| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0006336 |
| Description | The blood pressure after the contraction of the heart while the chambers of the heart refill with blood. | Trait category |
Other measurement
|
| Synonyms |
2 synonyms
|
| Mapped terms |
3 mapped terms
|
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | Ancestry distribution | Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000302 (GRS962_DBP) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Diastolic blood pressure | diastolic blood pressure | 962 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000302/ScoringFiles/PGS000302.txt.gz |
| PGS000912 (ukb_dbp_prs) |
PGP000240 | Vaura F et al. Hypertension (2021) |
Diastolic blood pressure | diastolic blood pressure | 1,098,015 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000912/ScoringFiles/PGS000912.txt.gz |
| PGS001133 (GBE_INI4079) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Diastolic BP (AR) | diastolic blood pressure | 14,103 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001133/ScoringFiles/PGS001133.txt.gz |
| PGS001900 (portability-PLR_diastolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diastolic blood pressure, automated reading | diastolic blood pressure | 66,335 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001900/ScoringFiles/PGS001900.txt.gz |
| PGS002114 (portability-ldpred2_diastolic_BP) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diastolic blood pressure, automated reading | diastolic blood pressure | 933,950 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002114/ScoringFiles/PGS002114.txt.gz |
| PGS002239 (DBP_PRS) |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 1,119,054 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002239/ScoringFiles/PGS002239.txt.gz | |
| PGS002258 (GRS901_DBP) |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Diastolic blood pressure | diastolic blood pressure | 885 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002258/ScoringFiles/PGS002258.txt.gz |
| PGS002322 (bp_DIASTOLICadjMEDz.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002322/ScoringFiles/PGS002322.txt.gz |
| PGS002362 (bp_DIASTOLICadjMEDz.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 920,925 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002362/ScoringFiles/PGS002362.txt.gz |
| PGS002394 (bp_DIASTOLICadjMEDz.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 11,460 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002394/ScoringFiles/PGS002394.txt.gz |
| PGS002443 (bp_DIASTOLICadjMEDz.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 31,790 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002443/ScoringFiles/PGS002443.txt.gz |
| PGS002492 (bp_DIASTOLICadjMEDz.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 137,641 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002492/ScoringFiles/PGS002492.txt.gz |
| PGS002541 (bp_DIASTOLICadjMEDz.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 3,531 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002541/ScoringFiles/PGS002541.txt.gz |
| PGS002590 (bp_DIASTOLICadjMEDz.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 2,090 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002590/ScoringFiles/PGS002590.txt.gz |
| PGS002639 (bp_DIASTOLICadjMEDz.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 539,912 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002639/ScoringFiles/PGS002639.txt.gz |
| PGS002688 (bp_DIASTOLICadjMEDz.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diastolic blood pressure | diastolic blood pressure | 985,844 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002688/ScoringFiles/PGS002688.txt.gz |
| PGS002889 (ExPRSweb_DBP_4079-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 755,822 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002889/ScoringFiles/PGS002889.txt.gz | |
| PGS002890 (ExPRSweb_DBP_4079-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 24,016 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002890/ScoringFiles/PGS002890.txt.gz | |
| PGS002891 (ExPRSweb_DBP_4079-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 40,911 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002891/ScoringFiles/PGS002891.txt.gz | |
| PGS002892 (ExPRSweb_DBP_4079-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 7,477,069 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002892/ScoringFiles/PGS002892.txt.gz | |
| PGS002893 (ExPRSweb_DBP_4079-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 1,113,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002893/ScoringFiles/PGS002893.txt.gz | |
| PGS002894 (ExPRSweb_DBP_4079-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 749,859 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002894/ScoringFiles/PGS002894.txt.gz | |
| PGS002895 (ExPRSweb_DBP_4079-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 15,687 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002895/ScoringFiles/PGS002895.txt.gz | |
| PGS002896 (ExPRSweb_DBP_4079-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 24,976 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002896/ScoringFiles/PGS002896.txt.gz | |
| PGS002897 (ExPRSweb_DBP_4079-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 7,259,551 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002897/ScoringFiles/PGS002897.txt.gz | |
| PGS002898 (ExPRSweb_DBP_4079-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 1,113,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002898/ScoringFiles/PGS002898.txt.gz | |
