Trait: diastolic blood pressure

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
Cardiovascular measurement
Synonyms 2 synonyms
  • DIABP
  • diastolic pressure
Mapped terms 3 mapped terms
  • MedDRA:10012751
  • NCIt:C25299
  • SNOMEDCT:271650006

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported
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)
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 |
Privรฉ 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 |
Privรฉ 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
PGS004232
(PRS732_DBP)
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Diastolic blood pressure diastolic blood pressure 732
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004232/ScoringFiles/PGS004232.txt.gz
PGS004233
(DBP_MVP)
 PGP000531 |
Kurniansyah N et al. Nat Commun (2022)
 Diastolic blood pressure diastolic blood pressure 149,559
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004233/ScoringFiles/PGS004233.txt.gz
PGS004371
(X4079.score)
 PGP000561 |
Jung H et al. Commun Biol (2024)
 Diastolic blood pressure, automated reading diastolic blood pressure 1,059,939
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004371/ScoringFiles/PGS004371.txt.gz
PGS004604
(DBP-meta-analysis)
 PGP000581 |
Keaton JM et al. Nat Genet (2024)
 Diastolic blood pressure diastolic blood pressure 7,356,519
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004604/ScoringFiles/PGS004604.txt.gz
PGS004755
(dbp_PRSmix_eur)
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Diastolic blood pressure diastolic blood pressure 1,172,953
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004755/ScoringFiles/PGS004755.txt.gz
PGS004756
(dbp_PRSmix_sas)
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Diastolic blood pressure diastolic blood pressure 2,906,802
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004756/ScoringFiles/PGS004756.txt.gz
PGS004757
(dbp_PRSmixPlus_eur)
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Diastolic blood pressure diastolic blood pressure 4,215,048
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004757/ScoringFiles/PGS004757.txt.gz
PGS004758
(dbp_PRSmixPlus_sas)
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Diastolic blood pressure diastolic blood pressure 4,139,034
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004758/ScoringFiles/PGS004758.txt.gz

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

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) โ€” โ€” Rยฒ: 0.0448 Sex, age, age^2, BMI โ€”
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) โ€” โ€” Rยฒ: 0.0088 Sex, age, age^2, BMI โ€”
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] โ€” Hazard Ratio (HR, top 2.5% vs middle 60%): 2.26 [2.17, 2.36] Sex, collection year, genotyping batch, PCs(1-10) โ€”
PPM002974 PGS000912
(ukb_dbp_prs)
 PSS001446|
European Ancestry|
218,754 individuals
 PGP000240 |
Vaura F et al. Hypertension (2021)
 Reported Trait: Late onset incident hypertension (โ‰ฅ55 years) HR: 1.26 [1.25, 1.28] โ€” Hazard Ratio (HR, top 2.5% vs middle 60%): 1.6 [1.48, 1.73] Sex, collection year, genotyping batch, PCs(1-10) โ€”
PPM002976 PGS000912
(ukb_dbp_prs)
 PSS001450|
European Ancestry|
9,906 individuals
 PGP000240 |
Vaura F et al. Hypertension (2021)
 Reported Trait: Incident hypertension โ€” C-index: 0.803 โ€” Age, sex, systolic blood pressure, diastolic blood pressure, body mass index, diabetes, current smoking โ€”
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] โ€” Hazard Ratio (HR, top 2.5% vs middle 60%): 2.78 [2.64, 2.93] Sex, collection year, genotyping batch, PCs(1-10) โ€”
PPM008393 PGS001133
(GBE_INI4079)
 PSS007261|
African Ancestry|
6,409 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Diastolic BP (AR) โ€” โ€” Rยฒ: 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 โ€”
PPM008394 PGS001133
(GBE_INI4079)
 PSS007262|
East Asian Ancestry|
1,634 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Diastolic BP (AR) โ€” โ€” Rยฒ: 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 โ€”
PPM008395 PGS001133
(GBE_INI4079)
 PSS007263|
European Ancestry|
23,727 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Diastolic BP (AR) โ€” โ€” Rยฒ: 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 โ€”
