Trait: cardiovascular disease biomarker measurement

Experimental Factor Ontology (EFO) Information
Identifier EFO_0005278
Description cardiovascular disease biomarkers, such as ST2 cardiac biomarker and C-reactive protein, are used as indicators for cardiovascular disease and as predictors for therapeutic responses
Trait category
Cardiovascular measurement
Child trait(s) 17 child traits

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
Note: This table shows all PGS for "cardiovascular disease biomarker measurement" and any child terms of this trait in the EFO hierarchy by default.
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000061
(GRS_LDL)
PGP000045 |
Johnson L et al. PLoS One (2015)
Low-density lipoprotein (LDL) cholesterol low density lipoprotein cholesterol measurement 37
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000061/ScoringFiles/PGS000061.txt.gz
PGS000065
(GLGC2017_LDL)
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
LDL cholesterol low density lipoprotein cholesterol measurement 103
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000065/ScoringFiles/PGS000065.txt.gz
PGS000115
(LDL-C_20)
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
LDL cholesterol low density lipoprotein cholesterol measurement 223
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000115/ScoringFiles/PGS000115.txt.gz
PGS000192
(GS9)
PGP000079 |
Kathiresan S et al. N Engl J Med (2008)
Cholesterol low density lipoprotein cholesterol measurement,
high density lipoprotein cholesterol measurement
9
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000192/ScoringFiles/PGS000192.txt.gz
PGS000300
(GRS80_HR)
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Heart rate resting heart rate 80
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000300/ScoringFiles/PGS000300.txt.gz
PGS000310
(GRS194_LDL)
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
LDL cholesterol low density lipoprotein cholesterol measurement 194
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000310/ScoringFiles/PGS000310.txt.gz
PGS000340
(LDL-Cpsp)
PGP000107 |
Trinder M et al. Circ Genom Precis Med (2020)
LDL cholesterol low density lipoprotein cholesterol measurement 28
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000340/ScoringFiles/PGS000340.txt.gz
PGS000661
(PRS-LDL)
PGP000121 |
Tam CHT et al. Genome Med (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 84
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000661/ScoringFiles/PGS000661.txt.gz
PGS000671
(snpnet.Apolipoprotein_A)
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Apolipoprotein A [g/L] apolipoprotein A 1 measurement 19,324
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000671/ScoringFiles/PGS000671.txt.gz - Check Terms/Licenses
PGS000688
(snpnet.LDL_direct_adjstatins)
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
LDL cholesterol [mmol/L] (statin adjusted) low density lipoprotein cholesterol measurement 16,184
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000688/ScoringFiles/PGS000688.txt.gz - Check Terms/Licenses
PGS000735
(PRS_PR)
PGP000144 |
Tadros R et al. Eur Heart J (2019)
PR interval PR interval 44
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000735/ScoringFiles/PGS000735.txt.gz
PGS000736
(PRS_QRS)
PGP000144 |
Tadros R et al. Eur Heart J (2019)
QRS duration QRS duration 26
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000736/ScoringFiles/PGS000736.txt.gz
PGS000768
(PRS_QT)
PGP000175 |
Lahrouchi N et al. Circulation (2020)
QT-interval QT interval 68
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000768/ScoringFiles/PGS000768.txt.gz
PGS000814
(GRS12_LDLc)
PGP000200 |
Talmud PJ et al. Lancet (2013)
LDL cholesterol low density lipoprotein cholesterol measurement 12
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000814/ScoringFiles/PGS000814.txt.gz
PGS000824
(LDL-C_PGS)
PGP000210 |
Zubair N et al. Sci Rep (2019)
LDL cholesterol low density lipoprotein cholesterol measurement 809
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000824/ScoringFiles/PGS000824.txt.gz - Check Terms/Licenses
PGS000846
(LDL)
PGP000211 |
Aly DM et al. Nat Genet (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 275
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000846/ScoringFiles/PGS000846.txt.gz
PGS000875
(PGS36_LDLc)
PGP000221 |
Leal LG et al. Mol Genet Genomic Med (2020)
LDL cholesterol low density lipoprotein cholesterol measurement 36
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000875/ScoringFiles/PGS000875.txt.gz
PGS000886
(GLGC_2021_AFR_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,222,318
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000886/ScoringFiles/PGS000886.txt.gz
PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 295
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000887/ScoringFiles/PGS000887.txt.gz
PGS000888
(GLGC_2021_ALL_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,239,184
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000888/ScoringFiles/PGS000888.txt.gz
PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 9,009
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000889/ScoringFiles/PGS000889.txt.gz
PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,029,158
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000890/ScoringFiles/PGS000890.txt.gz
PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 66
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000891/ScoringFiles/PGS000891.txt.gz
PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,119,211
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000892/ScoringFiles/PGS000892.txt.gz
PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 5,427
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000893/ScoringFiles/PGS000893.txt.gz
PGS000894
(GLGC_2021_HIS_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,175,595
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000894/ScoringFiles/PGS000894.txt.gz
PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 76
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000895/ScoringFiles/PGS000895.txt.gz
PGS000896
(GLGC_2021_SAS_LDL_PRS_weights_PRS-CS)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 1,100,062
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000896/ScoringFiles/PGS000896.txt.gz
PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PGP000230 |
Graham SE et al. Nature (2021)
LDL cholesterol low density lipoprotein cholesterol measurement 13
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000897/ScoringFiles/PGS000897.txt.gz
PGS000904
(PRS582_PR)
PGP000236 |
Ntalla I et al. Nat Commun (2020)
PR interval PR interval 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000904/ScoringFiles/PGS000904.txt.gz
PGS000905
(PRS743_PR)
PGP000236 |
Ntalla I et al. Nat Commun (2020)
PR interval PR interval 743
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000905/ScoringFiles/PGS000905.txt.gz
PGS001233
(GBE_INI102)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Heart rate (AR) heart rate 14,455
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001233/ScoringFiles/PGS001233.txt.gz
PGS001375
(GBE_INI22426)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Average heart rate heart rate 243
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001375/ScoringFiles/PGS001375.txt.gz
PGS001412
(GBE_INI22420)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
LV ejection fraction left ventricular ejection fraction measurement 266
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001412/ScoringFiles/PGS001412.txt.gz
PGS001413
(GBE_INI22423)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
LV stroke volume left ventricular stroke volume measurement 26
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001413/ScoringFiles/PGS001413.txt.gz
PGS001519
(GBE_INI4199)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Position of pulse wave notch arterial stiffness measurement 693
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001519/ScoringFiles/PGS001519.txt.gz
PGS001520
(GBE_INI4198)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Position of the pulse wave peak arterial stiffness measurement 1,358
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001520/ScoringFiles/PGS001520.txt.gz
PGS001521
(GBE_INI22330)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
PQ interval PR interval 391
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001521/ScoringFiles/PGS001521.txt.gz
PGS001523
(GBE_INI4194)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Pulse rate heart rate 4,117
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001523/ScoringFiles/PGS001523.txt.gz
PGS001524
(GBE_INI95)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Pulse rate (during blood-pressure measurement) heart rate 765
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001524/ScoringFiles/PGS001524.txt.gz
PGS001525
(GBE_INI12340)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
QRS duration QRS duration 401
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001525/ScoringFiles/PGS001525.txt.gz
PGS001526
(GBE_INI22331)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
QT interval QT interval 609
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001526/ScoringFiles/PGS001526.txt.gz
PGS001527
(GBE_INI22332)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
QTc interval (QT interval according to Bazett) QT interval 115
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001527/ScoringFiles/PGS001527.txt.gz
PGS001888
(portability-PLR_apoA)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Apolipoprotein A apolipoprotein A 1 measurement 74,596
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001888/ScoringFiles/PGS001888.txt.gz
PGS001902
(portability-PLR_ECG_P_duration)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
P duration P wave duration 640
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001902/ScoringFiles/PGS001902.txt.gz
PGS001903
(portability-PLR_ECG_PP_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PP interval PP interval 4,368
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001903/ScoringFiles/PGS001903.txt.gz
PGS001904
(portability-PLR_ECG_PQ_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PQ interval PR interval 826
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001904/ScoringFiles/PGS001904.txt.gz
PGS001905
(portability-PLR_ECG_QT_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QT interval QT interval 2,300
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001905/ScoringFiles/PGS001905.txt.gz
PGS001906
(portability-PLR_ECG_QTC_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QTc interval QT interval 641
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001906/ScoringFiles/PGS001906.txt.gz
PGS001907
(portability-PLR_ECG_RR_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
RR interval RR interval 1,964
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001907/ScoringFiles/PGS001907.txt.gz
PGS001933
(portability-PLR_LDL)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
LDL direct low density lipoprotein cholesterol measurement 25,604
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001933/ScoringFiles/PGS001933.txt.gz
PGS001948
(portability-PLR_log_ECG_QRS_duration)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QRS duration QRS duration 1,967
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001948/ScoringFiles/PGS001948.txt.gz
PGS001975
(portability-PLR_log_pulse_rate)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Pulse rate, automated reading heart rate 62,254
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001975/ScoringFiles/PGS001975.txt.gz
PGS001981
(portability-PLR_log_ventricular_rate)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Ventricular rate ventricular rate measurement 6,324
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001981/ScoringFiles/PGS001981.txt.gz
PGS002101
(portability-ldpred2_apoA)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Apolipoprotein A apolipoprotein A 1 measurement 681,234
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002101/ScoringFiles/PGS002101.txt.gz
PGS002116
(portability-ldpred2_ECG_P_duration)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
P duration P wave duration 564,874
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002116/ScoringFiles/PGS002116.txt.gz
PGS002117
(portability-ldpred2_ECG_PP_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PP interval PP interval 667,705
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002117/ScoringFiles/PGS002117.txt.gz
PGS002118
(portability-ldpred2_ECG_PQ_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
PQ interval PR interval 413,539
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002118/ScoringFiles/PGS002118.txt.gz
PGS002119
(portability-ldpred2_ECG_QT_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QT interval QT interval 571,268
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002119/ScoringFiles/PGS002119.txt.gz
PGS002120
(portability-ldpred2_ECG_QTC_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QTc interval QT interval 490,392
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002120/ScoringFiles/PGS002120.txt.gz
PGS002121
(portability-ldpred2_ECG_RR_interval)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
RR interval RR interval 616,710
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002121/ScoringFiles/PGS002121.txt.gz
PGS002150
(portability-ldpred2_LDL)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
LDL direct low density lipoprotein cholesterol measurement 360,007
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002150/ScoringFiles/PGS002150.txt.gz
PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
QRS duration QRS duration 471,172
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002166/ScoringFiles/PGS002166.txt.gz
PGS002193
(portability-ldpred2_log_pulse_rate)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Pulse rate, automated reading heart rate 858,487
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002193/ScoringFiles/PGS002193.txt.gz
PGS002199
(portability-ldpred2_log_ventricular_rate)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Ventricular rate ventricular rate measurement 705,680
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002199/ScoringFiles/PGS002199.txt.gz
PGS002267
(PRS89_AA)
PGP000296 |
Pirruccello JP et al. Nat Genet (2021)
Ascending thoracic aortic diameter cardiovascular disease biomarker measurement,
aortic measurement
89
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002267/ScoringFiles/PGS002267.txt.gz
PGS002274
(LDL-PRS)
PGP000303 |
Groenland EH et al. Atherosclerosis (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 279
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002274/ScoringFiles/PGS002274.txt.gz
PGS002276
(QTc_PRS-CS)
PGP000304 |
Nauffal V et al. Circulation (2022)
QTc duration QT interval 1,110,494
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002276/ScoringFiles/PGS002276.txt.gz
PGS002278
(GRS16_snLVEF)
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Supranormal left ventricular ejection fraction left ventricular ejection fraction measurement 16
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002278/ScoringFiles/PGS002278.txt.gz
PGS002279
(GRS22_rLVEF)
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reduced left ventricular ejection fraction left ventricular ejection fraction measurement 22
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002279/ScoringFiles/PGS002279.txt.gz
PGS002285
(GRS_286_LDL)
PGP000313 |
Kamiza AB et al. Nat Med (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 286
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002285/ScoringFiles/PGS002285.txt.gz
PGS002337
(biochemistry_LDLdirect.BOLT-LMM)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 1,109,311
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002337/ScoringFiles/PGS002337.txt.gz
PGS002369
(biochemistry_LDLdirect.BOLT-LMM-BBJ)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 920,930
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002369/ScoringFiles/PGS002369.txt.gz
PGS002409
(biochemistry_LDLdirect.P+T.0.0001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 7,626
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002409/ScoringFiles/PGS002409.txt.gz
PGS002458
(biochemistry_LDLdirect.P+T.0.001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 20,708
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002458/ScoringFiles/PGS002458.txt.gz
PGS002507
(biochemistry_LDLdirect.P+T.0.01)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 105,053
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002507/ScoringFiles/PGS002507.txt.gz
PGS002556
(biochemistry_LDLdirect.P+T.1e-06)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 3,244
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002556/ScoringFiles/PGS002556.txt.gz
PGS002605
(biochemistry_LDLdirect.P+T.5e-08)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 2,337
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002605/ScoringFiles/PGS002605.txt.gz
PGS002654
(biochemistry_LDLdirect.PolyFun-pred)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 274,585
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002654/ScoringFiles/PGS002654.txt.gz
