Mean = 51.9 years Sd = 14.8 years |
European | Self-identified race = White | BioMe | — |
| PSS011012 | — | — | 34,939 individuals, 47.0 % Male samples |
Mean = 59.1 years Sd = 16.9 years |
European | Self-identified race = white | MGBB | — |
| PSS011012 | — | — | 2,101 individuals, 37.0 % Male samples |
Mean = 52.1 years Sd = 16.3 years |
African American or Afro-Caribbean (Black) |
— | MGBB | — |
| PSS011012 | — | — | 1,269 individuals, 34.0 % Male samples |
Mean = 46.4 years Sd = 16.1 years |
Hispanic or Latin American (Hispanic) |
— | MGBB | — |
| PSS011012 | — | — | 1,511 individuals, 36.0 % Male samples |
Mean = 46.9 years Sd = 16.3 years |
Native American, Asian unspecified, Oceanian, Other | — | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 2,101 individuals, 37.0 % Male samples |
Mean = 52.1 years Sd = 16.3 years |
African American or Afro-Caribbean | Self-identified race = Black | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 1,269 individuals, 34.0 % Male samples |
Mean = 46.4 years Sd = 16.1 years |
Hispanic or Latin American | Self-identified race = Hispanic | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 1,511 individuals, 36.0 % Male samples |
Mean = 46.9 years Sd = 16.3 years |
Native American, Asian unspecified, Oceanian, Other | Self-identified race = Other | MGBB | — |
| PSS011014 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 34,939 individuals, 47.0 % Male samples |
Mean = 59.1 years Sd = 16.9 years |
European | Self-identified race = White | MGBB | — |
| PSS000970 | — | Median = 400.0 days | 1,584 individuals | — | European | — | GNEHGI2020Q2 | — |
| PSS000278 | Primary tumor samples from TCGA | — | [ ,
0.0 % Male samples |
Mean = 60.0 years Sd = 12.0 years |
European | — | TCGA | — |
| PSS000278 | — | — | [ ,
0.0 % Male samples |
— | European | — | eMERGE | — |
| PSS000279 | Primary tumor samples from TCGA | — | [
|
Mean = 66.0 years Sd = 11.0 years |
European | — | TCGA | — |
| PSS000279 | — | — | [
|
— | European | — | eMERGE | — |
| PSS000282 | Primary tumor samples from TCGA | — | [
|
Mean = 49.0 years Sd = 16.0 years |
European | — | TCGA | — |
| PSS000282 | — | — | [
|
— | European | — | eMERGE | — |
| PSS004134 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004135 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004136 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004137 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004138 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009847 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009848 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009849 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009850 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS009859 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009860 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009861 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009862 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS008161 | — | — | 6,305 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008166 | — | — | 5,927 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008167 | — | — | 5,954 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008168 | — | — | 6,272 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008169 | — | — | 5,228 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008170 | — | — | 6,312 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008217 | — | — | 6,209 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009893 | — | — | 366 individuals | — | African American or Afro-Caribbean | — | SEARCH | — |
| PSS009894 | — | — | 412 individuals | — | Hispanic or Latin American | — | SEARCH | — |
| PSS009895 | — | — | 1,168 individuals | — | European | — | SEARCH | — |
| PSS009896 | — | — | 99 individuals | — | Not reported | — | SEARCH | — |
| PSS000996 | All individuals (cases and controls) met the at-risk criteria for nonalcoholic fatty liver disease (NAFLD) defined as a BMI ≥30 kg/m2 or diagnosis of type 2 diabetes, or both, without evidence of any other cause of liver disease including excess alcohol . Cases were individuals who had been hospitalised with cirrhosis for the first time. A hospital admission for cirrhosis was defined according to the Ratib et al (PMID: 24419483) validated algorithm incorporating appropriate ICD discharge codes and OPCS Classification of Interventions and Procedures version 4 codes. | Mean = 7.9 years | [ ,
43.0 % Male samples |
Median = 59.0 years Range = [52.0, 64.0] years |
Not reported | — | UKB | GRS dataset used to test/ evaluate performance of GRS. The GRS dataset is independent of the discovery analysis datasets containing UKB participants. Possible sample overlap between the GRS dataset and the phase 1 replication/validation analysis and phase 2 replication analysis datasets containing UKB participants. |
| PSS009902 | — | — | [
|
— | European (Italian) |
— | NR | — |
| PSS009913 | — | — | [
|
— | European | — | PANSCAN | — |