PPM008396 PGS001133
(GBE_INI4079)
 PSS007264|
South Asian Ancestry|
7,640 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Diastolic BP (AR) โ€” โ€” Rยฒ: 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 โ€”
PPM008397 PGS001133
(GBE_INI4079)
 PSS007265|
European Ancestry|
63,825 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Diastolic BP (AR) โ€” โ€” Rยฒ: 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 โ€”
PPM010083 PGS001900
(portability-PLR_diastolic_BP)
 PSS009397|
European Ancestry|
18,718 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2491 [0.2356, 0.2625] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010084 PGS001900
(portability-PLR_diastolic_BP)
 PSS009171|
European Ancestry|
3,930 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2605 [0.231, 0.2895] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010085 PGS001900
(portability-PLR_diastolic_BP)
 PSS008725|
European Ancestry|
6,338 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2168 [0.1932, 0.2402] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010086 PGS001900
(portability-PLR_diastolic_BP)
 PSS008499|
Greater Middle Eastern Ancestry|
1,151 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1801 [0.1231, 0.2359] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010087 PGS001900
(portability-PLR_diastolic_BP)
 PSS008277|
South Asian Ancestry|
6,098 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1863 [0.162, 0.2105] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010088 PGS001900
(portability-PLR_diastolic_BP)
 PSS008054|
East Asian Ancestry|
1,719 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2437 [0.1985, 0.288] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010090 PGS001900
(portability-PLR_diastolic_BP)
 PSS008945|
African Ancestry|
3,850 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.0834 [0.0519, 0.1148] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM010089 PGS001900
(portability-PLR_diastolic_BP)
 PSS007841|
African Ancestry|
2,438 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1048 [0.0652, 0.144] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011767 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS009397|
European Ancestry|
18,718 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2531 [0.2397, 0.2665] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011768 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS009171|
European Ancestry|
3,930 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2679 [0.2385, 0.2967] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011769 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS008725|
European Ancestry|
6,338 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2221 [0.1986, 0.2455] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011770 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS008499|
Greater Middle Eastern Ancestry|
1,151 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1869 [0.1301, 0.2426] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011771 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS008277|
South Asian Ancestry|
6,098 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1939 [0.1695, 0.2179] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011772 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS008054|
East Asian Ancestry|
1,719 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.2244 [0.1788, 0.2691] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011773 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS007841|
African Ancestry|
2,438 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.1014 [0.0618, 0.1407] sex, age, birth date, deprivation index, 16 PCs โ€”
PPM011774 PGS002114
(portability-ldpred2_diastolic_BP)
 PSS008945|
African Ancestry|
3,850 individuals
 PGP000263 |
Privรฉ F et al. Am J Hum Genet (2022)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” Partial Correlation (partial-r): 0.0818 [0.0502, 0.1131] sex, age, birth date, deprivation index, 16 PCs โ€”
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] โ€” age, age^2, bmi, sex, top 10 principal components of ancestry โ€”
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] โ€” age, age^2, bmi, sex, top 10 principal components of ancestry โ€”