PGS002703
(biochemistry_LDLdirect.SBayesR)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 970,081
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002703/ScoringFiles/PGS002703.txt.gz
PGS002730
(GRSlipid_35)
PGP000337 |
Mayerhofer E et al. Brain (2022)
LDL lowering in response to statin low density lipoprotein cholesterol measurement,
response to statin
35
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002730/ScoringFiles/PGS002730.txt.gz
PGS002782
(GLGC_2021_ALL_nonHDL_PRS_weights_PRS-CS)
PGP000366 |
Kanoni S et al. medRxiv (2021)
|Pre
nonHDL Cholesterol non-high density lipoprotein cholesterol measurement 1,239,184
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002782/ScoringFiles/PGS002782.txt.gz
PGS003029
(ExPRSweb_LDL_30780-irnt_LASSOSUM_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 549,112
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003029/ScoringFiles/PGS003029.txt.gz
PGS003030
(ExPRSweb_LDL_30780-irnt_PT_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 2,066
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003030/ScoringFiles/PGS003030.txt.gz
PGS003031
(ExPRSweb_LDL_30780-irnt_PLINK_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 2,609
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003031/ScoringFiles/PGS003031.txt.gz
PGS003032
(ExPRSweb_LDL_30780-irnt_DBSLMM_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 7,457,930
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003032/ScoringFiles/PGS003032.txt.gz
PGS003033
(ExPRSweb_LDL_30780-irnt_PRSCS_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 1,113,830
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003033/ScoringFiles/PGS003033.txt.gz
PGS003034
(ExPRSweb_LDL_30780-raw_LASSOSUM_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 552,845
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003034/ScoringFiles/PGS003034.txt.gz
PGS003035
(ExPRSweb_LDL_30780-raw_PT_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 2,288
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003035/ScoringFiles/PGS003035.txt.gz
PGS003036
(ExPRSweb_LDL_30780-raw_PLINK_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 2,935
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003036/ScoringFiles/PGS003036.txt.gz
PGS003037
(ExPRSweb_LDL_30780-raw_DBSLMM_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 8,918,470
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003037/ScoringFiles/PGS003037.txt.gz
PGS003038
(ExPRSweb_LDL_30780-raw_PRSCS_MGI_20211120)
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 1,113,830
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003038/ScoringFiles/PGS003038.txt.gz
PGS003339
(CVGRS_LDL)
PGP000405 |
Kim YJ et al. Nat Commun (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 65
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003339/ScoringFiles/PGS003339.txt.gz
PGS003348
(ALLGRS_LDL)
PGP000405 |
Kim YJ et al. Nat Commun (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 78
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003348/ScoringFiles/PGS003348.txt.gz
PGS003403
(PRS28_LDL)
PGP000420 |
Trinder M et al. J Am Coll Cardiol (2019)
LDL cholesterol low density lipoprotein cholesterol measurement 28
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003403/ScoringFiles/PGS003403.txt.gz
PGS003404
(wGRS)
PGP000421 |
Wang J et al. Arterioscler Thromb Vasc Biol (2016)
LDL cholesterol low density lipoprotein cholesterol measurement 10
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003404/ScoringFiles/PGS003404.txt.gz
PGS003405
(165SNP_PRS)
PGP000422 |
Vanhoye X et al. Transl Res (2022)
LDL cholesterol low density lipoprotein cholesterol measurement 165
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003405/ScoringFiles/PGS003405.txt.gz
PGS003427
(lvmi)
PGP000434 |
Khurshid S et al. Nat Commun (2023)
Left ventricular mass index (LVMI) left ventricular mass index 465
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003427/ScoringFiles/PGS003427.txt.gz
PGS003472
(LDPred2_HrRt)
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Heart rate heart rate 776,860
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003472/ScoringFiles/PGS003472.txt.gz
PGS003474
(LDPred2_LDL)
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
LDL levels low density lipoprotein cholesterol measurement 842,513
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003474/ScoringFiles/PGS003474.txt.gz
PGS003477
(LDPred2_PP)
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Pulse pressure pulse pressure measurement 847,747
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003477/ScoringFiles/PGS003477.txt.gz
PGS003499
(cont-decay-ECG_PQ_interval)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
PQ interval PR interval 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003499/ScoringFiles/PGS003499.txt.gz
PGS003500
(cont-decay-ECG_QT_interval)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
QT interval QT interval 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003500/ScoringFiles/PGS003500.txt.gz
PGS003501
(cont-decay-ECG_QTC_interval)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
QTc interval QT interval 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003501/ScoringFiles/PGS003501.txt.gz
PGS003517
(cont-decay-LDL)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
LDL direct low density lipoprotein cholesterol measurement 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003517/ScoringFiles/PGS003517.txt.gz
PGS003529
(cont-decay-log_ECG_QRS_duration)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
QRS duration QRS duration 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003529/ScoringFiles/PGS003529.txt.gz
PGS003550
(cont-decay-log_pulse_rate)
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Pulse rate, automated reading heart rate 979,739
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003550/ScoringFiles/PGS003550.txt.gz
PGS003784
(LDL_EUR_CT)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 3,754
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003784/ScoringFiles/PGS003784.txt.gz
PGS003785
(LDL_EUR_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,490,736
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003785/ScoringFiles/PGS003785.txt.gz
PGS003786
(LDL_AFR_CT)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 188
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003786/ScoringFiles/PGS003786.txt.gz
PGS003787
(LDL_AFR_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,679,610
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003787/ScoringFiles/PGS003787.txt.gz
PGS003788
(LDL_AFR_weighted_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,679,610
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003788/ScoringFiles/PGS003788.txt.gz
PGS003789
(LDL_AFR_PRSCSx)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,155,363
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003789/ScoringFiles/PGS003789.txt.gz
PGS003790
(LDL_AFR_CTSLEB)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,120,053
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003790/ScoringFiles/PGS003790.txt.gz
PGS003791
(LDL_EAS_CT)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 80
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003791/ScoringFiles/PGS003791.txt.gz
PGS003792
(LDL_EAS_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,191,112
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003792/ScoringFiles/PGS003792.txt.gz
PGS003793
(LDL_EAS_weighted_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,191,112
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003793/ScoringFiles/PGS003793.txt.gz
PGS003794
(LDL_EAS_PRSCSx)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,155,363
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003794/ScoringFiles/PGS003794.txt.gz
PGS003795
(LDL_EAS_CTSLEB)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 564,379
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003795/ScoringFiles/PGS003795.txt.gz
PGS003796
(LDL_SAS_CT)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 25
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003796/ScoringFiles/PGS003796.txt.gz
PGS003797
(LDL_SAS_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,507,815
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003797/ScoringFiles/PGS003797.txt.gz
PGS003798
(LDL_SAS_weighted_LDpred2)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,507,815
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003798/ScoringFiles/PGS003798.txt.gz
PGS003799
(LDL_SAS_PRSCSx)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,155,363
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003799/ScoringFiles/PGS003799.txt.gz
PGS003800
(LDL_SAS_CTSLEB)
PGP000489 |
Zhang H et al. Nat Genet (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 801,576
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003800/ScoringFiles/PGS003800.txt.gz
PGS003855
(PRS44_LDL)
PGP000493 |
Li J et al. JAMA Netw Open (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 44
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003855/ScoringFiles/PGS003855.txt.gz
PGS003869
(LDL_PRScsx_ARB_AFRweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,022,259
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003869/ScoringFiles/PGS003869.txt.gz
PGS003870
(LDL_PRScsx_ARB_AMRweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,067,857
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003870/ScoringFiles/PGS003870.txt.gz
PGS003871
(LDL_PRScsx_ARB_ARBweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 882,001
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003871/ScoringFiles/PGS003871.txt.gz
PGS003872
(LDL_PRScsx_ARB_EASweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 958,649
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003872/ScoringFiles/PGS003872.txt.gz
PGS003873
(LDL_PRScsx_ARB_EURweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,069,677
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003873/ScoringFiles/PGS003873.txt.gz
PGS003874
(LDL_PRScsx_ARB_SASweights)
PGP000501 |
Shim I et al. Nature Communications (2023)
LDL cholesterol low density lipoprotein cholesterol measurement 1,054,648
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003874/ScoringFiles/PGS003874.txt.gz
PGS003974
(AFR_without-UKB_LDL)
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
LDL cholesterol low density lipoprotein cholesterol measurement 886,257
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003974/ScoringFiles/PGS003974.txt.gz
PGS003975
(EAS_without-UKB_LDL)
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
LDL cholesterol low density lipoprotein cholesterol measurement 862,971
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003975/ScoringFiles/PGS003975.txt.gz
PGS003976
(EUR_without-UKB_LDL)
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
LDL cholesterol low density lipoprotein cholesterol measurement 821,134
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003976/ScoringFiles/PGS003976.txt.gz
PGS003977
(SAS_without-UKB_LDL)
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
LDL cholesterol low density lipoprotein cholesterol measurement 826,248
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003977/ScoringFiles/PGS003977.txt.gz
PGS003978
(meta_without-UKB_LDL)
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
LDL cholesterol low density lipoprotein cholesterol measurement 348,056
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003978/ScoringFiles/PGS003978.txt.gz
PGS004327
(X4194.score)
PGP000561 |
Jung H et al. Commun Biol (2024)
Pulse rate heart rate 1,059,939
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004327/ScoringFiles/PGS004327.txt.gz
PGS004370
(X102.score)
PGP000561 |
Jung H et al. Commun Biol (2024)
Pulse rate, automated reading heart rate 1,059,939
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004370/ScoringFiles/PGS004370.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
PPM000155 PGS000061
(GRS_LDL)
PSS000098|
European Ancestry|
2,063 individuals
PGP000045 |
Johnson L et al. PLoS One (2015)
Reported Trait: Serum low-density lipoprotein (LDL) levels β: 15.0 Beta (p-value): 0.0352 age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG Association (p-value; unadjusted for covariates) < 0.001
PPM000156 PGS000061
(GRS_LDL)
PSS000097|
East Asian Ancestry|
666 individuals
PGP000045 |
Johnson L et al. PLoS One (2015)
Reported Trait: Serum low-density lipoprotein (LDL) levels β: 5.58 Beta (p-value): 0.697 age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG Association (p-value; unadjusted for covariates) < 0.001
PPM000157 PGS000061
(GRS_LDL)
PSS000096|
African Ancestry|
1,355 individuals
PGP000045 |
Johnson L et al. PLoS One (2015)
Reported Trait: Serum low-density lipoprotein (LDL) levels β: 30.04 Beta (p-value): 0.00282 age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG Association (p-value; unadjusted for covariates) < 0.001
PPM000158 PGS000061
(GRS_LDL)
PSS000099|
Hispanic or Latin American Ancestry|
1,256 individuals
PGP000045 |
Johnson L et al. PLoS One (2015)
Reported Trait: Serum low-density lipoprotein (LDL) levels β: 42.86 Beta (p-value): 2e-05 age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG Association (p-value; unadjusted for covariates) < 0.001
PPM000168 PGS000065
(GLGC2017_LDL)
PSS000104|
European Ancestry|
9,962 individuals
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
Reported Trait: Serum low-density lipoprotein (LDL) levels correlation (r): 0.274 [0.254, 0.294] age, sex Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA
PPM000171 PGS000065
(GLGC2017_LDL)
PSS000102|
European Ancestry|
1,641 individuals
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
Reported Trait: Serum low-density lipoprotein (LDL) levels correlation (r): 0.229 [0.172, 0.286] age, sex Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA
PPM000174 PGS000065
(GLGC2017_LDL)
PSS000103|
European Ancestry|
1,945 individuals
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
Reported Trait: Serum low-density lipoprotein (LDL) levels correlation (r): 0.29 [0.231, 0.349] age, sex Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA
PPM000177 PGS000065
(GLGC2017_LDL)
PSS000100|
African Ancestry|
6,407 individuals
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
Reported Trait: Serum low-density lipoprotein (LDL) levels correlation (r): 0.28 [0.257, 0.304] age, sex Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA
PPM000180 PGS000065
(GLGC2017_LDL)
PSS000101|
East Asian Ancestry|
21,295 individuals
PGP000046 |
Kuchenbaecker K et al. Nat Commun (2019)
Reported Trait: Serum low-density lipoprotein (LDL) levels correlation (r): 0.198 [0.161, 0.235] age, sex, region, 20 PCs of genetic ancestry Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA
PPM000264 PGS000115
(LDL-C_20)
PSS000184|
European Ancestry|
439,871 individuals
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels β: 28.01 (0.18) : 0.09 age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch)
PPM000265 PGS000115
(LDL-C_20)
PSS000183|
East Asian Ancestry|
10,640 individuals
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels β: 21.73 (1.25) : 0.06 age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch)
PPM000266 PGS000115
(LDL-C_20)
PSS000181|
African Ancestry|
4,680 individuals
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels β: 17.4 (1.91) : 0.04 age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch)
PPM000267 PGS000115
(LDL-C_20)
PSS000185|
Multi-ancestry (including European)|
455,191 individuals
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels β: 27.78 (0.18) : 0.09 age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch)
PPM000268 PGS000115
(LDL-C_20)
PSS000182|
Multi-ancestry (including European)|
47,845 individuals
PGP000053 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Cardiovascular disease events Hazard Ratio (HR; top vs. bottom decile of risk): 1.35 [1.3, 1.4] age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch)
PPM012859 PGS000115
(LDL-C_20)
PSS009580|
European Ancestry|
33,787 individuals
PGP000284 |
Tapela NM et al. Eur J Prev Cardiol (2021)
|Ext.
Reported Trait: Uncontrolled hypercholesterolaemia Odds Ratio (OR, top vs. bottom quintile): 2.78 [2.58, 3.0] age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline 218 SNPs remained after QC
PPM012860 PGS000115
(LDL-C_20)
PSS009577|
European Ancestry|
33,787 individuals
PGP000284 |
Tapela NM et al. Eur J Prev Cardiol (2021)
|Ext.
Reported Trait: Incident major adverse cardiovascular events in statin treatment Hazard Ratio (HR, top vs. bottom quintile): 1.03 [0.92, 1.14] age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline 218 SNPs remained after QC
PPM012861 PGS000115
(LDL-C_20)
PSS009578|
European Ancestry|
33,787 individuals
PGP000284 |
Tapela NM et al. Eur J Prev Cardiol (2021)
|Ext.
Reported Trait: Incident myocardial infarction in statin treatment Hazard Ratio (HR, top vs. bottom quintile): 1.08 [0.95, 1.23] age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline 218 SNPs remained after QC
PPM012862 PGS000115
(LDL-C_20)
PSS009579|
European Ancestry|
33,787 individuals
PGP000284 |
Tapela NM et al. Eur J Prev Cardiol (2021)
|Ext.