| PSS004312 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004313 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004314 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004315 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004316 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS004354 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004355 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004356 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004357 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004358 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004359 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004360 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004361 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004362 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004363 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009939 | — | — | 39,444 individuals | — | European (Finnish) |
— | FinnGen | — |
| PSS009943 | We used the disease definitions described in the supplement of Eastwood et al (2016). PMID: 27631769 | — | [ ,
45.0 % Male samples |
European | — | UKB | — | |
| PSS000341 | Cases were ascertained using ICD-10 C73 (PTC, FTC, cancer/carcinoma, and rare nonmedullary) | — | [ ,
46.41 % Male samples |
— | European | — | deCODE | — |
| PSS000342 | Histologically confirmed papillary or follicular thyroid carcinoma (PTC) patients (including traditional PTC and follicular variant PTC) | — | [ ,
26.08 % Male samples |
— | European | — | NR | — |
| PSS000343 | Cases were ascertained using ICD-10 C73 (PTC, FTC, cancer/carcinoma, and rare nonmedullary) | — | [ ,
45.97 % Male samples |
— | European | — | UKB | — |
| PSS001021 | Individuals with at least one recorded incident diagnosis of a borderline, in situ, or malignant primary cancer were defined as cases. | — | [ ,
0.0 % Male samples |
— | European | — | UKB | — |
| PSS001022 | Individuals with at least one recorded incident diagnosis of a borderline, in situ, or malignant primary cancer were defined as cases. | — | [
|
— | European | — | UKB | — |
| PSS008383 | — | — | 1,197 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS001024 | Individuals with at least one recorded incident diagnosis of a borderline, in situ, or malignant primary cancer were defined as cases. | — | [ ,
100.0 % Male samples |
— | European | — | UKB | — |
| PSS001025 | Individuals with at least one recorded incident diagnosis of a borderline, in situ, or malignant primary cancer were defined as cases. | — | [
|
— | European | — | UKB | — |
| PSS008388 | — | — | 1,140 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008389 | — | — | 1,143 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008390 | — | — | 1,186 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008391 | — | — | 1,107 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008392 | — | — | 1,197 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS004457 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004458 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004459 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004460 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008437 | — | — | 1,185 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009971 | — | — | 30,716 individuals | — | European | — | MGBB | — |
| PSS011181 | — | — | 3,071 individuals, 48.8 % Male samples |
Mean = 57.4 years Sd = 12.88 years |
Not reported | — | KORA | — |
| PSS009971 | — | — | 1,807 individuals | — | African unspecified (Black) |
— | MGBB | — |
| PSS009971 | — | — | 786 individuals | — | Asian unspecified | — | MGBB | — |
| PSS009971 | — | — | 3,113 individuals | — | Other | — | MGBB | — |
| PSS011182 | — | — | 381,825 individuals | — | European | — | UKB | — |
| PSS001044 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes, and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. For the ARIC cohort prevalent type 2 diabetes was defined at the baseline examination as fasting (≥8 h) blood glucose ≥126 mg/dL, or nonfasting glucose ≥200 mg/dL, self-report physician diagnosis of diabetes or “sugar in the blood,” or current medication use for diabetes within the last two weeks. For the CARDIA cohort, T2D was determined at last visit based on a combination of measured fasting glucose levels (≥7.0 mmol/L and ≥126 mg/dL) at examination years 0, 7, 10, 15, 20, or 25; self-report of oral hypoglycemic medications or insulin at years 0, 7, 10, 15, 20, or 25; a 2-h postload glucose ≥11.1 mmol/L (≥200 mg/dL) during a 75-g oral glucose tolerance test at years 10, 20, and 25; or an HbA1c ≥6.5% at years 20 and 25. | — | [
|
— | African American or Afro-Caribbean | — | ARIC, BioMe, CARDIA, MEC, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dafr. |
| PSS001045 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. | — | [
|
— | Asian unspecified | — | BioMe, MEC, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dasn. |