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 โ€” age, age^2, bmi, sex, top 10 principal components of ancestry โ€”
PPM012847 PGS002258
(GRS901_DBP)
 PSS009574|
European Ancestry|
14,004 individuals
 PGP000283 |
Evangelou E et al. Nat Genet (2018)
 Reported Trait: Systolic blood pressure ฮฒ: 2.06 [1.79, 2.32] โ€” โ€” โ€” *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 ฮฒ: 1.64 [1.46, 1.81] โ€” โ€” โ€” *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 ฮฒ: 0.42 [0.25, 0.58] โ€” โ€” โ€” *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] โ€” โ€” โ€” *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 ฮฒ: 2.38 [1.85, 2.9] โ€” โ€” โ€” *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 ฮฒ: 1.39 [1.09, 1.7] โ€” โ€” โ€” *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 ฮฒ: 0.99 [0.65, 1.32] โ€” โ€” โ€” *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] โ€” โ€” โ€” *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 ฮฒ: 2.58 [2.13, 3.03] โ€” โ€” โ€” *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 ฮฒ: 1.49 [1.25, 1.74] โ€” โ€” โ€” *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 ฮฒ: 1.09 [0.8, 1.39] โ€” โ€” โ€” *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] โ€” โ€” โ€” *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 ฮฒ: 1.93 โ€” โ€” 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 ฮฒ: 0.65 โ€” โ€” 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] โ€” โ€” PGS002257 *NOTE*: PGS is calculated as an average of PGS002257 and PGS002258
PPM015499 PGS002258
(GRS901_DBP)
 PSS009963|
European Ancestry|
33,770 individuals
 PGP000376 |
ร…berg F et al. Sci Rep (2022)
|Ext.		 Reported Trait: Liver-related outcome HR: 1.12 [1.01, 1.25] โ€” โ€” 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 โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0175 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.1101 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0588 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0793 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.027 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0009 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0008 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0012 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0044 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.04 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0506 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0259 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0527 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0106 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0122 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0001 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0205 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0036 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0081 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0375 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0365 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0189 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0174 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0078 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0305 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0289 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” 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 โ€” โ€” 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 โ€” โ€” 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 โ€” โ€” 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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.089 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
PPM014551 PGS002688
(bp_DIASTOLICadjMEDz.SBayesR)
 PSS009731|
African Ancestry|
6,128 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0195 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
PPM014649 PGS002688
(bp_DIASTOLICadjMEDz.SBayesR)
 PSS009733|
European Ancestry|
40,059 individuals
 PGP000332 |
Weissbrod O et al. Nat Genet (2022)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.1072 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 โ€” โ€” Incremental R2 (full model vs. covariates alone): 0.0596 age, sex, age*sex, assessment center, genotyping array, 10 PCs โ€”