Reported Trait: Incident stroke in statin treatment Hazard Ratio (HR, top vs. bottom quintile): 0.93 [0.77, 1.12] age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline 218 SNPs remained after QC
PPM000563 PGS000192
(GS9)
PSS000292|
European Ancestry|
4,232 individuals
PGP000079 |
Kathiresan S et al. N Engl J Med (2008)
Reported Trait: Incident cardiovascular event AUROC: 0.8 Hazard Ratio (HR; per allele): 1.15 [1.07, 1.24] age, sex, family history of MI, LDL cholesterol, HDL cholesterol, triglycerides, blood pressure, body mass index, diabetes status, smoking status, CRP, lipid lowering medication
PPM000562 PGS000192
(GS9)
PSS000292|
European Ancestry|
4,232 individuals
PGP000079 |
Kathiresan S et al. N Engl J Med (2008)
Reported Trait: High-density lipoprotein (HDL) levels Association p-value: 2.00e-18
PPM000561 PGS000192
(GS9)
PSS000292|
European Ancestry|
4,232 individuals
PGP000079 |
Kathiresan S et al. N Engl J Med (2008)
Reported Trait: Low-density lipoprotein (LDL) levels Association p-value: 3.00e-24
PPM000769 PGS000300
(GRS80_HR)
PSS000374|
European Ancestry|
1,318 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Heart rate (bpm) : 0.0211 Sex, age, age^2, BMI
PPM000770 PGS000300
(GRS80_HR)
PSS000376|
European Ancestry|
1,354 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Heart rate (bpm) : 0.0146 Sex, age, age^2, BMI
PPM000799 PGS000300
(GRS80_HR)
PSS000369|
European Ancestry|
334 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Heart rate (bpm) : 0.0028 Sex, age, age^2, BMI
PPM000800 PGS000300
(GRS80_HR)
PSS000371|
European Ancestry|
288 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Heart rate (bpm) : 0.0223 Sex, age, age^2, BMI
PPM000780 PGS000310
(GRS194_LDL)
PSS000376|
European Ancestry|
1,354 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Low-density lipoprotein (mmol/l) : 0.1849 Sex, age, age^2
PPM000924 PGS000340
(LDL-Cpsp)
PSS000466|
European Ancestry|
389,127 individuals
PGP000107 |
Trinder M et al. Circ Genom Precis Med (2020)
Reported Trait: Low-density lipoprotein cholesterol levels β: 0.82 (0.006) : 0.074 Age, sex
PPM000923 PGS000340
(LDL-Cpsp)
PSS000465|
Multi-ancestry (including European)|
1,120 individuals
PGP000107 |
Trinder M et al. Circ Genom Precis Med (2020)
Reported Trait: Low-density lipoprotein cholesterol levels in familial hypercholesterolemia mutation carriers Beta (per 20% increase in PGS): 0.13 [0.072, 0.19]
PPM000925 PGS000340
(LDL-Cpsp)
PSS000465|
Multi-ancestry (including European)|
1,120 individuals
PGP000107 |
Trinder M et al. Circ Genom Precis Med (2020)
Reported Trait: Atherosclerotic cardiovascular disease in familial hypercholesterolemia mutation carriers Odds Ratio (OR; top 20% vs. rest): 1.48 [1.02, 2.14] sex
PPM001361 PGS000661
(PRS-LDL)
PSS000588|
East Asian Ancestry|
426 individuals
PGP000121 |
Tam CHT et al. Genome Med (2021)
Reported Trait: LDL choldesterol at baseline (log transformed) β: 0.072 (0.012) Pearson Correlation Coefficient (r): 0.255
Incremental R² (PRS and covariates vs. covariates-alone): 0.0672
age, sex, BMI, PCs
PPM001362 PGS000661
(PRS-LDL)
PSS000594|
East Asian Ancestry|
4,917 individuals
PGP000121 |
Tam CHT et al. Genome Med (2021)
Reported Trait: LDL choldesterol at baseline (log transformed) β: 0.059 (0.004) Pearson Correlation Coefficient (r): 0.178
Incremental R² (PRS and covariates vs. covariates-alone): 0.0351
age, sex, BMI, PCs
PPM001363 PGS000661
(PRS-LDL)
PSS000590|
East Asian Ancestry|
1,941 individuals
PGP000121 |
Tam CHT et al. Genome Med (2021)
Reported Trait: LDL choldesterol at baseline (log transformed) β: 0.054 (0.006) Pearson Correlation Coefficient (r): 0.19
Incremental R² (PRS and covariates vs. covariates-alone): 0.036
age, sex, BMI, PCs
PPM001364 PGS000661
(PRS-LDL)
PSS000592|
East Asian Ancestry|
865 individuals
PGP000121 |
Tam CHT et al. Genome Med (2021)
Reported Trait: LDL choldesterol at baseline (log transformed) β: 0.058 (0.01) Pearson Correlation Coefficient (r): 0.195
Incremental R² (PRS and covariates vs. covariates-alone): 0.0374
age, sex, BMI, PCs
PPM001434 PGS000671
(snpnet.Apolipoprotein_A)
PSS000638|
East Asian Ancestry|
974 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] : 0.32046
Spearman's ρ: 0.329
Age, sex, PCs(1-40)
PPM001399 PGS000671
(snpnet.Apolipoprotein_A)
PSS000637|
African Ancestry|
5,550 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] : 0.1486
Spearman's ρ: 0.213
Age, sex, PCs(1-40)
PPM001469 PGS000671
(snpnet.Apolipoprotein_A)
PSS000639|
European Ancestry|
21,403 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] : 0.31504
Spearman's ρ: 0.385
Age, sex, PCs(1-40)
PPM001504 PGS000671
(snpnet.Apolipoprotein_A)
PSS000640|
South Asian Ancestry|
6,682 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] : 0.29281
Spearman's ρ: 0.358
Age, sex, PCs(1-40)
PPM001539 PGS000671
(snpnet.Apolipoprotein_A)
PSS000641|
European Ancestry|
57,932 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] : 0.30509
Spearman's ρ: 0.398
Age, sex, PCs(1-40)
PPM001580 PGS000671
(snpnet.Apolipoprotein_A)
PSS000795|
European Ancestry|
1,378 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Apolipoprotein A [g/L] Spearman's ρ: 0.241 Age, sex
PPM007280 PGS000671
(snpnet.Apolipoprotein_A)
PSS007086|
African Ancestry|
5,632 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Apolipoprotein A : 0.14722 [0.13131, 0.16312]
Incremental R2 (full-covars): 0.04255
PGS R2 (no covariates): 0.03865 [0.02947, 0.04784]
age, sex, UKB array type, Genotype PCs
PPM007281 PGS000671
(snpnet.Apolipoprotein_A)
PSS007087|
East Asian Ancestry|
1,462 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Apolipoprotein A : 0.28691 [0.25071, 0.3231]
Incremental R2 (full-covars): 0.07041
PGS R2 (no covariates): 0.08155 [0.0567, 0.10641]
age, sex, UKB array type, Genotype PCs
PPM007282 PGS000671
(snpnet.Apolipoprotein_A)
PSS007088|
European Ancestry|
21,609 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Apolipoprotein A : 0.28381 [0.27434, 0.29329]
Incremental R2 (full-covars): 0.11215
PGS R2 (no covariates): 0.12323 [0.11558, 0.13087]
age, sex, UKB array type, Genotype PCs
PPM007283 PGS000671
(snpnet.Apolipoprotein_A)
PSS007089|
South Asian Ancestry|
6,776 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Apolipoprotein A : 0.26533 [0.24858, 0.28209]
Incremental R2 (full-covars): 0.1056
PGS R2 (no covariates): 0.11603 [0.1027, 0.12937]
age, sex, UKB array type, Genotype PCs
PPM007284 PGS000671
(snpnet.Apolipoprotein_A)
PSS007090|
European Ancestry|
58,749 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Apolipoprotein A : 0.27548 [0.26974, 0.28122]
Incremental R2 (full-covars): 0.12135
PGS R2 (no covariates): 0.1349 [0.1301, 0.13969]
age, sex, UKB array type, Genotype PCs
PPM001416 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000714|
African Ancestry|
6,003 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) : 0.13357
Spearman's ρ: 0.289
Age, sex, PCs(1-40)
PPM001451 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000715|
East Asian Ancestry|
1,082 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) : 0.13985
Spearman's ρ: 0.301
Age, sex, PCs(1-40)
PPM001486 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000716|
European Ancestry|
23,535 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) : 0.26408
Spearman's ρ: 0.436
Age, sex, PCs(1-40)
PPM001521 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000717|
South Asian Ancestry|
7,319 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) : 0.11217
Spearman's ρ: 0.289
Age, sex, PCs(1-40)
PPM001556 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000718|
European Ancestry|
63,675 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) : 0.26409
Spearman's ρ: 0.446
Age, sex, PCs(1-40)
PPM001575 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000824|
European Ancestry|
2,097 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) Spearman's ρ: 0.159 Age, sex
PPM001576 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS000825|
European Ancestry|
1,987 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) Spearman's ρ: 0.138 Age, sex
PPM007365 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS007171|
African Ancestry|
6,086 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: LDL cholesterol : 0.05912 [0.048, 0.07024]
Incremental R2 (full-covars): 0.05479
PGS R2 (no covariates): 0.06663 [0.05492, 0.07834]
age, sex, UKB array type, Genotype PCs
PPM007366 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS007172|
East Asian Ancestry|
1,615 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: LDL cholesterol : 0.06107 [0.03908, 0.08305]
Incremental R2 (full-covars): 0.0498
PGS R2 (no covariates): 0.07486 [0.05087, 0.09885]
age, sex, UKB array type, Genotype PCs
PPM007367 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS007173|
European Ancestry|
23,728 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: LDL cholesterol : 0.10564 [0.09842, 0.11286]
Incremental R2 (full-covars): 0.096
PGS R2 (no covariates): 0.11974 [0.11218, 0.12731]
age, sex, UKB array type, Genotype PCs
PPM007368 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS007174|
South Asian Ancestry|
7,407 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: LDL cholesterol : 0.05634 [0.04642, 0.06625]
Incremental R2 (full-covars): 0.02423
PGS R2 (no covariates): 0.03502 [0.02702, 0.04301]
age, sex, UKB array type, Genotype PCs
PPM007369 PGS000688
(snpnet.LDL_direct_adjstatins)
PSS007175|
European Ancestry|
64,356 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: LDL cholesterol : 0.09533 [0.09111, 0.09955]
Incremental R2 (full-covars): 0.08543
PGS R2 (no covariates): 0.10869 [0.10426, 0.11313]
age, sex, UKB array type, Genotype PCs
PPM001759 PGS000735
(PRS_PR)
PSS000905|
European Ancestry|
1,185 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Ajmaline-induced Type I Brugada syndrome electrocardiogram OR: 1.017 [1.013, 1.022]
PPM001754 PGS000735
(PRS_PR)
PSS000904|
European Ancestry|
1,257 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: PR slope β: 0.22 (0.08)
PPM001750 PGS000735
(PRS_PR)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Baseline PR in non SCN5A mutation carriers Correlation coefficent (r): 0.23
PPM001752 PGS000735
(PRS_PR)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: PR slope in non SCN5A mutation carriers β: 0.16 (0.08) Correlation coefficient (r): 0.09
PPM001760 PGS000736
(PRS_QRS)
PSS000905|
European Ancestry|
1,185 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Ajmaline-induced Type I Brugada syndrome electrocardiogram OR: 1.047 [1.031, 1.063]
PPM001753 PGS000736
(PRS_QRS)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: QRS slope in non SCN5A mutation carriers β: 0.93 (0.2) Correlation coefficient (r): 0.14
PPM001751 PGS000736
(PRS_QRS)
PSS000906|
European Ancestry|
1,193 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: Baseline QRS in non SCN5A mutation carriers Correlation coefficent (r): 0.15
PPM001755 PGS000736
(PRS_QRS)
PSS000904|
European Ancestry|
1,257 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: QRS slope β: 0.8 (0.22)
PPM001756 PGS000736
(PRS_QRS)
PSS000903|
European Ancestry|
295 individuals
PGP000144 |
Tadros R et al. Eur Heart J (2019)
Reported Trait: QRS slope β: 0.8 (0.22) Age, SCN5A mutation
PPM001976 PGS000768
(PRS_QT)
PSS000987|
European Ancestry|
9,457 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome β: 0.322 (0.03) Odds Ratio (OR, top 25% vs. bottom 25%): 2.27 [1.9, 2.7] PCs (1-10)
PPM001977 PGS000768
(PRS_QT)
PSS000987|
European Ancestry|
9,457 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals with a single rare variant in a major LQTS gene β: 0.277 (0.032) Odds Ratio (OR, top 25% vs. bottom 25%): 2.09 [1.74, 2.51] PCs (1-10)
PPM001978 PGS000768
(PRS_QT)
PSS000987|
European Ancestry|
9,457 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals without a single rare variant in a major LQTS gene β: 0.733 (0.09) Odds Ratio (OR, top 25% vs. bottom 25%): 5.0 [2.73, 9.17] PCs (1-10)
PPM001979 PGS000768
(PRS_QT)
PSS000988|
East Asian Ancestry|
2,089 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome β: 0.412 (0.055) Odds Ratio (OR, top 25% vs. bottom 25%): 2.9 [2.09, 4.04] PCs (1-10) Only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM001980 PGS000768
(PRS_QT)
PSS000988|
East Asian Ancestry|
2,089 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals with a single rare variant in a major LQTS gene β: 0.384 (0.058) Odds Ratio (OR, top 25% vs. bottom 25%): 2.41 [1.71, 3.4] PCs (1-10) Only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM001981 PGS000768
(PRS_QT)
PSS000988|
East Asian Ancestry|
2,089 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals without a single rare variant in a major LQTS gene β: 0.74 (0.129) Odds Ratio (OR, top 25% vs. bottom 25%): 12.6 [3.28, 41.67] PCs (1-10) Only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM001982 PGS000768
(PRS_QT)
PSS000989|
Multi-ancestry (including European)|
11,546 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome β: 0.343 (0.0263) Odds Ratio (OR, top 25% vs. bottom 25%): 2.52 [2.16, 2.94] PCs (1-10) For Japanese individuals only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM001983 PGS000768
(PRS_QT)
PSS000989|
Multi-ancestry (including European)|
11,546 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals with a single rare variant in a major LQTS gene β: 0.294 (0.028) Odds Ratio (OR, top 25% vs. bottom 25%): 2.23 [1.9, 2.62] PCs (1-10) For Japanese individuals only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM001984 PGS000768
(PRS_QT)
PSS000989|
Multi-ancestry (including European)|
11,546 individuals
PGP000175 |
Lahrouchi N et al. Circulation (2020)
Reported Trait: Long QT syndrome in individuals without a single rare variant in a major LQTS gene β: 0.735 (0.0738) Odds Ratio (OR, top 25% vs. bottom 25%): 6.13 [3.57, 10.52] PCs (1-10) For Japanese individuals only 60 of the 68 SNP PRS were utilised. rs17457880, rs17460657, rs4656345, rs10040989, rs9920, rs1296720, rs17763769, rs1805128 were not included due to INFO < 0.3 and rs12300631 was used as a proxy for rs3026445.