| PSS001046 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the UKB cohort, T2D cases were defined by an ICD-10 code of E11.X or a self-reported diagnosis in an interview with a trained nurse. | — | [
|
— | European | — | UKB | Possible significant sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Deur |
| PSS001047 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. For the SOL cohort, T2D cases were defined as those with fasting time >8 h and fasting glucose levels ≥126 mg/dL, fasting ≤8 h and fasting glucose ≥200 mg/dL, post–oral glucose tolerance test glucose ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or on current treatment with antihyperglycemia medications. | — | [
|
— | Hispanic or Latin American | — | BioMe, MEC, SOL, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dhis. |
| PSS001048 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individualswith (1) a T2D diagnosis by a physician/medical professional and use of medication for treat-mentofdiabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. | — | [
|
— | Oceanian (Native Hawaiian) |
— | MEC | — |
| PSS004526 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004527 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004528 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004529 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004530 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS001068 | Spontaneous hypothyroidism cases and controls were defined using phecodes, which aggregate similar ICD-9-CM and ICD-10-CM. Individuals must have had at least 2 ICD codes for hypothyroidism to be assigned a phecode, and individuals with other thyroid diseases were excluded from the control set. | — | 51,070 individuals | — | European | — | BioVU | — |
| PSS001069 | All individuals had non-small cell lung cancer (NSCLC) and were receiving immune checkpoint inhibitor (CPI) therapy. Cases were individuals who had experienced immune-related thyroid dysfunction following CPI therapy. A thyroid event after the start of CPI therapy was defined as either (1) incident hypothyroidism or (2) transient incident hyperthyroidism followed by incident hypothyroidism. Incident hypothyroidism was defined as (a) a TSH of ≥ 10 mU/L or (b) TSH of ≥ 5 mU/L with a new prescription of levothyroxine ≥ 50 mcg. Incident hyperthyroidism was defined as TSH < 0.05 mU/L. | Median = 12.0 months | [ ,
44.0 % Male samples |
Median = 67.0 years IQR = [60.0, 74.0] years |
European, African unspecified, Asian unspecified, Hispanic or Latin American, NR | European = 506, African unspecified = 22, Asian unspecified = 17, Not reported = 6, Hispanic or Latin American = 10 | NR | Cases and controls were obtained from the Dana-Farber Cancer Institute (DFCI) |
| PSS001070 | All individuals had non-small cell lung cancer (NSCLC) and were receiving immune checkpoint inhibitor (CPI) therapy. of the 744 individuals receiving CPI therapy, 659 were being treated with Anti-PD-(L)1 monotherapy whilst 85 were being treated with Anti-PD-(L)1+CTLA-4 combination therapy. Cases were individuals who had experienced immune-related thyroid dysfunction following CPI therapy. A thyroid event after the start of CPI therapy was defined as either (1) incident hypothyroidism or (2) transient incident hyperthyroidism followed by incident hypothyroidism. Incident hypothyroidism was defined as (a) a TSH of ≥ 10 mU/L or (b) TSH of ≥ 5 mU/L with a new prescription of levothyroxine ≥ 50 mcg. Incident hyperthyroidism was defined as TSH < 0.05 mU/L. | — | [ ,
50.94 % Male samples |
— | European, African unspecified, Asian unspecified, Hispanic or Latin American, NR | European = 634, African unspecified = 50, Asian unspecified = 36, Not reported = 4, Hispanic or Latin American = 20 | MSKCC | Additional cases and controls were obtained from the Vanderbilt University Medical Centre (VUMC) |
| PSS001071 | All individuals had non-small cell lung cancer (NSCLC) and were receiving immune checkpoint inhibitor (CPI) therapy. Cases were individuals who had experienced immune-related thyroid dysfunction following CPI therapy. A thyroid event after the start of CPI therapy was defined as either (1) incident hypothyroidism or (2) transient incident hyperthyroidism followed by incident hypothyroidism. Incident hypothyroidism was defined as (a) a TSH of ≥ 10 mU/L or (b) TSH of ≥ 5 mU/L with a new prescription of levothyroxine ≥ 50 mcg. Incident hyperthyroidism was defined as TSH < 0.05 mU/L. | — | 634 individuals | — | European | — | MSKCC | Additional cases and controls were obtained from the Vanderbilt University Medical Centre (VUMC) |
| PSS000368 | TEDDY children were followed prospectively from 3–4 months of age, with visits every 3 months until 4 years of age. Each evaluation tested the three islet antibodies (GADA, IA2A and IAA), changes in family history, as well as other measurements specified by the TEDDY protocol. After 4 years of age, children with any islet autoantibodies remained on quarterly visits, while antibody-negative children were evaluated every 6 months. Children were followed prospectively until 15 years of age or until T1D onset, as defined using the American Diabetes Association’s criteria for diagnosis (doi: 10.1196/annals.1447.062) | Median = 9.3 years Range = [0.0833, 14.0] years |