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 ฮฒ: 1.21 (0.0464) โ€” Rยฒ: 0.026 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.11 (0.0477) โ€” Rยฒ: 0.0197 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.09 (0.0487) โ€” Rยฒ: 0.0174 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.06 (0.0468) โ€” Rยฒ: 0.0196 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.33 (0.0478) โ€” Rยฒ: 0.0275 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.23 (0.0468) โ€” Rยฒ: 0.0264 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.14 (0.048) โ€” Rยฒ: 0.0202 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.09 (0.0488) โ€” Rยฒ: 0.0176 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.05 (0.0468) โ€” Rยฒ: 0.0191 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 1.33 (0.0479) โ€” Rยฒ: 0.0276 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.327 (0.0456) โ€” Rยฒ: 0.00237 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.254 (0.0451) โ€” Rยฒ: 0.00138 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.267 (0.0452) โ€” Rยฒ: 0.00171 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.218 (0.0451) โ€” Rยฒ: 0.00094 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.46 (0.0457) โ€” Rยฒ: 0.00439 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.319 (0.0456) โ€” Rยฒ: 0.00228 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.26 (0.0452) โ€” Rยฒ: 0.00144 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.273 (0.0452) โ€” Rยฒ: 0.00178 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.142 (0.0458) โ€” Rยฒ: 0.00032 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.442 (0.0456) โ€” Rยฒ: 0.00414 SEX,AGE,Batch,PC1,PC2,PC3,PC4 โ€”
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 ฮฒ: 0.02 (0.01) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.034 (0.017) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.015 (0.012) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.103 (0.034) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.016 (0.035) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.009 (1.009) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 0.056 (0.024) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 ฮฒ: 1.066 (0.05) โ€” โ€” Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI โ€”
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 โ€” โ€” partial-R2: 0.06 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.07 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.05 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.03 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.05 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.03 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.05 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.01 sex, age, deprivation index, PC1-16 โ€”
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 โ€” โ€” partial-R2: 0.01 sex, age, deprivation index, PC1-16 โ€”
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 ฮฒ: 1.8 (0.26) โ€” Rยฒ: 0.0397 age, sex, array version, and the first 10 principal components of ancestry โ€”
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 ฮฒ: 2.41 [2.31, 2.5] โ€” โ€” 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)
PPM020231 PGS004232
(PRS732_DBP)
 PSS011310|
European Ancestry|
1,750 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Resistant blood pressure โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.56 [0.92, 2.7] โ€” โ€”
PPM020235 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Systolic blood pressure in all stroke โ€” โ€” Beta (beta, top PRS quintile vs bottom PRS quintile): 3.52 (0.42) age, sex, and vascular risk factors โ€”
PPM020236 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Uncontrolled blood pressure in all stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.6 [1.35, 1.89] age, sex, and vascular risk factors โ€”
PPM020237 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Resistant blood pressure in all stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.24 [1.6, 3.19] age, sex, and vascular risk factors โ€”