PPM012972 PGS000814
(GRS12_LDLc)
PSS009637|
Ancestry Not Reported|
1,519 individuals
PGP000311 |
Olmastroni E et al. J Am Heart Assoc (2022)
|Ext.
Reported Trait: Polygenic hypercholesterolemia AUROC: 0.59 [0.56, 0.62] Sensitivity (%, cutoff of 0.905): 78.0
Specificity (%, cutoff of 0.905): 36.0
PPM002202 PGS000814
(GRS12_LDLc)
PSS001072|
Ancestry Not Reported|
967 individuals
PGP000205 |
Rimbert A et al. Arterioscler Thromb Vasc Biol (2020)
|Ext.
Reported Trait: Liver steatosis Odds Ratio (OR, polygenic vs monogenic hypobetalipoproteinemia cases): 0.13 [0.1, 1.16] Age, sex
PPM002201 PGS000814
(GRS12_LDLc)
PSS001072|
Ancestry Not Reported|
967 individuals
PGP000205 |
Rimbert A et al. Arterioscler Thromb Vasc Biol (2020)
|Ext.
Reported Trait: Hypobetalipoproteinemia Percentage of cases with polygenic etiology (%): 34.0 Polygenic etiology = PRS<10th percentile
PPM002170 PGS000814
(GRS12_LDLc)
PSS001058|
European Ancestry|
3,020 individuals
PGP000200 |
Talmud PJ et al. Lancet (2013)
Reported Trait: Low-density lipoprotein cholesterol level >4.9mmol/L Risk Ratio (RR, top 10% vs bottom 10%): 4.17 [3.01, 5.78]
PPM002171 PGS000814
(GRS12_LDLc)
PSS001059|
European Ancestry|
3,660 individuals
PGP000200 |
Talmud PJ et al. Lancet (2013)
Reported Trait: Low-density lipoprotein cholesterol level >4.9mmol/L in individuals who have familial hypercholestrolaemia and no known mutation AUROC: 0.65 [0.62, 0.68]
PPM002168 PGS000814
(GRS12_LDLc)
PSS001058|
European Ancestry|
3,020 individuals
PGP000200 |
Talmud PJ et al. Lancet (2013)
Reported Trait: Low-density lipoprotein (LDL) cholesterol β: 0.33 [0.3, 0.37] : 0.11
PPM002169 PGS000814
(GRS12_LDLc)
PSS001058|
European Ancestry|
3,020 individuals
PGP000200 |
Talmud PJ et al. Lancet (2013)
Reported Trait: Low-density lipoprotein (LDL) cholesterol β: 0.34 [0.31, 0.38] Sex, age, lipid-lowering drug use, body-mass index, diabetes status, smoking status, blood pressure
PPM002503 PGS000814
(GRS12_LDLc)
PSS001124|
European Ancestry|
4,787 individuals
PGP000221 |
Leal LG et al. Mol Genet Genomic Med (2020)
|Ext.
Reported Trait: Low-density lipoprotein cholesterol AUROC: 0.65
PPM013054 PGS000814
(GRS12_LDLc)
PSS009666|
South Asian Ancestry|
7,016 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration : 0.049 [0.035, 0.063] Age, sex
PPM013055 PGS000814
(GRS12_LDLc)
PSS009668|
European Ancestry|
353,166 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration >4.9 mmol/L OR: 11.01 [10.08, 12.04]
PPM013056 PGS000814
(GRS12_LDLc)
PSS009667|
African Ancestry|
7,082 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration >4.9 mmol/L OR: 10.54 [5.29, 21.67]
PPM013057 PGS000814
(GRS12_LDLc)
PSS009666|
South Asian Ancestry|
7,016 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration >4.9 mmol/L OR: 6.64 [2.98, 15.22]
PPM013058 PGS000814
(GRS12_LDLc)
PSS009668|
European Ancestry|
353,166 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 1.76 [1.56, 1.99]
PPM013059 PGS000814
(GRS12_LDLc)
PSS009667|
African Ancestry|
7,082 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 2.26 [0.78, 7.22]
PPM013060 PGS000814
(GRS12_LDLc)
PSS009666|
South Asian Ancestry|
7,016 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 1.24 [0.62, 2.53]
PPM013061 PGS000814
(GRS12_LDLc)
PSS009668|
European Ancestry|
353,166 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 1.25 [1.13, 1.39]
PPM013062 PGS000814
(GRS12_LDLc)
PSS009667|
African Ancestry|
7,082 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 1.09 [0.48, 2.58]
PPM013063 PGS000814
(GRS12_LDLc)
PSS009666|
South Asian Ancestry|
7,016 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: Coronary heart disease OR: 1.98 [0.95, 4.25]
PPM013052 PGS000814
(GRS12_LDLc)
PSS009668|
European Ancestry|
353,166 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration : 0.108 [0.105, 0.111] Age, sex
PPM013053 PGS000814
(GRS12_LDLc)
PSS009667|
African Ancestry|
7,082 individuals
PGP000330 |
Gratton J et al. Front Genet (2022)
|Ext.
Reported Trait: LDL-C concentration : 0.105 [0.086, 0.124] Age, sex
PPM016205 PGS000814
(GRS12_LDLc)
PSS010056|
Greater Middle Eastern Ancestry|
6,140 individuals
PGP000406 |
Gandhi GD et al. J Transl Med (2022)
|Ext.
Reported Trait: Probable vs. unlikely dyslipidemia p: 0.0003
PPM016207 PGS000814
(GRS12_LDLc)
PSS010058|
Ancestry Not Reported|
237 individuals
PGP000408 |
Borg SÁ et al. Atheroscler Plus (2022)
|Ext.
Reported Trait: Coronary artery calcium score >0 in potential clinical FH cases Odds ratio (OR, >80 percentile vs <= 80 percentile): 8.05 [1.65, 39.29] Smoking, hypertension, waist circumference and lipoprotein(a)
PPM017045 PGS000814
(GRS12_LDLc)
PSS010104|
European Ancestry|
89,528 individuals
PGP000422 |
Vanhoye X et al. Transl Res (2022)
|Ext.
Reported Trait: LDL-c blood concentration β: 0.25 [0.25, 0.26] AUROC: 0.6503 [0.644, 0.657] : 0.1055 Age, BMI, sex, age
PPM002230 PGS000824
(LDL-C_PGS)
PSS001083|
Multi-ancestry (including European)|
2,531 individuals
PGP000210 |
Zubair N et al. Sci Rep (2019)
Reported Trait: Low density lipoprotein cholesterol : 0.111 Age at baseline, sex, enrollment channel, PCs(1-7), observation season, observation vendor
PPM002313 PGS000846
(LDL)
PSS001086|
European Ancestry|
3,194 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Autoimmune Diabetes OR: 1.02 [0.92, 1.13] PC1-10
PPM002316 PGS000846
(LDL)
PSS001085|
European Ancestry|
4,116 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Obesity-related Diabetes OR: 1.0 [0.94, 1.07] PC1-10
PPM002317 PGS000846
(LDL)
PSS001084|
European Ancestry|
5,597 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Age-Related Diabetes OR: 0.95 [0.9, 1.0] PC1-10
PPM002315 PGS000846
(LDL)
PSS001088|
European Ancestry|
3,869 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Resistant Diabetes OR: 0.92 [0.86, 0.99] PC1-10
PPM002314 PGS000846
(LDL)
PSS001087|
European Ancestry|
3,930 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Deficient Diabetes OR: 0.95 [0.89, 1.02] PC1-10
PPM002500 PGS000875
(PGS36_LDLc)
PSS001124|
European Ancestry|
4,787 individuals
PGP000221 |
Leal LG et al. Mol Genet Genomic Med (2020)
Reported Trait: Low-density lipoprotein cholesterol : 0.08 Age, gender, body mass index, ancestry differences captured by the first two components from multidimensional scaling
PPM002501 PGS000875
(PGS36_LDLc)
PSS001124|
European Ancestry|
4,787 individuals
PGP000221 |
Leal LG et al. Mol Genet Genomic Med (2020)
Reported Trait: Severe hypercholesterolemia Risk Ratio (RR, top 30% vs bottom 30%): 4.8 [2.6, 8.9]
PPM002502 PGS000875
(PGS36_LDLc)
PSS001124|
European Ancestry|
4,787 individuals
PGP000221 |
Leal LG et al. Mol Genet Genomic Med (2020)
Reported Trait: Low-density lipoprotein cholesterol AUROC: 0.67
PPM002576 PGS000886
(GLGC_2021_AFR_LDL_PRS_weights_PRS-CS)
PSS001153|
African Ancestry|
1,341 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.064 sex, batch, PC1-4, and birth year
PPM002628 PGS000886
(GLGC_2021_AFR_LDL_PRS_weights_PRS-CS)
PSS001163|
African Ancestry|
6,863 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.112 sex, batch, age at initial assessment, PCs1-4
PPM002577 PGS000886
(GLGC_2021_AFR_LDL_PRS_weights_PRS-CS)
PSS001154|
European Ancestry|
17,190 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.056 sex, batch, PC1-4, and birth year
PPM002545 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001146|
African Ancestry|
3,566 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.125 age, sex, PC1-3
PPM002557 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001149|
African Ancestry|
4,972 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.128 age, sex, PC1-6
PPM002560 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001150|
African Ancestry|
3,743 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.076 age, sex, and PC1-4
PPM002563 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001151|
South Asian Ancestry|
15,242 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Max LDL cholesterol : 0.069 age, sex, and PC1-10
PPM002568 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.051 age, sex, and recruitment area
PPM002574 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001153|
African Ancestry|
1,341 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.115 sex, batch, PC1-4, and birth year
PPM002575 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001154|
European Ancestry|
17,190 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.074 sex, batch, PC1-4, and birth year
PPM002584 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.148 sex, PC1-4, birth year, and mean age
PPM002585 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.063 sex, PC1-4, birth year, and mean age
PPM002587 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.071 sex, PC1-4, birth year, and mean age
PPM002616 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001160|
African Ancestry|
2,138 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.129 birth year, sex, and PC1-4
PPM002629 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001163|
African Ancestry|
6,863 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.175 sex, batch, age at initial assessment, PCs1-4
PPM002543 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001144|
African Ancestry|
4,273 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.118 age, sex, PC1-3
PPM002544 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001145|
African Ancestry|
707 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.101 age, sex, PC1-3
PPM002554 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001148|
African Ancestry|
1,745 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.085 age, sex, PC1-6
PPM002586 PGS000887
(GLGC_2021_AFR_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.103 sex, PC1-4, birth year, and mean age
PPM002624 PGS000888
(GLGC_2021_ALL_LDL_PRS_weights_PRS-CS)
PSS001162|
Multi-ancestry (including European)|
461,918 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.175 sex, batch, age at initial assessment, PCs1-4
PPM002588 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.162 sex, PC1-4, birth year, and mean age
PPM002589 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.1 sex, PC1-4, birth year, and mean age
PPM002590 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.158 sex, PC1-4, birth year, and mean age
PPM002546 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001144|
African Ancestry|
4,273 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.114 age, sex, PC1-3
PPM002547 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001145|
African Ancestry|
707 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.067 age, sex, PC1-3
PPM002548 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001146|
African Ancestry|
3,566 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.123 age, sex, PC1-3
PPM002552 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001147|
African Ancestry|
10,460 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.173 age, sex, PC1-6
PPM002555 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001148|
African Ancestry|
1,745 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.069 age, sex, PC1-6
PPM002558 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001149|
African Ancestry|
4,972 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.108 age, sex, PC1-6
PPM002561 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001150|
African Ancestry|
3,743 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.075 age, sex, and PC1-4
PPM002569 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.095 age, sex, and recruitment area
PPM002578 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001153|
African Ancestry|
1,341 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.122 sex, batch, PC1-4, and birth year
PPM002579 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001154|
European Ancestry|
17,190 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.13 sex, batch, PC1-4, and birth year
PPM002591 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.134 sex, PC1-4, birth year, and mean age
PPM002617 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001160|
African Ancestry|
2,138 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.132 birth year, sex, and PC1-4
PPM002625 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001162|
Multi-ancestry (including European)|
461,918 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.182 sex, batch, age at initial assessment, PCs1-4
PPM002564 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001151|
South Asian Ancestry|
15,242 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Max LDL cholesterol : 0.105 age, sex, and PC1-10
PPM002619 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS001161|
East Asian Ancestry|
28,217 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.098 sex, age, recruitment method, and PC1-20
PPM020883 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS011442|
European Ancestry|
564 individuals
PGP000599 |
Guarischi-Sousa R et al. Circ Genom Precis Med (2023)
|Ext.
Reported Trait: Raised coronary lesion OR: 1.42 [1.16, 1.73]
PPM020891 PGS000889
(GLGC_2021_ALL_LDL_PRS_weights_PT)
PSS011441|
African Ancestry|
504 individuals
PGP000599 |
Guarischi-Sousa R et al. Circ Genom Precis Med (2023)
|Ext.