| PGS002899 (ExPRSweb_DBP_94-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 353,663 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002899/ScoringFiles/PGS002899.txt.gz | |
| PGS002900 (ExPRSweb_DBP_94-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 13,289 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002900/ScoringFiles/PGS002900.txt.gz | |
| PGS002901 (ExPRSweb_DBP_94-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 27,506 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002901/ScoringFiles/PGS002901.txt.gz | |
| PGS002902 (ExPRSweb_DBP_94-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 7,218,263 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002902/ScoringFiles/PGS002902.txt.gz | |
| PGS002903 (ExPRSweb_DBP_94-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 1,113,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002903/ScoringFiles/PGS002903.txt.gz | |
| PGS002904 (ExPRSweb_DBP_94-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 353,446 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002904/ScoringFiles/PGS002904.txt.gz | |
| PGS002905 (ExPRSweb_DBP_94-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 10,968 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002905/ScoringFiles/PGS002905.txt.gz | |
| PGS002906 (ExPRSweb_DBP_94-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 22,461 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002906/ScoringFiles/PGS002906.txt.gz | |
| PGS002907 (ExPRSweb_DBP_94-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 6,683,891 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002907/ScoringFiles/PGS002907.txt.gz | |
| PGS002908 (ExPRSweb_DBP_94-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Diastolic Blood Pressure | diastolic blood pressure | 1,113,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002908/ScoringFiles/PGS002908.txt.gz | |
| PGS003463 (LDPred2_DBP) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Diastolic blood pressure | diastolic blood pressure | 848,440 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003463/ScoringFiles/PGS003463.txt.gz |
| PGS003498 (cont-decay-diastolic_BP) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Diastolic blood pressure, automated reading | diastolic blood pressure | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003498/ScoringFiles/PGS003498.txt.gz |
| PGS003883 (DBP_lassosum2_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Diastolic blood pressure | diastolic blood pressure | 25,857 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003883/ScoringFiles/PGS003883.txt.gz |
| PGS003961 (DBP_AFR) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Diastolic blood pressure | diastolic blood pressure | 1,221,464 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003961/ScoringFiles/PGS003961.txt.gz |
| PGS003962 (DBP_EAS) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Diastolic blood pressure | diastolic blood pressure | 978,280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003962/ScoringFiles/PGS003962.txt.gz |
| PGS003963 (DBP_EUR) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Diastolic blood pressure | diastolic blood pressure | 1,110,130 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003963/ScoringFiles/PGS003963.txt.gz |
| PGS003964 (DBP_weightedPRSsum) |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Diastolic blood pressure | diastolic blood pressure | 1,267,600 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003964/ScoringFiles/PGS003964.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000772 | PGS000302 (GRS962_DBP) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Diastolic blood pressure (mmHg) | — | — | R²: 0.0448 | Sex, age, age^2, BMI | — |
| PPM000802 | PGS000302 (GRS962_DBP) |
PSS000371| European Ancestry| 288 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Diastolic blood pressure (mmHg) | — | — | R²: 0.0088 | Sex, age, age^2, BMI | — |
| PPM002972 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | HR: 1.41 [1.4, 1.42] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.26 [2.17, 2.36] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002974 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Late onset incident hypertension (≥55 years) | HR: 1.26 [1.25, 1.28] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 1.6 [1.48, 1.73] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM002976 | PGS000912 (ukb_dbp_prs) |
PSS001450| European Ancestry| 9,906 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Incident hypertension | — | C-index: 0.803 | — | Age, sex, systolic blood pressure, diastolic blood pressure, body mass index, diabetes, current smoking | — |
| PPM002973 | PGS000912 (ukb_dbp_prs) |
PSS001446| European Ancestry| 218,754 individuals |
PGP000240 | Vaura F et al. Hypertension (2021) |
Reported Trait: Early onset incident hypertension (< 55 years) | HR: 1.58 [1.56, 1.6] | — | Hazard Ratio (HR, top 2.5% vs middle 60%): 2.78 [2.64, 2.93] | Sex, collection year, genotyping batch, PCs(1-10) | — |
| PPM008393 | PGS001133 (GBE_INI4079) |
PSS007261| African Ancestry| 6,409 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.00961 [0.00489, 0.01433] Incremental R2 (full-covars): 0.004 PGS R2 (no covariates): 0.00541 [0.00186, 0.00897] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008394 | PGS001133 (GBE_INI4079) |