PPM020241 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Systolic blood pressure in Ischemic stroke โ€” โ€” Beta (beta, top PRS quintile vs bottom PRS quintile): 2.96 (0.84) age, sex, and vascular risk factors โ€”
PPM020242 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Uncontrolled blood pressure in Ischemic stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 1.45 [1.03, 2.03] age, sex, and vascular risk factors โ€”
PPM020243 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Resistant blood pressure in Ischemic stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 3.0 [1.62, 5.88] age, sex, and vascular risk factors โ€”
PPM020247 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Systolic blood pressure in Hemorrhagic stroke โ€” โ€” Beta (beta, top PRS quintile vs bottom PRS quintile): 3.66 (1.08) age, sex, and vascular risk factors โ€”
PPM020248 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Uncontrolled blood pressure in Hemorrhagic stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.63 [1.71, 4.1] age, sex, and vascular risk factors โ€”
PPM020249 PGS004232
(PRS732_DBP)
 PSS011309|
European Ancestry|
408,475 individuals
 PGP000529 |
Acosta JN et al. Neurology (2023)
 Reported Trait: Resistant blood pressure in Hemorrhagic stroke โ€” โ€” Odds ratio (OR, top PRS quintile vs bottom PRS quintile): 2.24 [0.84, 6.73] age, sex, and vascular risk factors โ€”
PPM020252 PGS004233
(DBP_MVP)
 PSS011312|
Multi-ancestry (including European)|
39,035 individuals
 PGP000531 |
Kurniansyah N et al. Nat Commun (2022)
 Reported Trait: Prevelant hypertension โ€” AUROC: 0.754 [0.741, 0.767] โ€” sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components โ€”
PPM020486 PGS004371
(X4079.score)
 PSS011364|
European Ancestry|
56,192 individuals
 PGP000561 |
Jung H et al. Commun Biol (2024)
 Reported Trait: Diastolic blood pressure, automated reading โ€” โ€” PGS R2 (no covariates): 0.18635 โ€” โ€”
PPM020762 PGS004604
(DBP-meta-analysis)
 PSS011397|
European Ancestry|
10,210 individuals
 PGP000581 |
Keaton JM et al. Nat Genet (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” Rยฒ: 0.1212
beta (high vs low tertile): 10.31		 Age, Age2, Sex, BMI โ€”
PPM020765 PGS004604
(DBP-meta-analysis)
 PSS011396|
African Ancestry|
21,843 individuals
 PGP000581 |
Keaton JM et al. Nat Genet (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” beta (high vs low tertile): 6.23 Age, Age2, Sex, BMI โ€”
PPM020980 PGS004755
(dbp_PRSmix_eur)
 PSS011465|
European Ancestry|
9,462 individuals
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (Full model versus model with only covariates): 0.044 [0.036, 0.052] age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 Incremental R2 (Full model versus model with only covariates)
PPM020981 PGS004756
(dbp_PRSmix_sas)
 PSS011491|
South Asian Ancestry|
7,185 individuals
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (Full model versus model with only covariates): 0.04 [0.031, 0.048] age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 Incremental R2 (Full model versus model with only covariates)
PPM020982 PGS004757
(dbp_PRSmixPlus_eur)
 PSS011465|
European Ancestry|
9,462 individuals
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (Full model versus model with only covariates): 0.05 [0.042, 0.059] age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 Incremental R2 (Full model versus model with only covariates)
PPM020983 PGS004758
(dbp_PRSmixPlus_sas)
 PSS011491|
South Asian Ancestry|
7,185 individuals
 PGP000604 |
Truong B et al. Cell Genom (2024)
 Reported Trait: Diastolic blood pressure โ€” โ€” Incremental R2 (Full model versus model with only covariates): 0.046 [0.036, 0.055] age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 Incremental R2 (Full model versus model with only covariates)

Evaluated Samples

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 โ€”
[
  • 574 cases
  • , 4,452 controls
]
,
37.0 % Male samples
 Mean = 50.6 years African American or Afro-Caribbean African American, Non-Hispanic Black BioVU โ€”
PSS009511 Apparent Treatment-Resistant Hypertension โ€”
[
  • 574 cases
  • , 4,452 controls
]
,
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 โ€”
[
  • 2,961 cases
  • , 25,584 controls
]
,
46.0 % Male samples