[ ,
50.86 % Male samples |
Range = [3.0, 4.0] years | NR | — | TEDDY | From 2004–2010, 424,788 newborns were screened at six US and European centers for high-risk HLA genotypes. TEDDY then enrolled 8,676 eligible infants with the intent to follow them until 15 years of age. The three major eligible HLA DR–DQ haplotypes are DR3–DQA1*0501–DQB1*0201, DR4–DQA1*0301–DQB1*0302 and DR8–DQA1*0401–DQB1*0402. |
| PSS004555 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004556 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004557 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004558 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004559 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004560 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004561 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004562 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004563 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004564 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004565 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004566 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004567 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004568 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004569 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004570 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004571 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004572 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004573 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004574 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004575 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004576 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004577 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004578 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004579 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004580 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004581 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004582 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004583 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004584 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004585 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004586 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004587 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004588 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004589 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS001084 | Moderate Age-Related Diabetes (MARD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001085 | Moderate Obesity-related Diabetes (MOD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001086 | Severe Autoimmune Diabetes (SAID) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001087 | Severe Insulin-Deficient Diabetes (SIDD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001088 | Severe Insulin-Resistant Diabetes (SIRD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001092 | All individuals had cystic fibrosis with either 2 severe CFTR mutations and/or clinically diagnosed exocrine pancreatic insufficiency. Cases are individuals with cystic fibrosis related diabetes (CFRD).Phenotypes were obtained from extracted medical charts and CF Foundation Patient Registry through 2011. CFRD was defined by clinician diagnosis of diabetes plus insulin treatment for at least 1 year. The onset of CFRD was defined as the date at which insulin was started, if it was subsequently continued for at least 1 year. In approximately 50% of the participants, independent laboratory data (such as oral glucose tolerance test or hemoglobin A1c) were able to independently confirm the diagnosis of CFRD. Diabetes data were censored at the last clinic visit or date of solid organ transplant. | — | [ ,
47.04 % Male samples |
Mean = 20.0 years | Not reported | — | CGS, CWRU, FrGMC, JHU, UNC | — |
| PSS001094 | Cases were individuals with liver disease. Of the 1,699 cases, 1,473 had fatty liver disease (FLD) whilst 226 had hepatocellular carcinoma (HCC). Of the 1,473 individuals with FLD, 297 had severe fibrosis and were therefore classified as being within stage 3-4 of FLD. Severe fibrosis was defined in the presence of histological fibrosis F3-F4 (when liver biopsy was available) or in presence of clinical, endoscopic or radiological signs of portal hypertension or cirrhosis, or liver stiffness ≥8.4 kPa evaluated by Fibroscan. Diagnosis of HCC was based on EASL-EORTC Clinical Practice Guidelines. | — | [ ,
57.76 % Male samples |
— | European | — | NR | Cases were obtained from the Nonalcoholic Fatty Liver Disease (NAFLD) Case-Control Cross-Sectional Cohort. |
| PSS001095 | All individuals had liver disease. Of the 158 cases, 72 had cirrhosis whilst 84 had hepatocellular cancer. Diagnosis of HCC was based on EASL-EORTC Clinical Practice Guidelines | — | [ ,