Reported Trait: Raised coronary lesion OR: 1.18 [0.95, 1.47]
PPM002571 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.094 age, sex, and recruitment area
PPM002596 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.041 sex, PC1-4, birth year, and mean age
PPM002598 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.083 sex, PC1-4, birth year, and mean age
PPM002599 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.063 sex, PC1-4, birth year, and mean age
PPM002620 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001161|
East Asian Ancestry|
28,217 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.094 sex, age, recruitment method, and PC1-20
PPM002626 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001164|
East Asian Ancestry|
1,441 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.113 sex, batch, age at initial assessment, PCs1-4
PPM002597 PGS000890
(GLGC_2021_EAS_LDL_PRS_weights_PRS-CS)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.09 sex, PC1-4, birth year, and mean age
PPM002570 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.098 age, sex, and recruitment area
PPM002592 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.056 sex, PC1-4, birth year, and mean age
PPM002593 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.098 sex, PC1-4, birth year, and mean age
PPM002594 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.083 sex, PC1-4, birth year, and mean age
PPM002595 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.057 sex, PC1-4, birth year, and mean age
PPM002627 PGS000891
(GLGC_2021_EAS_LDL_PRS_weights_PT)
PSS001164|
East Asian Ancestry|
1,441 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.1 sex, batch, age at initial assessment, PCs1-4
PPM002549 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001144|
African Ancestry|
4,273 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.052 age, sex, PC1-3
PPM002550 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001145|
African Ancestry|
707 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.063 age, sex, PC1-3
PPM002551 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001146|
African Ancestry|
3,566 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.055 age, sex, PC1-3
PPM002553 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001147|
African Ancestry|
10,460 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.122 age, sex, PC1-6
PPM002556 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001148|
African Ancestry|
1,745 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.041 age, sex, PC1-6
PPM002559 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001149|
African Ancestry|
4,972 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.04 age, sex, PC1-6
PPM002562 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001150|
African Ancestry|
3,743 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.022 age, sex, and PC1-4
PPM002566 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001151|
South Asian Ancestry|
15,242 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Max LDL cholesterol : 0.088 age, sex, and PC1-10
PPM002573 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.064 age, sex, and recruitment area
PPM002582 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001153|
African Ancestry|
1,341 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.062 sex, batch, PC1-4, and birth year
PPM002583 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001154|
European Ancestry|
17,190 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.129 sex, batch, PC1-4, and birth year
PPM002604 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.04 sex, PC1-4, birth year, and mean age
PPM002605 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.067 sex, PC1-4, birth year, and mean age
PPM002606 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.153 sex, PC1-4, birth year, and mean age
PPM002607 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.114 sex, PC1-4, birth year, and mean age
PPM002618 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001160|
African Ancestry|
2,138 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.069 birth year, sex, and PC1-4
PPM002621 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001161|
East Asian Ancestry|
28,217 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.074 sex, age, recruitment method, and PC1-20
PPM002622 PGS000892
(GLGC_2021_EUR_LDL_PRS_weights_PRS-CS)
PSS001165|
European Ancestry|
389,158 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.182 sex, batch, age at initial assessment, PCs1-4
PPM002565 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001151|
South Asian Ancestry|
15,242 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Max LDL cholesterol : 0.096 age, sex, and PC1-10
PPM002580 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001153|
African Ancestry|
1,341 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.058 sex, batch, PC1-4, and birth year
PPM002581 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001154|
European Ancestry|
17,190 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.123 sex, batch, PC1-4, and birth year
PPM002600 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.042 sex, PC1-4, birth year, and mean age
PPM002601 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.066 sex, PC1-4, birth year, and mean age
PPM002602 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.152 sex, PC1-4, birth year, and mean age
PPM002603 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.106 sex, PC1-4, birth year, and mean age
PPM002623 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001165|
European Ancestry|
389,158 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.176 sex, batch, age at initial assessment, PCs1-4
PPM002572 PGS000893
(GLGC_2021_EUR_LDL_PRS_weights_PT)
PSS001152|
East Asian Ancestry|
118,260 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.071 age, sex, and recruitment area
PPM002632 PGS000894
(GLGC_2021_HIS_LDL_PRS_weights_PRS-CS)
PSS001155|
Hispanic or Latin American Ancestry|
360 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.023 sex, batch, PC1-4, and birth year
PPM002609 PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.079 sex, PC1-4, birth year, and mean age
PPM002610 PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.119 sex, PC1-4, birth year, and mean age
PPM002611 PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.102 sex, PC1-4, birth year, and mean age
PPM002633 PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PSS001155|
Hispanic or Latin American Ancestry|
360 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.088 sex, batch, PC1-4, and birth year
PPM002608 PGS000895
(GLGC_2021_HIS_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.1 sex, PC1-4, birth year, and mean age
PPM002630 PGS000896
(GLGC_2021_SAS_LDL_PRS_weights_PRS-CS)
PSS001166|
South Asian Ancestry|
6,814 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.04 sex, batch, age at initial assessment, PCs1-4
PPM002567 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001151|
South Asian Ancestry|
15,242 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Max LDL cholesterol : 0.077 age, sex, and PC1-10
PPM002612 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001156|
African Ancestry|
18,251 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.076 sex, PC1-4, birth year, and mean age
PPM002613 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001157|
Additional Asian Ancestries|
4,155 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.067 sex, PC1-4, birth year, and mean age
PPM002614 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001158|
European Ancestry|
68,381 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.101 sex, PC1-4, birth year, and mean age
PPM002615 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001159|
Hispanic or Latin American Ancestry|
7,669 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Mean LDL cholesterol : 0.069 sex, PC1-4, birth year, and mean age
PPM002631 PGS000897
(GLGC_2021_SAS_LDL_PRS_weights_PT)
PSS001166|
South Asian Ancestry|
6,814 individuals
PGP000230 |
Graham SE et al. Nature (2021)
Reported Trait: Baseline LDL cholesterol : 0.058 sex, batch, age at initial assessment, PCs1-4
PPM002666 PGS000904
(PRS582_PR)
PSS001175|
European Ancestry|
309,269 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrial fibrillation OR: 0.95
β: -0.047 (0.009)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002667 PGS000904
(PRS582_PR)
PSS001178|
European Ancestry|
290,252 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Distal conduction disease OR: 1.11
β: 0.103 (0.019)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002668 PGS000904
(PRS582_PR)
PSS001176|
European Ancestry|
309,041 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrioventricular preexcitation OR: 0.85
β: -0.168 (0.057)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002669 PGS000904
(PRS582_PR)
PSS001179|
European Ancestry|
309,241 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Implantable cardioverter defibrillator OR: 1.09
β: 0.086 (0.04)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002670 PGS000904
(PRS582_PR)
PSS001180|
European Ancestry|
309,246 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Mitral valve prolapse OR: 1.1
β: 0.093 (0.044)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002671 PGS000904
(PRS582_PR)
PSS001181|
European Ancestry|
305,471 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Non-ischemic cardiomyopathy OR: 0.95
β: -0.051 (0.024)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002672 PGS000904
(PRS582_PR)
PSS001182|
European Ancestry|
309,270 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Pacemaker OR: 1.06
β: 0.062 (0.016)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002673 PGS000904
(PRS582_PR)
PSS001183|
European Ancestry|
309,255 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Valve disease OR: 1.03
β: 0.03 (0.013)
Baseline age, sex, genotyping array, trait-related principal components Only 581 SNPs from the 582 SNP PRS were utilised. 1 SNP was not included due to low imputation quality.
PPM002674 PGS000905
(PRS743_PR)
PSS001175|
European Ancestry|
309,269 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrial fibrillation OR: 0.94
β: -0.058 (0.009)
Baseline age, sex, genotyping array, trait-related principal components
PPM002675 PGS000905
(PRS743_PR)
PSS001178|
European Ancestry|
290,252 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Distal conduction disease β: 0.105 (0.019)
OR: 1.11
Baseline age, sex, genotyping array, trait-related principal components
PPM002676 PGS000905
(PRS743_PR)
PSS001176|
European Ancestry|
309,041 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Atrioventricular preexcitation OR: 0.83
β: -0.191 (0.057)
Baseline age, sex, genotyping array, trait-related principal components
PPM002677 PGS000905
(PRS743_PR)
PSS001177|
European Ancestry|
309,246 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Coronary artery disease OR: 0.99
β: -0.014 (0.007)
Baseline age, sex, genotyping array, trait-related principal components
PPM002678 PGS000905
(PRS743_PR)
PSS001182|
European Ancestry|
309,270 individuals
PGP000236 |
Ntalla I et al. Nat Commun (2020)
Reported Trait: Pacemaker OR: 1.06
β: 0.056 (0.016)
Baseline age, sex, genotyping array, trait-related principal components
PPM008674 PGS001233
(GBE_INI102)
PSS004781|
African Ancestry|
6,409 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (AR) : 0.02255 [0.01542, 0.02969]
Incremental R2 (full-covars): 0.0174
PGS R2 (no covariates): 0.01806 [0.01165, 0.02447]
age, sex, UKB array type, Genotype PCs
PPM008675 PGS001233
(GBE_INI102)
PSS004782|
East Asian Ancestry|
1,634 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (AR) : 0.06312 [0.04082, 0.08543]
Incremental R2 (full-covars): 0.04857
PGS R2 (no covariates): 0.05506 [0.03405, 0.07607]
age, sex, UKB array type, Genotype PCs
PPM008676 PGS001233
(GBE_INI102)
PSS004783|
European Ancestry|
23,727 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (AR) : 0.06698 [0.06098, 0.07297]
Incremental R2 (full-covars): 0.06128
PGS R2 (no covariates): 0.06178 [0.05599, 0.06757]
age, sex, UKB array type, Genotype PCs
PPM008677 PGS001233
(GBE_INI102)
PSS004784|
South Asian Ancestry|
7,640 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (AR) : 0.05587 [0.04599, 0.06575]
Incremental R2 (full-covars): 0.04337
PGS R2 (no covariates): 0.04305 [0.03426, 0.05184]
age, sex, UKB array type, Genotype PCs
PPM008678 PGS001233
(GBE_INI102)
PSS004785|
European Ancestry|
63,825 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (AR) : 0.07415 [0.07034, 0.07795]
Incremental R2 (full-covars): 0.06338
PGS R2 (no covariates): 0.06346 [0.0599, 0.06702]
age, sex, UKB array type, Genotype PCs
PPM005325 PGS001375
(GBE_INI22426)
PSS004996|
African Ancestry|
192 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ave. heart rate : 0.06508 [0.05349, 0.07667]
Incremental R2 (full-covars): 0.00545
PGS R2 (no covariates): 0.00196 [-0.00019, 0.00411]
age, sex, UKB array type, Genotype PCs
PPM005326 PGS001375
(GBE_INI22426)
PSS004997|
East Asian Ancestry|
110 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ave. heart rate : 0.10436 [0.07694, 0.13177]
Incremental R2 (full-covars): -0.00244
PGS R2 (no covariates): 0.00402 [-0.00196, 0.01001]
age, sex, UKB array type, Genotype PCs
PPM005327 PGS001375
(GBE_INI22426)
PSS004998|
European Ancestry|
1,708 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ave. heart rate : 0.02859 [0.02451, 0.03267]
Incremental R2 (full-covars): 0.00535
PGS R2 (no covariates): 0.0045 [0.00284, 0.00616]
age, sex, UKB array type, Genotype PCs
PPM005328 PGS001375
(GBE_INI22426)
PSS004999|
South Asian Ancestry|
319 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ave. heart rate : 0.05234 [0.04274, 0.06194]
Incremental R2 (full-covars): 0.00014
PGS R2 (no covariates): 0.00114 [-0.00035, 0.00263]
age, sex, UKB array type, Genotype PCs
PPM005329 PGS001375
(GBE_INI22426)
PSS005000|
European Ancestry|
5,528 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ave. heart rate : 0.01988 [0.01779, 0.02196]
Incremental R2 (full-covars): 0.00417
PGS R2 (no covariates): 0.00374 [0.00282, 0.00466]
age, sex, UKB array type, Genotype PCs
PPM005316 PGS001412
(GBE_INI22420)
PSS004987|
East Asian Ancestry|
110 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV ejection fraction : 0.21638 [0.18183, 0.25092]
Incremental R2 (full-covars): 0.00243
PGS R2 (no covariates): 0.0051 [-0.00163, 0.01183]
age, sex, UKB array type, Genotype PCs
PPM005317 PGS001412
(GBE_INI22420)
PSS004988|
European Ancestry|
1,708 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV ejection fraction : 0.07182 [0.06564, 0.07799]
Incremental R2 (full-covars): 0.0014
PGS R2 (no covariates): 0.00189 [0.00081, 0.00297]
age, sex, UKB array type, Genotype PCs
PPM005315 PGS001412
(GBE_INI22420)
PSS004986|
African Ancestry|
192 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV ejection fraction : 0.07902 [0.06643, 0.0916]
Incremental R2 (full-covars): 0.0065
PGS R2 (no covariates): 0.00921 [0.00459, 0.01383]
age, sex, UKB array type, Genotype PCs
PPM005318 PGS001412
(GBE_INI22420)
PSS004989|
South Asian Ancestry|
319 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV ejection fraction : 0.06719 [0.05648, 0.07789]