 Mean = 58.58 years European European, Non-Hispanic White BioVU โ€”
PSS009512 Apparent Treatment-Resistant Hypertension โ€”
[
  • 2,961 cases
  • , 25,584 controls
]
,
46.0 % Male samples
 Mean = 58.58 years European European, Non-Hispanic White BioVU Multi-Ancestry analysis
PSS010270 โ€” โ€” 2,194 individuals,
45.0 % Male samples
 Mean = 58.0 years
Sd = 7.1 years		 European Ashkenazi UKB โ€”
PSS009171 โ€” โ€” 3,930 individuals โ€” European Poland (NE Europe) UKB โ€”
PSS008277 โ€” โ€” 6,098 individuals โ€” South Asian India (South Asia) UKB โ€”
PSS011465 โ€” โ€” 9,462 individuals โ€” European โ€” AllofUs โ€”
PSS009963 โ€” Median = 12.9 years 33,770 individuals,
46.5 % Male samples
 Mean = 49.6 years European
(Finnish)		 Finland FINRISK, Health2000 โ€”
PSS010942 โ€” โ€” 18,679 individuals,
46.0 % Male samples
 Mean = 56.9 years
Sd = 7.9 years		 European white British UKB โ€”
PSS007261 โ€” โ€” 6,409 individuals โ€” African unspecified โ€” UKB โ€”
PSS007262 โ€” โ€” 1,634 individuals โ€” East Asian โ€” UKB โ€”
PSS007263 โ€” โ€” 23,727 individuals โ€” European non-white British ancestry UKB โ€”
PSS007264 โ€” โ€” 7,640 individuals โ€” South Asian โ€” UKB โ€”
PSS007265 โ€” โ€” 63,825 individuals โ€” European white British ancestry UKB Testing cohort (heldout set)
PSS010690 โ€” โ€” 6,182 individuals,
45.0 % Male samples
 Mean = 54.5 years
Sd = 8.4 years		 European Italian UKB โ€”
PSS010438 โ€” โ€” 1,709 individuals,
33.0 % Male samples
 Mean = 52.5 years
Sd = 7.8 years		 East Asian Chinese UKB โ€”
PSS011396 the earliest median eligible non-Emergency Department outpatient measured SBP in the electronic health record, and the corresponding DBP. For individuals with an even number of SBP measures in their record, the lower value was used to compute the median. For individuals with fewer than three measurements available, the lowest available SBP and corresponding DBP were used. Measures were considered ineligible if they occurred at or after an ICD-9/10 billing code from the groups 585/N18 (chronic kidney disease), 405/I15 (secondary hypertension), or 428/I50 (heart failure). For participants who had started an antihypertensive medication before the date of their median SBP measurement, 15 mm Hg was added to SBP and 10 mm Hg to DBP. Eligible SBP measures were restricted to a range of 30 to 300 mmHg. Eligible DBP measures were restricted to values over 30 mmHg. Eligible DBP measures were restricted to values over 30 mmHg. Sample size for SBP, DBP, and PP GWAS analysis included 21,843 individuals. Pulse pressure was defined as SBP minus DBP. Hypertension status was defined by phecodes 401* and/or antihypertensive medication use. โ€” 21,843 individuals,
42.69 % Male samples
 Mean = 48.3 years
Sd = 14.75 years		 African American or Afro-Caribbean
(American)		 โ€” AllofUs โ€”
PSS011397 In Lifelines, BP was measured every minute during a period of ten minutes using an automated DINAMAP Monitor (GE Healthcare) and the average of the final three readings was recorded for SBP and DBP. Participants with a measured BP โ‰ฅ140/90 mm Hg irrespective of treatment and those taking antihypertensive medication (ATC codes C02, C03, C07, C08, C09) irrespective of BP were defined as having hypertension. In continuous trait analyses, 15 mm Hg was added to SBP and 10 mm Hg was added to DBP for 1,236 individuals who were taking antihypertensive medication. PP was calculated using these medication-adjusted BP values. โ€” 10,210 individuals,
41.6 % Male samples
 Mean = 44.66 years
Sd = 13.05 years		 European
(Dutch)		 โ€” LifeLines โ€”
PSS008945 โ€” โ€” 3,850 individuals โ€” African unspecified Nigeria (West Africa) UKB โ€”
PSS011097 โ€” โ€” 2,669 individuals โ€” Greater Middle Eastern (Middle Eastern, North African or Persian)
(Arab)		 โ€” 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 Friedewaldโ€™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 Jaffeฬ method without deproteinisation (Ecolineยฎ MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 Highโ€sensitivity Cโ€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). โ€” 288 individuals,
69.2 % Male samples
 Mean = 15.83 years
Sd = 0.6 years		 European โ€” TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS010001 Diastolic Blood Pressure; Quantitative โ€” 23,074 individuals โ€” European โ€” MGI โ€”