43.59 % Male samples |
— | Not reported | — | NR | — |
| PSS001096 | Cases were individuals with liver disease. Of the 1,628 cases, 1,426 individuals had cirrhosis whilst 202 had hepatocellular cancer (HCC). Cirrhosis was defined as ICD-10 codes I85.0, I85.9, K70.3, K70.4, K72.1, K74.1, K74.2, K74.6, K76.6, K76.7 using hospitalization records (data-field 41270). HCC was defined by combining International Classification of Diseases, Tenth Revision (ICD-10) code C22.0 from both UK cancer registry (data-field 40006), and hospitalization records (data-field 41270). | — | [ ,
46.22 % Male samples |
— | European | — | UKB | — |
| PSS001097 | Cases were individuals with hepatocellular cancer (HCC). HCC was defined by combining International Classification of Diseases, Tenth Revision (ICD-10) code C22.0 from both UK cancer registry (data-field 40006), and hospitalization records (data-field 41270). | — | [
|
— | European | — | UKB | — |
| PSS001098 | All individuals had a body mass index ≥30. Cases were individuals with hepatocellular cancer (HCC). HCC was defined by combining International Classification of Diseases, Tenth Revision (ICD-10) code C22.0 from both UK cancer registry (data-field 40006), and hospitalization records (data-field 41270). | — | [
|
— | European | — | UKB | — |
| PSS008607 | — | — | 6,640 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS001101 | All individuals had no diagnosis of cirrhosis. Cases were individuals with hepatocellular cancer (HCC). HCC was defined by combining International Classification of Diseases, Tenth Revision (ICD-10) code C22.0 from both UK cancer registry (data-field 40006), and hospitalization records (data-field 41270). | — | [
|
— | European | — | UKB | — |
| PSS001103 | All individuals had type 2 diabetes (T2D). Diabetes was defined as individuals having either of following criteria: 1) self-reported type 2 or unspecified diabetes (codes 1220 and 1223 in data-field 20002); 2) ICD10 diagnoses codes E11 and E14 (data-field 41270); 3) insulin treatment or use of oral glucose lowering drugs (data-fields 6153, 6177 and 20003); 4) serum glucose level ≥11.1 mmol/L (200mg/dL); 5) HbA1c ≥ 48 mmol/mol (6.5%). Cases were individuals with hepatocellular cancer (HCC). HCC was defined by combining International Classification of Diseases, Tenth Revision (ICD-10) code C22.0 from both UK cancer registry (data-field 40006), and hospitalization records (data-field 41270). | — | [
|
— | European | — | UKB | — |
| PSS008612 | — | — | 6,363 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008614 | — | — | 6,601 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008615 | — | — | 6,300 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008616 | — | — | 6,646 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008613 | — | — | 6,381 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS001117 | T2D cases were defined as having an ICD-10 code of E11.X or having self-reported T2D in the in- terview. Only cases in which the individuals did not have T2D during the first assessment visit period (2006–2010) but were subsequently fol- lowed up for incident T2D events were considered. | Median = 3.58 years | [ ,
47.81 % Male samples |
— | European | — | UKB | — |
| PSS008663 | — | — | 6,543 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS010014 | PheCode 250.2 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | MGI | — |
| PSS011224 | — | — | [
|
— | European | — | EB | — |
| PSS011225 | — | — | [
|
— | European | — | EB | — |
| PSS010036 | Field ID: 2443; Binary | — | [
|
— | European | — | UKB | — |
| PSS011235 | T1D, ICD10: E10, ICD9: 250[0|1]1 (exclude E11) | — | [
|
— | European | — | FinnGen | — |
| PSS011236 | T2D, ICD10: E11, ICD9: 250[0|1]0 (exclude E10) | — | [
|
— | European | — | FinnGen | — |
| PSS011248 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011249 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS000441 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
47.3 % Male samples |
Mean (Age At Baseline) = 48.0 years | European (Finnish) |
— | FINRISK | FINRISK surveys from 1992, 1997, 2002 and 2007 |
| PSS011264 | — | — | [
|
— | European | — | HUNT | — |
| PSS000448 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
43.7 % Male samples |
Mean (Age At Baseline) = 59.2 years Sd = 16.6 years |
European (Finnish) |
— | FinnGen | — |
| PSS011265 | — | — | [
|
— | European | — | HUNT | — |
| PSS011277 | — | — | [
|
— | European | — | UKB | — |
| PSS011278 | — | — | [
|
— | European | — | UKB | — |
| PSS010055 | — | — | 22,608 individuals | — | East Asian | — | KBA, KoGES | — |
| PSS011291 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011295 | — | — | 1,798 individuals | — | Not reported | — | NR | StartRight |
| PSS011296 | 22,667 sibling pairs | — | 45,334 individuals | — | European | — | UKB | — |
| PSS006886 | — | — | 673 individuals | — | African unspecified | — | UKB | — |