Incremental R2 (full-covars): 0.00348
PGS R2 (no covariates): 0.00252 [0.00031, 0.00474]
age, sex, UKB array type, Genotype PCs
PPM005319 PGS001412
(GBE_INI22420)
PSS004990|
European Ancestry|
5,528 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV ejection fraction : 0.04862 [0.04545, 0.05179]
Incremental R2 (full-covars): 0.00384
PGS R2 (no covariates): 0.00375 [0.00283, 0.00468]
age, sex, UKB array type, Genotype PCs
PPM005320 PGS001413
(GBE_INI22423)
PSS004991|
African Ancestry|
192 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV stroke volume : 0.2894 [0.27082, 0.30798]
Incremental R2 (full-covars): 0.00042
PGS R2 (no covariates): 2e-05 [-0.00021, 0.00026]
age, sex, UKB array type, Genotype PCs
PPM005321 PGS001413
(GBE_INI22423)
PSS004992|
East Asian Ancestry|
110 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV stroke volume : 0.24626 [0.21082, 0.28171]
Incremental R2 (full-covars): 0.00076
PGS R2 (no covariates): 0.00073 [-0.00183, 0.00328]
age, sex, UKB array type, Genotype PCs
PPM005322 PGS001413
(GBE_INI22423)
PSS004993|
European Ancestry|
1,708 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV stroke volume : 0.27363 [0.26419, 0.28306]
Incremental R2 (full-covars): -0.00044
PGS R2 (no covariates): 8e-05 [-0.00014, 0.00031]
age, sex, UKB array type, Genotype PCs
PPM005323 PGS001413
(GBE_INI22423)
PSS004994|
South Asian Ancestry|
319 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV stroke volume : 0.21177 [0.19571, 0.22783]
Incremental R2 (full-covars): -0.00201
PGS R2 (no covariates): 0.00017 [-0.00041, 0.00074]
age, sex, UKB array type, Genotype PCs
PPM005324 PGS001413
(GBE_INI22423)
PSS004995|
European Ancestry|
5,528 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: LV stroke volume : 0.20777 [0.20231, 0.21322]
Incremental R2 (full-covars): 0.00246
PGS R2 (no covariates): 0.00431 [0.00333, 0.0053]
age, sex, UKB array type, Genotype PCs
PPM007125 PGS001519
(GBE_INI4199)
PSS007341|
African Ancestry|
3,863 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of pulse wave notch : 0.02994 [0.02178, 0.0381]
Incremental R2 (full-covars): 0.00194
PGS R2 (no covariates): 0.00226 [-0.00004, 0.00457]
age, sex, UKB array type, Genotype PCs
PPM007126 PGS001519
(GBE_INI4199)
PSS007342|
East Asian Ancestry|
807 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of pulse wave notch : 0.02934 [0.01358, 0.04509]
Incremental R2 (full-covars): 0.0026
PGS R2 (no covariates): 0.00283 [-0.0022, 0.00785]
age, sex, UKB array type, Genotype PCs
PPM007127 PGS001519
(GBE_INI4199)
PSS007343|
European Ancestry|
11,021 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of pulse wave notch : 0.02545 [0.02159, 0.02931]
Incremental R2 (full-covars): 0.00502
PGS R2 (no covariates): 0.00515 [0.00337, 0.00692]
age, sex, UKB array type, Genotype PCs
PPM007128 PGS001519
(GBE_INI4199)
PSS007344|
South Asian Ancestry|
5,226 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of pulse wave notch : 0.04794 [0.03871, 0.05717]
Incremental R2 (full-covars): 0.00501
PGS R2 (no covariates): 0.0043 [0.00141, 0.00719]
age, sex, UKB array type, Genotype PCs
PPM007129 PGS001519
(GBE_INI4199)
PSS007345|
European Ancestry|
26,777 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of pulse wave notch : 0.03558 [0.03284, 0.03833]
Incremental R2 (full-covars): 0.00809
PGS R2 (no covariates): 0.00826 [0.0069, 0.00962]
age, sex, UKB array type, Genotype PCs
PPM007120 PGS001520
(GBE_INI4198)
PSS007336|
African Ancestry|
3,863 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of the pulse wave peak : 0.05763 [0.04663, 0.06862]
Incremental R2 (full-covars): -0.00367
PGS R2 (no covariates): 3e-05 [-0.00023, 0.00029]
age, sex, UKB array type, Genotype PCs
PPM007121 PGS001520
(GBE_INI4198)
PSS007337|
East Asian Ancestry|
807 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of the pulse wave peak : 0.0542 [0.03334, 0.07507]
Incremental R2 (full-covars): -0.00065
PGS R2 (no covariates): 0.00041 [-0.0015, 0.00231]
age, sex, UKB array type, Genotype PCs
PPM007122 PGS001520
(GBE_INI4198)
PSS007338|
European Ancestry|
11,021 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of the pulse wave peak : 0.09762 [0.09061, 0.10462]
Incremental R2 (full-covars): 0.00071
PGS R2 (no covariates): 0.00137 [0.00045, 0.00229]
age, sex, UKB array type, Genotype PCs
PPM007123 PGS001520
(GBE_INI4198)
PSS007339|
South Asian Ancestry|
5,226 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of the pulse wave peak : 0.03074 [0.02321, 0.03826]
Incremental R2 (full-covars): 0.0
PGS R2 (no covariates): 0.00076 [-0.00046, 0.00198]
age, sex, UKB array type, Genotype PCs
PPM007124 PGS001520
(GBE_INI4198)
PSS007340|
European Ancestry|
26,777 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Position of the pulse wave peak : 0.07148 [0.06773, 0.07522]
Incremental R2 (full-covars): 0.00342
PGS R2 (no covariates): 0.00338 [0.00251, 0.00426]
age, sex, UKB array type, Genotype PCs
PPM005300 PGS001521
(GBE_INI22330)
PSS004966|
African Ancestry|
120 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.14397 [0.12818, 0.15975]
Incremental R2 (full-covars): 0.00024
PGS R2 (no covariates): 0.01367 [0.00807, 0.01928]
age, sex, UKB array type, Genotype PCs
PPM005301 PGS001521
(GBE_INI22330)
PSS004967|
East Asian Ancestry|
68 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.2664 [0.23052, 0.30228]
Incremental R2 (full-covars): -0.00945
PGS R2 (no covariates): 0.00783 [-0.00049, 0.01615]
age, sex, UKB array type, Genotype PCs
PPM005302 PGS001521
(GBE_INI22330)
PSS004968|
European Ancestry|
834 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.10209 [0.09497, 0.10922]
Incremental R2 (full-covars): 0.04534
PGS R2 (no covariates): 0.05149 [0.04615, 0.05684]
age, sex, UKB array type, Genotype PCs
PPM005303 PGS001521
(GBE_INI22330)
PSS004969|
South Asian Ancestry|
193 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.13589 [0.12179, 0.15]
Incremental R2 (full-covars): -0.01928
PGS R2 (no covariates): 0.00031 [-0.00047, 0.00108]
age, sex, UKB array type, Genotype PCs
PPM005304 PGS001521
(GBE_INI22330)
PSS004970|
European Ancestry|
3,353 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: PQ interval : 0.07982 [0.0759, 0.08375]
Incremental R2 (full-covars): 0.02363
PGS R2 (no covariates): 0.02488 [0.02256, 0.0272]
age, sex, UKB array type, Genotype PCs
PPM007115 PGS001523
(GBE_INI4194)
PSS007331|
African Ancestry|
3,863 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate : 0.01921 [0.0126, 0.02582]
Incremental R2 (full-covars): 0.01159
PGS R2 (no covariates): 0.01226 [0.00694, 0.01757]
age, sex, UKB array type, Genotype PCs
PPM007116 PGS001523
(GBE_INI4194)
PSS007332|
East Asian Ancestry|
807 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate : 0.0379 [0.02015, 0.05565]
Incremental R2 (full-covars): 0.02204
PGS R2 (no covariates): 0.02422 [0.00983, 0.03861]
age, sex, UKB array type, Genotype PCs
PPM007117 PGS001523
(GBE_INI4194)
PSS007333|
European Ancestry|
11,021 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate : 0.03431 [0.02987, 0.03876]
Incremental R2 (full-covars): 0.03005
PGS R2 (no covariates): 0.03012 [0.02594, 0.03431]
age, sex, UKB array type, Genotype PCs
PPM007118 PGS001523
(GBE_INI4194)
PSS007334|
South Asian Ancestry|
5,226 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate : 0.04886 [0.03955, 0.05817]
Incremental R2 (full-covars): 0.0265
PGS R2 (no covariates): 0.02722 [0.02012, 0.03433]
age, sex, UKB array type, Genotype PCs
PPM007119 PGS001523
(GBE_INI4194)
PSS007335|
European Ancestry|
26,777 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate : 0.04573 [0.04265, 0.04881]
Incremental R2 (full-covars): 0.03275
PGS R2 (no covariates): 0.033 [0.03034, 0.03565]
age, sex, UKB array type, Genotype PCs
PPM007225 PGS001524
(GBE_INI95)
PSS007496|
African Ancestry|
209 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (during blood-pressure measurement) : 0.06125 [0.04996, 0.07254]
Incremental R2 (full-covars): -0.01473
PGS R2 (no covariates): 0.00497 [0.00156, 0.00838]
age, sex, UKB array type, Genotype PCs
PPM007226 PGS001524
(GBE_INI95)
PSS007497|
East Asian Ancestry|
141 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (during blood-pressure measurement) : 0.0637 [0.04131, 0.08609]
Incremental R2 (full-covars): 0.00078
PGS R2 (no covariates): 0.00983 [0.00052, 0.01913]
age, sex, UKB array type, Genotype PCs
PPM007227 PGS001524
(GBE_INI95)
PSS007498|
European Ancestry|
2,103 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (during blood-pressure measurement) : 0.02805 [0.02401, 0.0321]
Incremental R2 (full-covars): 0.0191
PGS R2 (no covariates): 0.02008 [0.01663, 0.02353]
age, sex, UKB array type, Genotype PCs
PPM007228 PGS001524
(GBE_INI95)
PSS007499|
South Asian Ancestry|
381 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (during blood-pressure measurement) : 0.0378 [0.02951, 0.04608]
Incremental R2 (full-covars): 0.00144
PGS R2 (no covariates): 0.00428 [0.0014, 0.00717]
age, sex, UKB array type, Genotype PCs
PPM007229 PGS001524
(GBE_INI95)
PSS007500|
European Ancestry|
6,590 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Pulse rate (during blood-pressure measurement) : 0.01671 [0.0148, 0.01863]
Incremental R2 (full-covars): 0.00704
PGS R2 (no covariates): 0.00724 [0.00596, 0.00851]
age, sex, UKB array type, Genotype PCs
PPM005235 PGS001525
(GBE_INI12340)
PSS004806|
African Ancestry|
203 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QRS duration : 0.20692 [0.18939, 0.22446]
Incremental R2 (full-covars): 0.01284
PGS R2 (no covariates): 0.02209 [0.01502, 0.02915]
age, sex, UKB array type, Genotype PCs
PPM005236 PGS001525
(GBE_INI12340)
PSS004807|
East Asian Ancestry|
102 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QRS duration : 0.199 [0.16514, 0.23286]
Incremental R2 (full-covars): 0.01328
PGS R2 (no covariates): 0.00454 [-0.00181, 0.0109]
age, sex, UKB array type, Genotype PCs
PPM005237 PGS001525
(GBE_INI12340)
PSS004808|
European Ancestry|
1,601 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QRS duration : 0.1428 [0.13475, 0.15084]
Incremental R2 (full-covars): 0.02153
PGS R2 (no covariates): 0.01977 [0.01635, 0.02319]
age, sex, UKB array type, Genotype PCs
PPM005238 PGS001525
(GBE_INI12340)
PSS004809|
South Asian Ancestry|
315 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QRS duration : 0.20988 [0.19385, 0.2259]
Incremental R2 (full-covars): 0.00738
PGS R2 (no covariates): 0.00578 [0.00243, 0.00912]
age, sex, UKB array type, Genotype PCs
PPM005239 PGS001525
(GBE_INI12340)
PSS004810|
European Ancestry|
5,223 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QRS duration : 0.11697 [0.11241, 0.12153]
Incremental R2 (full-covars): 0.01872
PGS R2 (no covariates): 0.02164 [0.01947, 0.02382]
age, sex, UKB array type, Genotype PCs
PPM005305 PGS001526
(GBE_INI22331)
PSS004971|
African Ancestry|
120 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QT interval : 0.07804 [0.06552, 0.09056]
Incremental R2 (full-covars): -0.0033
PGS R2 (no covariates): 0.00046 [-0.00058, 0.0015]
age, sex, UKB array type, Genotype PCs
PPM005306 PGS001526
(GBE_INI22331)
PSS004972|
East Asian Ancestry|
68 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QT interval : 0.32528 [0.28882, 0.36175]
Incremental R2 (full-covars): 0.0416
PGS R2 (no covariates): 0.07506 [0.05104, 0.09907]
age, sex, UKB array type, Genotype PCs
PPM005307 PGS001526
(GBE_INI22331)
PSS004973|
European Ancestry|
872 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QT interval : 0.05819 [0.05255, 0.06383]
Incremental R2 (full-covars): 0.02543
PGS R2 (no covariates): 0.02774 [0.02372, 0.03176]
age, sex, UKB array type, Genotype PCs
PPM005308 PGS001526
(GBE_INI22331)
PSS004974|
South Asian Ancestry|
201 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QT interval : 0.06747 [0.05675, 0.0782]
Incremental R2 (full-covars): -0.0012
PGS R2 (no covariates): 0.0053 [0.0021, 0.00851]
age, sex, UKB array type, Genotype PCs
PPM005309 PGS001526
(GBE_INI22331)
PSS004975|
European Ancestry|
3,523 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QT interval : 0.01777 [0.01579, 0.01974]
Incremental R2 (full-covars): 0.01493
PGS R2 (no covariates): 0.01503 [0.01321, 0.01685]
age, sex, UKB array type, Genotype PCs
PPM005310 PGS001527
(GBE_INI22332)
PSS004976|
African Ancestry|
120 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QTC interval : 0.19276 [0.17553, 0.20998]
Incremental R2 (full-covars): 0.00351
PGS R2 (no covariates): 0.00541 [0.00185, 0.00897]
age, sex, UKB array type, Genotype PCs
PPM005311 PGS001527
(GBE_INI22332)
PSS004977|
East Asian Ancestry|
68 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QTC interval : 0.21617 [0.18164, 0.25071]
Incremental R2 (full-covars): 0.01252
PGS R2 (no covariates): 0.00397 [-0.00198, 0.00991]
age, sex, UKB array type, Genotype PCs
PPM005312 PGS001527
(GBE_INI22332)
PSS004978|
European Ancestry|
872 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QTC interval : 0.07278 [0.06657, 0.079]
Incremental R2 (full-covars): 0.01137
PGS R2 (no covariates): 0.00935 [0.00697, 0.01173]
age, sex, UKB array type, Genotype PCs
PPM005313 PGS001527
(GBE_INI22332)
PSS004979|
South Asian Ancestry|
201 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QTC interval : 0.07001 [0.05911, 0.0809]
Incremental R2 (full-covars): -0.00126
PGS R2 (no covariates): 0.00213 [0.00009, 0.00417]
age, sex, UKB array type, Genotype PCs
PPM005314 PGS001527
(GBE_INI22332)
PSS004980|
European Ancestry|
3,523 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: QTC interval : 0.07628 [0.07243, 0.08013]
Incremental R2 (full-covars): 0.01976
PGS R2 (no covariates): 0.02423 [0.02193, 0.02652]
age, sex, UKB array type, Genotype PCs
PPM009988 PGS001888
(portability-PLR_apoA)
PSS009384|
European Ancestry|
17,339 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4103 [0.3978, 0.4226] sex, age, birth date, deprivation index, 16 PCs
PPM009990 PGS001888
(portability-PLR_apoA)
PSS008712|
European Ancestry|
5,765 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4138 [0.3921, 0.435] sex, age, birth date, deprivation index, 16 PCs
PPM009991 PGS001888
(portability-PLR_apoA)
PSS008486|
Greater Middle Eastern Ancestry|
1,033 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.3636 [0.3089, 0.4158] sex, age, birth date, deprivation index, 16 PCs
PPM009992 PGS001888
(portability-PLR_apoA)
PSS008264|
South Asian Ancestry|
5,470 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.3639 [0.3406, 0.3867] sex, age, birth date, deprivation index, 16 PCs
PPM009993 PGS001888
(portability-PLR_apoA)
PSS008042|
East Asian Ancestry|
1,543 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.35 [0.3051, 0.3933] sex, age, birth date, deprivation index, 16 PCs
PPM009994 PGS001888
(portability-PLR_apoA)
PSS007828|
African Ancestry|
2,151 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.2555 [0.2154, 0.2948] sex, age, birth date, deprivation index, 16 PCs
PPM009995 PGS001888
(portability-PLR_apoA)
PSS008932|
African Ancestry|
3,389 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.2218 [0.1894, 0.2536] sex, age, birth date, deprivation index, 16 PCs
PPM009989 PGS001888
(portability-PLR_apoA)
PSS009158|
European Ancestry|
3,563 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4163 [0.3887, 0.4432] sex, age, birth date, deprivation index, 16 PCs