PSS011491 โ€” โ€” 7,185 individuals โ€” South Asian โ€” G&H โ€”
PSS008054 โ€” โ€” 1,719 individuals โ€” East Asian China (East Asia) UKB โ€”
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 Friedewaldโ€™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 Jaffeฬ method without deproteinisation (Ecolineยฎ MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 Highโ€sensitivity Cโ€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). โ€” 1,354 individuals,
47.56 % Male samples
 Mean = 16.22 years
Sd = 0.66 years		 European โ€” TRAILS โ€”
PSS010185 โ€” โ€” 1,115 individuals,
41.1 % Male samples
 Mean = 46.18 years Hispanic or Latin American โ€” HCHS, SOL โ€”
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 โ‰ฅ140 mmHg or diastolic blood pressure โ‰ฅ90 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). โ€”
[
  • 725 cases
  • , 9,181 controls
]
 โ€” European
(Finnish)		 โ€” FINRISK โ€”
PSS009643 Corrected for baseline antihypertensive use โ€” 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 โ€”
PSS010858 โ€” โ€” 3,920 individuals,
38.0 % Male samples
 Mean = 54.3 years
Sd = 7.5 years		 European Polish UKB โ€”
PSS010606 โ€” โ€” 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 โ€”
PSS008725 โ€” โ€” 6,338 individuals โ€” European Italy (South Europe) UKB โ€”
PSS010354 โ€” โ€” 2,424 individuals,
36.0 % Male samples
 Mean = 52.5 years
Sd = 8.1 years		 African American or Afro-Caribbean Caribbean UKB โ€”
PSS011364 โ€” โ€” 56,192 individuals โ€” European โ€” UKB โ€”
PSS007841 โ€” โ€” 2,438 individuals โ€” African American or Afro-Caribbean Carribean UKB โ€”
PSS011309 โ€” โ€” 408,475 individuals,
59.0 % Male samples
 Mean = 61.0 years
Sd = 7.0 years		 European โ€” UKB โ€”
PSS011310 โ€” โ€” 1,750 individuals,
65.0 % Male samples
 Mean = 68.0 years
Sd = 11.0 years		 European โ€” VISP โ€”
PSS011189 โ€” โ€” 19,441 individuals,
44.7 % Male samples
 Mean = 47.36 years
Sd = 14.8 years		 African unspecified โ€” AllofUs โ€”
PSS011189 โ€” โ€” 2,891 individuals,
40.3 % Male samples
 Mean = 42.96 years
Sd = 16.67 years		 Asian unspecified โ€” AllofUs โ€”
PSS011189 โ€” โ€” 48,155 individuals,
40.4 % Male samples
 Mean = 53.65 years
Sd = 16.61 years		 European โ€” AllofUs โ€”
PSS011189 โ€” โ€” 18,034 individuals,
31.9 % Male samples
 Mean = 44.27 years
Sd = 15.79 years		 Hispanic or Latin American โ€” AllofUs โ€”
PSS011312 โ€” โ€” 22,701 individuals,
27.8 % Male samples
 โ€” European โ€” ARIC, CHS, FHS, MESA, WHI โ€”
PSS011312 โ€” โ€” 8,822 individuals,
31.9 % Male samples
 โ€” African American or Afro-Caribbean โ€” 6 cohorts
  • ARIC
  • ,CHS
  • ,GENOA
  • ,JHS
  • ,MESA
  • ,WHI
 โ€”
PSS011312 โ€” โ€” 6,718 individuals,
38.0 % Male samples
 โ€” Hispanic or Latin American โ€” 6 cohorts
  • CHS
  • ,FHS
  • ,HCHS
  • ,MESA
  • ,SOL
  • ,WHI
 โ€”
PSS011312 โ€” โ€” 794 individuals,
37.9 % Male samples
 โ€” Asian unspecified โ€” MESA, WHI โ€”
PSS010774 โ€” โ€” 3,819 individuals,
46.0 % Male samples
 Mean = 51.9 years
Sd = 8.1 years		 African unspecified Nigerian UKB โ€”
PSS009574 โ€” โ€” 14,004 individuals โ€” European โ€” Airwave โ€”
PSS009575 โ€” โ€” 6,970 individuals โ€” African unspecified โ€” UKB โ€”
PSS008499 โ€” โ€” 1,151 individuals โ€” Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB โ€”
PSS009576 โ€” โ€” 8,827 individuals โ€” South Asian โ€” UKB โ€”
PSS009397 โ€” โ€” 18,718 individuals โ€” European UK (+ Ireland) UKB โ€”
PSS009731 โ€” โ€” 6,128 individuals โ€” African unspecified โ€” UKB โ€”
PSS009732 โ€” โ€” 859 individuals โ€” East Asian โ€” UKB โ€”
PSS009733 โ€” โ€” 40,059 individuals โ€” European Non-British European UKB โ€”
PSS009734 โ€” โ€” 7,573 individuals โ€” South Asian โ€” UKB โ€”
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 โ‰ฅ140 mmHg or diastolic blood pressure โ‰ฅ90 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 โ‰ฅ55 years, respectively. โ€”
[
  • 55,917 cases
  • , 162,837 controls
]
 โ€” European
(Finnish)		 โ€” FinnGen โ€”
PSS010522 โ€” โ€” 6,050 individuals,
54.0 % Male samples
 Mean = 53.4 years
Sd = 8.4 years		 South Asian Indian UKB โ€”
PSS009510 Apparent Treatment-Resistant Hypertension โ€”
[
  • 106 cases
  • , 4,301 controls
]
 โ€” Not reported โ€” BioVU Multi-Ancestry analysis