PSS007262| East Asian Ancestry| 1,634 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.10887 [0.081, 0.13673] Incremental R2 (full-covars): 0.03804 PGS R2 (no covariates): 0.04085 [0.02248, 0.05923] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008395 | PGS001133 (GBE_INI4079) |
PSS007263| European Ancestry| 23,727 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.08484 [0.07822, 0.09146] Incremental R2 (full-covars): 0.04531 PGS R2 (no covariates): 0.04978 [0.04451, 0.05504] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008396 | PGS001133 (GBE_INI4079) |
PSS007264| South Asian Ancestry| 7,640 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.03516 [0.02715, 0.04317] Incremental R2 (full-covars): 0.02383 PGS R2 (no covariates): 0.02615 [0.01918, 0.03312] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008397 | PGS001133 (GBE_INI4079) |
PSS007265| European Ancestry| 63,825 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diastolic BP (AR) | — | — | R²: 0.07507 [0.07124, 0.07889] Incremental R2 (full-covars): 0.04511 PGS R2 (no covariates): 0.04581 [0.04273, 0.04889] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010083 | PGS001900 (portability-PLR_diastolic_BP) |
PSS009397| European Ancestry| 18,718 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2491 [0.2356, 0.2625] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010084 | PGS001900 (portability-PLR_diastolic_BP) |
PSS009171| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2605 [0.231, 0.2895] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010085 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008725| European Ancestry| 6,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2168 [0.1932, 0.2402] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010086 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008499| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1801 [0.1231, 0.2359] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010087 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008277| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1863 [0.162, 0.2105] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010088 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008054| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2437 [0.1985, 0.288] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010090 | PGS001900 (portability-PLR_diastolic_BP) |
PSS008945| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0834 [0.0519, 0.1148] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010089 | PGS001900 (portability-PLR_diastolic_BP) |
PSS007841| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1048 [0.0652, 0.144] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011767 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS009397| European Ancestry| 18,718 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2531 [0.2397, 0.2665] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011768 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS009171| European Ancestry| 3,930 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2679 [0.2385, 0.2967] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011769 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008725| European Ancestry| 6,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2221 [0.1986, 0.2455] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011770 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008499| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1869 [0.1301, 0.2426] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011771 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008277| South Asian Ancestry| 6,098 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1939 [0.1695, 0.2179] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011772 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008054| East Asian Ancestry| 1,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.2244 [0.1788, 0.2691] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011773 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS007841| African Ancestry| 2,438 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.1014 [0.0618, 0.1407] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011774 | PGS002114 (portability-ldpred2_diastolic_BP) |
PSS008945| African Ancestry| 3,850 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic blood pressure, automated reading | — | — | Partial Correlation (partial-r): 0.0818 [0.0502, 0.1131] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012728 | PGS002239 (DBP_PRS) |
PSS009510| Ancestry Not Reported| 4,407 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.06 [1.01, 1.11] | AUROC: 0.681 [0.669, 0.686] | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012726 | PGS002239 (DBP_PRS) |
PSS009511| African Ancestry| 10,052 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.04 [0.94, 1.16] | AUROC: 0.663 [0.644, 0.688] | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012727 | PGS002239 (DBP_PRS) |
PSS009512| European Ancestry| 57,090 individuals |
PGP000270 | Breeyear JH et al. Circ Genom Precis Med (2022) |
Reported Trait: Apparent Treatment-Resistant Hypertension | OR: 1.05 [1.01, 1.11] | AUROC: 0.679 | — | age, age^2, bmi, sex, top 10 principal components of ancestry | — |
| PPM012847 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.06 [1.79, 2.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012848 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.64 [1.46, 1.81] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012849 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.42 [0.25, 0.58] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012850 | PGS002258 (GRS901_DBP) |