PPM010099 PGS001902
(portability-PLR_ECG_P_duration)
PSS009365|
European Ancestry|
1,622 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0975 [0.0487, 0.1458] sex, age, birth date, deprivation index, 16 PCs
PPM010100 PGS001902
(portability-PLR_ECG_P_duration)
PSS009139|
European Ancestry|
310 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1126 [-0.0026, 0.2249] sex, age, birth date, deprivation index, 16 PCs
PPM010101 PGS001902
(portability-PLR_ECG_P_duration)
PSS008693|
European Ancestry|
474 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0776 [-0.0146, 0.1684] sex, age, birth date, deprivation index, 16 PCs
PPM010102 PGS001902
(portability-PLR_ECG_P_duration)
PSS008467|
Greater Middle Eastern Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): -0.1487 [-0.4886, 0.2303] sex, age, birth date, deprivation index, 16 PCs
PPM010103 PGS001902
(portability-PLR_ECG_P_duration)
PSS008247|
South Asian Ancestry|
299 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0714 [-0.0464, 0.1872] sex, age, birth date, deprivation index, 16 PCs
PPM010104 PGS001902
(portability-PLR_ECG_P_duration)
PSS008025|
East Asian Ancestry|
134 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.2031 [0.0199, 0.3731] sex, age, birth date, deprivation index, 16 PCs
PPM010105 PGS001902
(portability-PLR_ECG_P_duration)
PSS007811|
African Ancestry|
76 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.2803 [0.0188, 0.5059] sex, age, birth date, deprivation index, 16 PCs
PPM010106 PGS001902
(portability-PLR_ECG_P_duration)
PSS008915|
African Ancestry|
138 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1764 [-0.0045, 0.3461] sex, age, birth date, deprivation index, 16 PCs
PPM010108 PGS001903
(portability-PLR_ECG_PP_interval)
PSS009137|
European Ancestry|
191 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.1015 [-0.0493, 0.2478] sex, age, birth date, deprivation index, 16 PCs
PPM010109 PGS001903
(portability-PLR_ECG_PP_interval)
PSS008691|
European Ancestry|
225 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.1429 [0.006, 0.2745] sex, age, birth date, deprivation index, 16 PCs
PPM010110 PGS001903
(portability-PLR_ECG_PP_interval)
PSS008465|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): -0.3367 [-0.9398, 0.7761] sex, age, birth date, deprivation index, 16 PCs
PPM010111 PGS001903
(portability-PLR_ECG_PP_interval)
PSS008245|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0817 [-0.0824, 0.2415] sex, age, birth date, deprivation index, 16 PCs
PPM010113 PGS001903
(portability-PLR_ECG_PP_interval)
PSS007809|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0201 [-0.349, 0.3838] sex, age, birth date, deprivation index, 16 PCs
PPM010114 PGS001903
(portability-PLR_ECG_PP_interval)
PSS008913|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.2346 [-0.0787, 0.5057] sex, age, birth date, deprivation index, 16 PCs
PPM010107 PGS001903
(portability-PLR_ECG_PP_interval)
PSS009363|
European Ancestry|
1,036 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.1051 [0.0439, 0.1655] sex, age, birth date, deprivation index, 16 PCs
PPM010112 PGS001903
(portability-PLR_ECG_PP_interval)
PSS008023|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.144 [-0.1314, 0.3987] sex, age, birth date, deprivation index, 16 PCs
PPM010115 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS009364|
European Ancestry|
992 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.173 [0.1113, 0.2333] sex, age, birth date, deprivation index, 16 PCs
PPM010116 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS009138|
European Ancestry|
181 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1945 [0.041, 0.3389] sex, age, birth date, deprivation index, 16 PCs
PPM010117 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008692|
European Ancestry|
217 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2467 [0.1108, 0.3736] sex, age, birth date, deprivation index, 16 PCs
PPM010118 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008466|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2876 [-0.7969, 0.9331] sex, age, birth date, deprivation index, 16 PCs
PPM010119 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008246|
South Asian Ancestry|
159 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.09 [-0.0776, 0.2527] sex, age, birth date, deprivation index, 16 PCs
PPM010120 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008024|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.0694 [-0.2047, 0.3335] sex, age, birth date, deprivation index, 16 PCs
PPM010121 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS007810|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.212 [-0.1676, 0.5368] sex, age, birth date, deprivation index, 16 PCs
PPM010122 PGS001904
(portability-PLR_ECG_PQ_interval)
PSS008914|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2774 [-0.0331, 0.539] sex, age, birth date, deprivation index, 16 PCs
PPM010124 PGS001905
(portability-PLR_ECG_QT_interval)
PSS009141|
European Ancestry|
193 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.1764 [0.0279, 0.3172] sex, age, birth date, deprivation index, 16 PCs
PPM010125 PGS001905
(portability-PLR_ECG_QT_interval)
PSS008695|
European Ancestry|
226 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.2353 [0.1019, 0.3604] sex, age, birth date, deprivation index, 16 PCs
PPM010126 PGS001905
(portability-PLR_ECG_QT_interval)
PSS008469|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): -0.1488 [-0.8569, 0.7538] sex, age, birth date, deprivation index, 16 PCs
PPM010127 PGS001905
(portability-PLR_ECG_QT_interval)
PSS008249|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): -0.0176 [-0.18, 0.1459] sex, age, birth date, deprivation index, 16 PCs
PPM010128 PGS001905
(portability-PLR_ECG_QT_interval)
PSS008027|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.325 [0.06, 0.5472] sex, age, birth date, deprivation index, 16 PCs
PPM010129 PGS001905
(portability-PLR_ECG_QT_interval)
PSS007813|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): -0.034 [-0.3956, 0.3367] sex, age, birth date, deprivation index, 16 PCs
PPM010130 PGS001905
(portability-PLR_ECG_QT_interval)
PSS008917|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.1053 [-0.2091, 0.4] sex, age, birth date, deprivation index, 16 PCs
PPM010123 PGS001905
(portability-PLR_ECG_QT_interval)
PSS009367|
European Ancestry|
1,042 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.1488 [0.0883, 0.2082] sex, age, birth date, deprivation index, 16 PCs
PPM010131 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS009366|
European Ancestry|
1,040 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2353 [0.1765, 0.2925] sex, age, birth date, deprivation index, 16 PCs
PPM010132 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS009140|
European Ancestry|
191 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2876 [0.1438, 0.4196] sex, age, birth date, deprivation index, 16 PCs
PPM010133 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS008694|
European Ancestry|
225 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.1528 [0.0161, 0.2839] sex, age, birth date, deprivation index, 16 PCs
PPM010135 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS008248|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): -0.0987 [-0.2576, 0.0654] sex, age, birth date, deprivation index, 16 PCs
PPM010136 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS008026|
East Asian Ancestry|
72 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2317 [-0.044, 0.4746] sex, age, birth date, deprivation index, 16 PCs
PPM010137 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS007812|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): -0.0515 [-0.4103, 0.321] sex, age, birth date, deprivation index, 16 PCs
PPM010138 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS008916|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.1979 [-0.1168, 0.4766] sex, age, birth date, deprivation index, 16 PCs
PPM010134 PGS001906
(portability-PLR_ECG_QTC_interval)
PSS008468|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.5901 [-0.425, 0.9478] sex, age, birth date, deprivation index, 16 PCs
PPM010139 PGS001907
(portability-PLR_ECG_RR_interval)
PSS009368|
European Ancestry|
1,042 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.065 [0.0037, 0.1258] sex, age, birth date, deprivation index, 16 PCs
PPM010140 PGS001907
(portability-PLR_ECG_RR_interval)
PSS009142|
European Ancestry|
193 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.0882 [-0.0618, 0.2343] sex, age, birth date, deprivation index, 16 PCs
PPM010141 PGS001907
(portability-PLR_ECG_RR_interval)
PSS008696|
European Ancestry|
226 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.1096 [-0.0276, 0.2426] sex, age, birth date, deprivation index, 16 PCs
PPM010142 PGS001907
(portability-PLR_ECG_RR_interval)
PSS008470|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): -0.3743 [-0.9096, 0.628] sex, age, birth date, deprivation index, 16 PCs
PPM010143 PGS001907
(portability-PLR_ECG_RR_interval)
PSS008250|
South Asian Ancestry|
166 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.0596 [-0.1039, 0.2199] sex, age, birth date, deprivation index, 16 PCs
PPM010144 PGS001907
(portability-PLR_ECG_RR_interval)
PSS008028|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.1051 [-0.1701, 0.365] sex, age, birth date, deprivation index, 16 PCs
PPM010146 PGS001907
(portability-PLR_ECG_RR_interval)
PSS008918|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.0322 [-0.2782, 0.3365] sex, age, birth date, deprivation index, 16 PCs
PPM010145 PGS001907
(portability-PLR_ECG_RR_interval)
PSS007814|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): -0.1946 [-0.5237, 0.1851] sex, age, birth date, deprivation index, 16 PCs
PPM010339 PGS001933
(portability-PLR_LDL)
PSS009376|
European Ancestry|
18,968 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3331 [0.3204, 0.3457] sex, age, birth date, deprivation index, 16 PCs
PPM010340 PGS001933
(portability-PLR_LDL)
PSS009150|
European Ancestry|
3,946 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3496 [0.3219, 0.3768] sex, age, birth date, deprivation index, 16 PCs
PPM010341 PGS001933
(portability-PLR_LDL)
PSS008704|
European Ancestry|
6,312 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3177 [0.2953, 0.3397] sex, age, birth date, deprivation index, 16 PCs
PPM010342 PGS001933
(portability-PLR_LDL)
PSS008478|
Greater Middle Eastern Ancestry|
1,122 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.297 [0.2422, 0.3499] sex, age, birth date, deprivation index, 16 PCs
PPM010343 PGS001933
(portability-PLR_LDL)
PSS008256|
South Asian Ancestry|
5,987 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2086 [0.1842, 0.2327] sex, age, birth date, deprivation index, 16 PCs
PPM010344 PGS001933
(portability-PLR_LDL)
PSS008034|
East Asian Ancestry|
1,716 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2593 [0.2144, 0.3032] sex, age, birth date, deprivation index, 16 PCs
PPM010345 PGS001933
(portability-PLR_LDL)
PSS007820|
African Ancestry|
2,338 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2864 [0.2486, 0.3234] sex, age, birth date, deprivation index, 16 PCs
PPM010346 PGS001933
(portability-PLR_LDL)
PSS008924|
African Ancestry|
3,651 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2203 [0.1891, 0.251] sex, age, birth date, deprivation index, 16 PCs
PPM010461 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS008759|
European Ancestry|
487 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2468 [0.1596, 0.3301] sex, age, birth date, deprivation index, 16 PCs
PPM010459 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS009431|
European Ancestry|
1,702 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2202 [0.1743, 0.2652] sex, age, birth date, deprivation index, 16 PCs
PPM010462 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS008533|
Greater Middle Eastern Ancestry|
50 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.1933 [-0.1794, 0.5176] sex, age, birth date, deprivation index, 16 PCs
PPM010463 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS008311|
South Asian Ancestry|
305 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2407 [0.1281, 0.3472] sex, age, birth date, deprivation index, 16 PCs
PPM010464 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS008088|
East Asian Ancestry|
137 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.0168 [-0.1652, 0.1978] sex, age, birth date, deprivation index, 16 PCs
PPM010465 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS007875|
African Ancestry|
77 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.155 [-0.11, 0.3995] sex, age, birth date, deprivation index, 16 PCs
PPM010466 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS008979|
African Ancestry|
140 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.0017 [-0.1776, 0.1809] sex, age, birth date, deprivation index, 16 PCs
PPM010460 PGS001948
(portability-PLR_log_ECG_QRS_duration)
PSS009205|
European Ancestry|
329 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.1602 [0.0495, 0.267] sex, age, birth date, deprivation index, 16 PCs
PPM010675 PGS001975
(portability-PLR_log_pulse_rate)
PSS009464|
European Ancestry|
18,718 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2692 [0.2559, 0.2825] sex, age, birth date, deprivation index, 16 PCs
PPM010676 PGS001975
(portability-PLR_log_pulse_rate)
PSS009238|
European Ancestry|
3,930 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2436 [0.2139, 0.2729] sex, age, birth date, deprivation index, 16 PCs
PPM010677 PGS001975
(portability-PLR_log_pulse_rate)
PSS008792|
European Ancestry|
6,338 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2694 [0.2463, 0.2921] sex, age, birth date, deprivation index, 16 PCs
PPM010678 PGS001975
(portability-PLR_log_pulse_rate)
PSS008566|
Greater Middle Eastern Ancestry|
1,151 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2658 [0.2107, 0.3191] sex, age, birth date, deprivation index, 16 PCs
PPM010679 PGS001975
(portability-PLR_log_pulse_rate)
PSS008344|
South Asian Ancestry|
6,098 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2364 [0.2125, 0.26] sex, age, birth date, deprivation index, 16 PCs
PPM010680 PGS001975
(portability-PLR_log_pulse_rate)
PSS008121|
East Asian Ancestry|
1,719 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.1969 [0.1508, 0.2422] sex, age, birth date, deprivation index, 16 PCs
PPM010681 PGS001975
(portability-PLR_log_pulse_rate)
PSS007908|
African Ancestry|
2,438 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.1477 [0.1085, 0.1865] sex, age, birth date, deprivation index, 16 PCs
PPM010682 PGS001975
(portability-PLR_log_pulse_rate)
PSS009012|
African Ancestry|
3,850 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.1343 [0.103, 0.1652] sex, age, birth date, deprivation index, 16 PCs
PPM010723 PGS001981
(portability-PLR_log_ventricular_rate)
PSS009469|
European Ancestry|
1,711 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.1331 [0.086, 0.1796] sex, age, birth date, deprivation index, 16 PCs
PPM010724 PGS001981
(portability-PLR_log_ventricular_rate)
PSS009243|
European Ancestry|
329 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.0953 [-0.0164, 0.2047] sex, age, birth date, deprivation index, 16 PCs
PPM010726 PGS001981
(portability-PLR_log_ventricular_rate)