| PSS006887 | — | — | 86 individuals | — | East Asian | — | UKB | — |
| PSS006888 | — | — | 1,059 individuals | — | European | non-white British ancestry | UKB | — |
| PSS006889 | — | — | 1,335 individuals | — | South Asian | — | UKB | — |
| PSS006890 | — | — | 3,195 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011299 | T2D ICD-10 code E11 | Median = 12.55 years IQR = [11.72, 13.27] years |
395,809 individuals, 45.8 % Male samples |
Mean = 56.7 years Sd = 8.0 years |
European | — | UKB | — |
| PSS011301 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011302 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011303 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011304 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011305 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS008833 | — | — | 3,896 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008837 | — | — | 3,830 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008838 | — | — | 3,836 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008839 | — | — | 3,876 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008840 | — | — | 3,490 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008841 | — | — | 3,896 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011306 | — | — | 5,024 individuals, 40.0 % Male samples |
— | East Asian (Chinese) |
— | Wuxi NCDs | — |
| PSS010083 | C56, histology was one of the followings: Papillary serous cystadenocarcinoma; Serous cystadenocarcinoma; Serous cystadenoma, borderline malignancy; Serous papillary cystic tumor of borderline malignancy; Serous surface papillary carcinoma | — | [
|
— | European (British) |
— | UKB | Controls were samples without any cancer diagnosis or self-reported cancer |
| PSS010087 | — | — | [ ,
0.0 % Male samples |
— | European | — | CIMBA | — |
| PSS010088 | — | — | [ ,
0.0 % Male samples |
— | European | — | CIMBA | — |
| PSS010089 | — | — | [ ,
0.0 % Male samples |
— | African unspecified | — | OCAC | — |
| PSS010090 | — | — | [ ,
0.0 % Male samples |
— | East Asian | — | OCAC | — |
| PSS010091 | — | — | [ ,
0.0 % Male samples |
— | European | — | UKB | — |
| PSS008886 | — | — | 3,837 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS010098 | — | — | 189,171 individuals, 0.0 % Male samples |
— | European | — | UKB | — |
| PSS011323 | — | — | [
|
— | Not reported | — | NAR, SAR | — |
| PSS010101 | — | — | [ ,
0.0 % Male samples |
— | South Asian | — | BiB, START | 70% validation set from each cohort |
| PSS011328 | — | — | 133,830 individuals, 0.0 % Male samples |
— | European (British) |
— | UKB | — |
| PSS011329 | — | — | 115,207 individuals, 100.0 % Male samples |
— | European (British) |
— | UKB | — |
| PSS000524 | — | — | [ ,
0.0 % Male samples |
— | European | — | 59 cohorts
|
— |
| PSS000528 | — | — | [ ,
0.0 % Male samples |
— | European | — | 59 cohorts
|
— |
| PSS000530 | To assess associationss between the PRS and ovarian cancer risk, eligibility was restricted to women who had not been diagnosed with ovarian cancer and had not had RRSO at the time of baselinne questionnaire completion. Carriers diagnosed with invasive ovarian, fallopian tube, or peritoneal cancer during the follow-up were considered affected. | — | [ ,
0.0 % Male samples |
— | European | — | 61 cohorts
|
— |
| PSS000532 | To assess associationss between the PRS and ovarian cancer risk, eligibility was restricted to women who had not been diagnosed with ovarian cancer and had not had RRSO at the time of baseline questionnaire completion. Carriers diagnosed with invasive ovarian, fallopian tbe, or peritoneal cancer during the follow-up were considered affected. | — | [ ,
0.0 % Male samples |
— | European | — | 61 cohorts
|
— |
| PSS010136 | — | — | [
|
— | European | — | UKB | — |
| PSS011360 | — | — | 2,676 individuals, 32.47 % Male samples |
Mean = 54.0 years Sd = 11.8 years |
East Asian (Chinese) |
— | WHZH | — |
| PSS010149 | — | — | [ ,
0.0 % Male samples |
— | European | — | UKB | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS010154 | — | — | [
|
— | European | — | UKB | — |
| PSS010157 | — | — | [
|
Mean = 42.3 years | Hispanic or Latin American (Mexican) |
— | METSB | — |
| PSS009053 | — | — | 4,120 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009058 | — | — | 3,930 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009059 | — | — | 3,938 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009060 | — | — | 4,100 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009061 | — | — | 3,954 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009062 | — | — | 4,121 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011395 | — | Mean = 8.1 years | 357,419 individuals | — | European (White British) |
— | UKB | — |
| PSS011407 | — | Mean = 6.8 years IQR = [6.3, 7.3] years |
[ ,
44.0 % Male samples |
Mean = 61.1 years Sd = 7.8 years |
European, Not reported | White European (97.1%) | UKB | — |
| PSS009109 | — | — | 4,060 individuals | — | European | Poland (NE Europe) | UKB | — |