PSS009574| European Ancestry| 14,004 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.27 [1.23, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012851 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.38 [1.85, 2.9] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012852 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.39 [1.09, 1.7] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012853 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 0.99 [0.65, 1.32] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012854 | PGS002258 (GRS901_DBP) |
PSS009575| African Ancestry| 6,970 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.26 [1.2, 1.33] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012855 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Systolic blood pressure | β: 2.58 [2.13, 3.03] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012856 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Diastolic blood pressure | β: 1.49 [1.25, 1.74] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012857 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Pulse pressure | β: 1.09 [0.8, 1.39] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM012858 | PGS002258 (GRS901_DBP) |
PSS009576| South Asian Ancestry| 8,827 individuals |
PGP000283 | Evangelou E et al. Nat Genet (2018) |
Reported Trait: Hypertension | OR: 1.3 [1.24, 1.36] | — | — | — | *Note performance is based on the average between GRS901_SBP and GRS_901_DBP |
| PPM013004 | PGS002258 (GRS901_DBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Systolic blood pressure | β: 1.93 | — | — | PGS002257, age, age^2, sex, BMI, randomization arm, history of CVD event, serum creatinine, fasting blood glucose, LDL levels, 10 genetic PCs | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM013005 | PGS002258 (GRS901_DBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Diastolic blood pressure | β: 0.65 | — | — | PGS002257, age, age^2, sex, BMI, randomization arm, history of CVD event, serum creatinine, fasting blood glucose, LDL levels, 10 genetic PCs | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM013006 | PGS002258 (GRS901_DBP) |
PSS009643| Ancestry Not Reported| 6,335 individuals |
PGP000317 | Parcha V et al. Hypertension (2022) |Ext. |
Reported Trait: Adverse cardiovascular events | HR: 1.12 [1.02, 1.23] | — | — | PGS002257 | *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258 |
| PPM015499 | PGS002258 (GRS901_DBP) |
PSS009963| European Ancestry| 33,770 individuals |
PGP000376 | Åberg F et al. Sci Rep (2022) |Ext. |
Reported Trait: Liver-related outcome | HR: 1.12 [1.01, 1.25] | — | — | Age, sex, body mass index, waist circumference, weekly alcohol use, fraction of alcohol use as wine, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, diabetes, exercise habits, smoking status (current, former, never smoker) and baseline cardiovascular disease | — |
| PPM013087 | PGS002322 (bp_DIASTOLICadjMEDz.BOLT-LMM) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0175 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013185 | PGS002322 (bp_DIASTOLICadjMEDz.BOLT-LMM) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.1101 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013234 | PGS002322 (bp_DIASTOLICadjMEDz.BOLT-LMM) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0588 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013136 | PGS002322 (bp_DIASTOLICadjMEDz.BOLT-LMM) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0793 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013297 | PGS002362 (bp_DIASTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.027 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013274 | PGS002362 (bp_DIASTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013343 | PGS002362 (bp_DIASTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013320 | PGS002362 (bp_DIASTOLICadjMEDz.BOLT-LMM-BBJ) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0012 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013375 | PGS002394 (bp_DIASTOLICadjMEDz.P+T.0.0001) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0044 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013424 | PGS002394 (bp_DIASTOLICadjMEDz.P+T.0.0001) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.04 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013473 | PGS002394 (bp_DIASTOLICadjMEDz.P+T.0.0001) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0506 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013522 | PGS002394 (bp_DIASTOLICadjMEDz.P+T.0.0001) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0259 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013669 | PGS002443 (bp_DIASTOLICadjMEDz.P+T.0.001) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0527 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013571 | PGS002443 (bp_DIASTOLICadjMEDz.P+T.0.001) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013620 | PGS002443 (bp_DIASTOLICadjMEDz.P+T.0.001) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0106 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013718 | PGS002443 (bp_DIASTOLICadjMEDz.P+T.0.001) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0122 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013767 | PGS002492 (bp_DIASTOLICadjMEDz.P+T.0.01) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013816 | PGS002492 (bp_DIASTOLICadjMEDz.P+T.0.01) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013865 | PGS002492 (bp_DIASTOLICadjMEDz.P+T.0.01) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0205 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013914 | PGS002492 (bp_DIASTOLICadjMEDz.P+T.0.01) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0036 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013963 | PGS002541 (bp_DIASTOLICadjMEDz.P+T.1e-06) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0081 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014012 | PGS002541 (bp_DIASTOLICadjMEDz.P+T.1e-06) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0375 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014061 | PGS002541 (bp_DIASTOLICadjMEDz.P+T.1e-06) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0365 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014110 | PGS002541 (bp_DIASTOLICadjMEDz.P+T.1e-06) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0189 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014306 | PGS002590 (bp_DIASTOLICadjMEDz.P+T.5e-08) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0174 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014159 | PGS002590 (bp_DIASTOLICadjMEDz.P+T.5e-08) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0078 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014257 | PGS002590 (bp_DIASTOLICadjMEDz.P+T.5e-08) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0305 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014208 | PGS002590 (bp_DIASTOLICadjMEDz.P+T.5e-08) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0289 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014355 | PGS002639 (bp_DIASTOLICadjMEDz.PolyFun-pred) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.023 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_DIASTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014404 | PGS002639 (bp_DIASTOLICadjMEDz.PolyFun-pred) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0907 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_DIASTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014453 | PGS002639 (bp_DIASTOLICadjMEDz.PolyFun-pred) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1136 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_DIASTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014502 | PGS002639 (bp_DIASTOLICadjMEDz.PolyFun-pred) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0588 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See bp_DIASTOLICadjMEDz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014600 | PGS002688 (bp_DIASTOLICadjMEDz.SBayesR) |
PSS009732| East Asian Ancestry| 859 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.089 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014551 | PGS002688 (bp_DIASTOLICadjMEDz.SBayesR) |
PSS009731| African Ancestry| 6,128 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0195 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014649 | PGS002688 (bp_DIASTOLICadjMEDz.SBayesR) |
PSS009733| European Ancestry| 40,059 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.1072 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014698 | PGS002688 (bp_DIASTOLICadjMEDz.SBayesR) |
PSS009734| South Asian Ancestry| 7,573 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diastolic blood pressure | — | — | Incremental R2 (full model vs. covariates alone): 0.0596 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM015768 | PGS002889 (ExPRSweb_DBP_4079-irnt_LASSOSUM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.21 (0.0464) | — | R²: 0.026 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015771 | PGS002890 (ExPRSweb_DBP_4079-irnt_PT_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.11 (0.0477) | — | R²: 0.0197 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015769 | PGS002891 (ExPRSweb_DBP_4079-irnt_PLINK_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.09 (0.0487) | — | R²: 0.0174 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015767 | PGS002892 (ExPRSweb_DBP_4079-irnt_DBSLMM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.06 (0.0468) | — | R²: 0.0196 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015770 | PGS002893 (ExPRSweb_DBP_4079-irnt_PRSCS_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.33 (0.0478) | — | R²: 0.0275 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015773 | PGS002894 (ExPRSweb_DBP_4079-raw_LASSOSUM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.23 (0.0468) | — | R²: 0.0264 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015776 | PGS002895 (ExPRSweb_DBP_4079-raw_PT_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.14 (0.048) | — | R²: 0.0202 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015774 | PGS002896 (ExPRSweb_DBP_4079-raw_PLINK_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.09 (0.0488) | — | R²: 0.0176 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015772 | PGS002897 (ExPRSweb_DBP_4079-raw_DBSLMM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.05 (0.0468) | — | R²: 0.0191 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015775 | PGS002898 (ExPRSweb_DBP_4079-raw_PRSCS_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 1.33 (0.0479) | — | R²: 0.0276 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015778 | PGS002899 (ExPRSweb_DBP_94-irnt_LASSOSUM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.327 (0.0456) | — | R²: 0.00237 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015781 | PGS002900 (ExPRSweb_DBP_94-irnt_PT_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.254 (0.0451) | — | R²: 0.00138 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015779 | PGS002901 (ExPRSweb_DBP_94-irnt_PLINK_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.267 (0.0452) | — | R²: 0.00171 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015777 | PGS002902 (ExPRSweb_DBP_94-irnt_DBSLMM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.218 (0.0451) | — | R²: 0.00094 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015780 | PGS002903 (ExPRSweb_DBP_94-irnt_PRSCS_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.46 (0.0457) | — | R²: 0.00439 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015783 | PGS002904 (ExPRSweb_DBP_94-raw_LASSOSUM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.319 (0.0456) | — | R²: 0.00228 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015786 | PGS002905 (ExPRSweb_DBP_94-raw_PT_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.26 (0.0452) | — | R²: 0.00144 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015784 | PGS002906 (ExPRSweb_DBP_94-raw_PLINK_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.273 (0.0452) | — | R²: 0.00178 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015782 | PGS002907 (ExPRSweb_DBP_94-raw_DBSLMM_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.142 (0.0458) | — | R²: 0.00032 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015785 | PGS002908 (ExPRSweb_DBP_94-raw_PRSCS_MGI_20211120) |
PSS010001| European Ancestry| 23,074 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Diastolic Blood Pressure | β: 0.442 (0.0456) | — | R²: 0.00414 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM017273 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Respiratory event index | β: 0.02 (0.01) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017342 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Respiratory event index in obsese | β: 0.034 (0.017) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017343 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Respiratory event index in non-obsese | β: 0.015 (0.012) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017362 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Obstructive sleep apnea in obsese | β: 0.103 (0.034) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017363 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Obstructive sleep apnea in non-obsese | β: 0.016 (0.035) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017393 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Respiratory event index x obesity interaction | β: 0.009 (1.009) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017296 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Obstructive sleep apnea | β: 0.056 (0.024) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017403 | PGS003463 (LDPred2_DBP) |
PSS010185| Hispanic or Latin American Ancestry| 1,115 individuals |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Reported Trait: Obstructive sleep apnea x obesity interaction | β: 1.066 (0.05) | — | — | Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI | — |
| PPM017426 | PGS003498 (cont-decay-diastolic_BP) |
PSS010942| European Ancestry| 18,679 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.06 | sex, age, deprivation index, PC1-16 | — |
| PPM017510 | PGS003498 (cont-decay-diastolic_BP) |
PSS010858| European Ancestry| 3,920 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
| PPM017594 | PGS003498 (cont-decay-diastolic_BP) |
PSS010690| European Ancestry| 6,182 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM017678 | PGS003498 (cont-decay-diastolic_BP) |
PSS010606| Greater Middle Eastern Ancestry| 1,122 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
| PPM017762 | PGS003498 (cont-decay-diastolic_BP) |
PSS010270| European Ancestry| 2,194 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM017846 | PGS003498 (cont-decay-diastolic_BP) |
PSS010522| South Asian Ancestry| 6,050 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
| PPM017930 | PGS003498 (cont-decay-diastolic_BP) |
PSS010438| East Asian Ancestry| 1,709 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.05 | sex, age, deprivation index, PC1-16 | — |
| PPM018014 | PGS003498 (cont-decay-diastolic_BP) |
PSS010354| African Ancestry| 2,424 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.01 | sex, age, deprivation index, PC1-16 | — |
| PPM018098 | PGS003498 (cont-decay-diastolic_BP) |
PSS010774| African Ancestry| 3,819 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Diastolic blood pressure, automated reading | — | — | partial-R2: 0.01 | sex, age, deprivation index, PC1-16 | — |
| PPM018775 | PGS003883 (DBP_lassosum2_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Diastolic blood pressure | β: 1.8 (0.26) | — | R²: 0.0397 | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM019122 | PGS003964 (DBP_weightedPRSsum) |
PSS011189| Multi-ancestry (including European)| 88,521 individuals |
PGP000510 | Kurniansyah N et al. Nat Commun (2023) |
Reported Trait: Diastolic blood pressure | β: 2.41 [2.31, 2.5] | — | — | age, sex at birth, BMI, self-reported race/ethnicity, and the first 10 PCs of genetic data | best performing DBP PRSs as selected in the TOPMed dataset (PRS-CSx2) |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS009511 | Apparent Treatment-Resistant Hypertension | — | [ ,
37.0 % Male samples |
Mean = 50.6 years | African American or Afro-Caribbean | African American, Non-Hispanic Black | BioVU | — |
| PSS009511 | Apparent Treatment-Resistant Hypertension | — | [ ,
37.0 % Male samples |
Mean = 50.6 years | African American or Afro-Caribbean | African American, Non-Hispanic Black | BioVU | Multi-Ancestry analysis |
| PSS009512 | Apparent Treatment-Resistant Hypertension | — | [ ,
46.0 % Male samples |
Mean = 58.58 years | European | European, Non-Hispanic White | BioVU | — |
| PSS009512 | Apparent Treatment-Resistant Hypertension | — | [ ,
46.0 % Male samples |
Mean = 58.58 years | European | European, Non-Hispanic White | BioVU | Multi-Ancestry analysis |
| PSS010270 | — | — | 2,194 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
| PSS009171 | — | — | 3,930 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS008277 | — | — | 6,098 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009963 | — | Median = 12.9 years | 33,770 individuals, 46.5 % Male samples |
Mean = 49.6 years | European (Finnish) |
Finland | FINRISK, Health2000 | — |
| PSS010942 | — | — | 18,679 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
| PSS007261 | — | — | 6,409 individuals | — | African unspecified | — | UKB | — |
| PSS007262 | — | — | 1,634 individuals | — | East Asian | — | UKB | — |
| PSS007263 | — | — | 23,727 individuals | — | European | non-white British ancestry | UKB | — |
| PSS007264 | — | — | 7,640 individuals | — | South Asian | — | UKB | — |
| PSS007265 | — | — | 63,825 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS010690 | — | — | 6,182 individuals, 45.0 % Male samples |
Mean = 54.5 years Sd = 8.4 years |
European | Italian | UKB | — |
| PSS010438 | — | — | 1,709 individuals, 33.0 % Male samples |
Mean = 52.5 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
| PSS008945 | — | — | 3,850 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS000371 | Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 288 individuals, 69.2 % Male samples |
Mean = 15.83 years Sd = 0.6 years |
European | — | TRAILS, TRAILSCC | TRAILS Clinical Cohort |
| PSS010001 | Diastolic Blood Pressure; Quantitative | — | 23,074 individuals | — | European | — | MGI | — |
| PSS008054 | — | — | 1,719 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS000376 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,354 individuals, 47.56 % Male samples |
Mean = 16.22 years Sd = 0.66 years |
European | — | TRAILS | — |
| PSS010185 | — | — | 1,115 individuals, 41.1 % Male samples |
Mean = 46.18 years | Hispanic or Latin American | — | HCHS, SOL | — |
| PSS001450 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). | — | [
|
— | European (Finnish) |
— | FINRISK | — |
| PSS009643 | Corrected for baseline antihypertensive use | — | 6,335 individuals, 62.7 % Male samples |
Median = 62.1 years Sd = [57.8, 67.1] years |
Not reported | 30.4% non-White individuals | ACCORD | — |
| PSS010858 | — | — | 3,920 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
| PSS010606 | — | — | 1,122 individuals, 60.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
| PSS008725 | — | — | 6,338 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS010354 | — | — | 2,424 individuals, 36.0 % Male samples |
Mean = 52.5 years Sd = 8.1 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
| PSS007841 | — | — | 2,438 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011189 | — | — | 19,441 individuals, 44.7 % Male samples |
Mean = 47.36 years Sd = 14.8 years |
African unspecified | — | AllofUs | — |
| PSS011189 | — | — | 2,891 individuals, 40.3 % Male samples |
Mean = 42.96 years Sd = 16.67 years |
Asian unspecified | — | AllofUs | — |
| PSS011189 | — | — | 48,155 individuals, 40.4 % Male samples |
Mean = 53.65 years Sd = 16.61 years |
European | — | AllofUs | — |
| PSS011189 | — | — | 18,034 individuals, 31.9 % Male samples |
Mean = 44.27 years Sd = 15.79 years |
Hispanic or Latin American | — | AllofUs | — |
| PSS010774 | — | — | 3,819 individuals, 46.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
| PSS009574 | — | — | 14,004 individuals | — | European | — | Airwave | — |
| PSS009575 | — | — | 6,970 individuals | — | African unspecified | — | UKB | — |
| PSS008499 | — | — | 1,151 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009576 | — | — | 8,827 individuals | — | South Asian | — | UKB | — |
| PSS009397 | — | — | 18,718 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009731 | — | — | 6,128 individuals | — | African unspecified | — | UKB | — |
| PSS009732 | — | — | 859 individuals | — | East Asian | — | UKB | — |
| PSS009733 | — | — | 40,059 individuals | — | European | Non-British European | UKB | — |
| PSS009734 | — | — | 7,573 individuals | — | South Asian | — | UKB | — |
| PSS001446 | Cases were individuals with incident hypertension. Hypertension was defined as persistently high systemic arterial blood pressure based on multiple blood pressure readings (consistent systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) or medical expenses reimbursement history. Diagnoses were based on the International Classification of Diseases (ICD) 8 codes (I1[0-3]/I15/I674) , ICD-9 codes (I1[0-3]/I15/I674), and ICD-10 codes (I1[0-3]/I15/I674). Of the 55,917 cases, 27,361 had early-onset incident hypertension, whilst 28,556 had late-onset incident hypertension. Early-onset and late-onset hypertension were defined as age of onset <55 and ≥55 years, respectively. | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS010522 | — | — | 6,050 individuals, 54.0 % Male samples |
Mean = 53.4 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
| PSS009510 | Apparent Treatment-Resistant Hypertension | — | [
|
— | Not reported | — | BioVU | Multi-Ancestry analysis |