PSS008571|
Greater Middle Eastern Ancestry|
50 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): -0.2266 [-0.5425, 0.1456] sex, age, birth date, deprivation index, 16 PCs
PPM010727 PGS001981
(portability-PLR_log_ventricular_rate)
PSS008349|
South Asian Ancestry|
307 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.025 [-0.0911, 0.1404] sex, age, birth date, deprivation index, 16 PCs
PPM010728 PGS001981
(portability-PLR_log_ventricular_rate)
PSS008126|
East Asian Ancestry|
137 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): -0.0998 [-0.2763, 0.0832] sex, age, birth date, deprivation index, 16 PCs
PPM010729 PGS001981
(portability-PLR_log_ventricular_rate)
PSS007913|
African Ancestry|
78 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.0409 [-0.2198, 0.296] sex, age, birth date, deprivation index, 16 PCs
PPM010730 PGS001981
(portability-PLR_log_ventricular_rate)
PSS009017|
African Ancestry|
140 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): -0.1197 [-0.2927, 0.0608] sex, age, birth date, deprivation index, 16 PCs
PPM010725 PGS001981
(portability-PLR_log_ventricular_rate)
PSS008797|
European Ancestry|
490 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.1205 [0.0304, 0.2087] sex, age, birth date, deprivation index, 16 PCs
PPM011664 PGS002101
(portability-ldpred2_apoA)
PSS009384|
European Ancestry|
17,339 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4018 [0.3893, 0.4143] sex, age, birth date, deprivation index, 16 PCs
PPM011665 PGS002101
(portability-ldpred2_apoA)
PSS009158|
European Ancestry|
3,563 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4015 [0.3735, 0.4288] sex, age, birth date, deprivation index, 16 PCs
PPM011666 PGS002101
(portability-ldpred2_apoA)
PSS008712|
European Ancestry|
5,765 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.4118 [0.3901, 0.433] sex, age, birth date, deprivation index, 16 PCs
PPM011667 PGS002101
(portability-ldpred2_apoA)
PSS008486|
Greater Middle Eastern Ancestry|
1,033 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.3567 [0.3017, 0.4093] sex, age, birth date, deprivation index, 16 PCs
PPM011668 PGS002101
(portability-ldpred2_apoA)
PSS008264|
South Asian Ancestry|
5,470 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.3678 [0.3447, 0.3906] sex, age, birth date, deprivation index, 16 PCs
PPM011670 PGS002101
(portability-ldpred2_apoA)
PSS007828|
African Ancestry|
2,151 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.2377 [0.1973, 0.2774] sex, age, birth date, deprivation index, 16 PCs
PPM011671 PGS002101
(portability-ldpred2_apoA)
PSS008932|
African Ancestry|
3,389 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.2133 [0.1808, 0.2453] sex, age, birth date, deprivation index, 16 PCs
PPM011669 PGS002101
(portability-ldpred2_apoA)
PSS008042|
East Asian Ancestry|
1,543 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Apolipoprotein A Partial Correlation (partial-r): 0.353 [0.3082, 0.3962] sex, age, birth date, deprivation index, 16 PCs
PPM011785 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS008693|
European Ancestry|
474 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0919 sex, age, birth date, deprivation index, 16 PCs
PPM011783 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS009365|
European Ancestry|
1,622 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0694 [0.0205, 0.118] sex, age, birth date, deprivation index, 16 PCs
PPM011784 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS009139|
European Ancestry|
310 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1064 [-0.0089, 0.2189] sex, age, birth date, deprivation index, 16 PCs
PPM011786 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS008467|
Greater Middle Eastern Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): -0.0742 [-0.429, 0.3005] sex, age, birth date, deprivation index, 16 PCs
PPM011787 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS008247|
South Asian Ancestry|
299 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.0224 [-0.0953, 0.1394] sex, age, birth date, deprivation index, 16 PCs
PPM011788 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS008025|
East Asian Ancestry|
134 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1083 [-0.0771, 0.2865] sex, age, birth date, deprivation index, 16 PCs
PPM011789 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS007811|
African Ancestry|
76 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1808 [-0.0862, 0.4236] sex, age, birth date, deprivation index, 16 PCs
PPM011790 PGS002116
(portability-ldpred2_ECG_P_duration)
PSS008915|
African Ancestry|
138 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: P duration Partial Correlation (partial-r): 0.1921 [0.0118, 0.3604] sex, age, birth date, deprivation index, 16 PCs
PPM011796 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS008023|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.1932 [-0.0813, 0.4405] sex, age, birth date, deprivation index, 16 PCs
PPM011791 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS009363|
European Ancestry|
1,036 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0979 [0.0366, 0.1584] sex, age, birth date, deprivation index, 16 PCs
PPM011792 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS009137|
European Ancestry|
191 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.2685 [0.1234, 0.4024] sex, age, birth date, deprivation index, 16 PCs
PPM011793 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS008691|
European Ancestry|
225 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.1491 [0.0123, 0.2804] sex, age, birth date, deprivation index, 16 PCs
PPM011794 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS008465|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.5089 [-0.6776, 0.9601] sex, age, birth date, deprivation index, 16 PCs
PPM011795 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS008245|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0824 [-0.0817, 0.2421] sex, age, birth date, deprivation index, 16 PCs
PPM011797 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS007809|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0366 [-0.3344, 0.3978] sex, age, birth date, deprivation index, 16 PCs
PPM011798 PGS002117
(portability-ldpred2_ECG_PP_interval)
PSS008913|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PP interval Partial Correlation (partial-r): 0.0184 [-0.2909, 0.3242] sex, age, birth date, deprivation index, 16 PCs
PPM011801 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008692|
European Ancestry|
217 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2529 [0.1173, 0.3793] sex, age, birth date, deprivation index, 16 PCs
PPM011799 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS009364|
European Ancestry|
992 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1997 [0.1385, 0.2593] sex, age, birth date, deprivation index, 16 PCs
PPM011800 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS009138|
European Ancestry|
181 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.2082 [0.0553, 0.3516] sex, age, birth date, deprivation index, 16 PCs
PPM011802 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008466|
Greater Middle Eastern Ancestry|
25 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1708 [-0.8377, 0.9152] sex, age, birth date, deprivation index, 16 PCs
PPM011803 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008246|
South Asian Ancestry|
159 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.116 [-0.0515, 0.2771] sex, age, birth date, deprivation index, 16 PCs
PPM011804 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008024|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1237 [-0.1517, 0.3812] sex, age, birth date, deprivation index, 16 PCs
PPM011805 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS007810|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1518 [-0.2274, 0.491] sex, age, birth date, deprivation index, 16 PCs
PPM011806 PGS002118
(portability-ldpred2_ECG_PQ_interval)
PSS008914|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: PQ interval Partial Correlation (partial-r): 0.1868 [-0.1282, 0.4676] sex, age, birth date, deprivation index, 16 PCs
PPM011807 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS009367|
European Ancestry|
1,042 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.1358 [0.0751, 0.1954] sex, age, birth date, deprivation index, 16 PCs
PPM011811 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS008249|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): -0.0112 [-0.1738, 0.1521] sex, age, birth date, deprivation index, 16 PCs
PPM011813 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS007813|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.0468 [-0.3253, 0.4063] sex, age, birth date, deprivation index, 16 PCs
PPM011808 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS009141|
European Ancestry|
193 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.2209 [0.0742, 0.3583] sex, age, birth date, deprivation index, 16 PCs
PPM011809 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS008695|
European Ancestry|
226 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.197 [0.062, 0.3249] sex, age, birth date, deprivation index, 16 PCs
PPM011810 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS008469|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): -0.0945 [-0.8415, 0.7766] sex, age, birth date, deprivation index, 16 PCs
PPM011812 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS008027|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.3302 [0.0658, 0.5513] sex, age, birth date, deprivation index, 16 PCs
PPM011814 PGS002119
(portability-ldpred2_ECG_QT_interval)
PSS008917|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QT interval Partial Correlation (partial-r): 0.071 [-0.2419, 0.3705] sex, age, birth date, deprivation index, 16 PCs
PPM011815 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS009366|
European Ancestry|
1,040 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2417 [0.1831, 0.2987] sex, age, birth date, deprivation index, 16 PCs
PPM011816 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS009140|
European Ancestry|
191 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2789 [0.1344, 0.4117] sex, age, birth date, deprivation index, 16 PCs
PPM011817 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS008694|
European Ancestry|
225 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.1159 [-0.0214, 0.249] sex, age, birth date, deprivation index, 16 PCs
PPM011818 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS008468|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.3605 [-0.6376, 0.9068] sex, age, birth date, deprivation index, 16 PCs
PPM011819 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS008248|
South Asian Ancestry|
165 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): -0.106 [-0.2645, 0.058] sex, age, birth date, deprivation index, 16 PCs
PPM011820 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS008026|
East Asian Ancestry|
72 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.1801 [-0.0976, 0.4317] sex, age, birth date, deprivation index, 16 PCs
PPM011821 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS007812|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): -0.0667 [-0.4229, 0.3073] sex, age, birth date, deprivation index, 16 PCs
PPM011822 PGS002120
(portability-ldpred2_ECG_QTC_interval)
PSS008916|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QTC interval Partial Correlation (partial-r): 0.2359 [-0.0773, 0.5068] sex, age, birth date, deprivation index, 16 PCs
PPM011824 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS009142|
European Ancestry|
193 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.2615 [0.1169, 0.3953] sex, age, birth date, deprivation index, 16 PCs
PPM011823 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS009368|
European Ancestry|
1,042 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.1001 [0.039, 0.1604] sex, age, birth date, deprivation index, 16 PCs
PPM011825 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS008696|
European Ancestry|
226 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.115 [-0.022, 0.2478] sex, age, birth date, deprivation index, 16 PCs
PPM011826 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS008470|
Greater Middle Eastern Ancestry|
26 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.2994 [-0.6766, 0.8938] sex, age, birth date, deprivation index, 16 PCs
PPM011827 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS008250|
South Asian Ancestry|
166 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.0599 [-0.1036, 0.2202] sex, age, birth date, deprivation index, 16 PCs
PPM011828 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS008028|
East Asian Ancestry|
73 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.1681 [-0.107, 0.4194] sex, age, birth date, deprivation index, 16 PCs
PPM011829 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS007814|
African Ancestry|
49 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): 0.0409 [-0.3305, 0.4014] sex, age, birth date, deprivation index, 16 PCs
PPM011830 PGS002121
(portability-ldpred2_ECG_RR_interval)
PSS008918|
African Ancestry|
61 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: RR interval Partial Correlation (partial-r): -0.0491 [-0.3514, 0.2625] sex, age, birth date, deprivation index, 16 PCs
PPM012054 PGS002150
(portability-ldpred2_LDL)
PSS008924|
African Ancestry|
3,651 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2251 [0.194, 0.2558] sex, age, birth date, deprivation index, 16 PCs
PPM012047 PGS002150
(portability-ldpred2_LDL)
PSS009376|
European Ancestry|
18,968 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3346 [0.3219, 0.3472] sex, age, birth date, deprivation index, 16 PCs
PPM012048 PGS002150
(portability-ldpred2_LDL)
PSS009150|
European Ancestry|
3,946 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3475 [0.3197, 0.3747] sex, age, birth date, deprivation index, 16 PCs
PPM012049 PGS002150
(portability-ldpred2_LDL)
PSS008704|
European Ancestry|
6,312 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.3081 [0.2856, 0.3303] sex, age, birth date, deprivation index, 16 PCs
PPM012050 PGS002150
(portability-ldpred2_LDL)
PSS008478|
Greater Middle Eastern Ancestry|
1,122 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2975 [0.2427, 0.3504] sex, age, birth date, deprivation index, 16 PCs
PPM012051 PGS002150
(portability-ldpred2_LDL)
PSS008256|
South Asian Ancestry|
5,987 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2191 [0.1948, 0.2431] sex, age, birth date, deprivation index, 16 PCs
PPM012052 PGS002150
(portability-ldpred2_LDL)
PSS008034|
East Asian Ancestry|
1,716 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.2555 [0.2104, 0.2994] sex, age, birth date, deprivation index, 16 PCs
PPM012053 PGS002150
(portability-ldpred2_LDL)
PSS007820|
African Ancestry|
2,338 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: LDL direct Partial Correlation (partial-r): 0.294 [0.2563, 0.3307] sex, age, birth date, deprivation index, 16 PCs
PPM012175 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS009431|
European Ancestry|
1,702 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2257 [0.1798, 0.2706] sex, age, birth date, deprivation index, 16 PCs
PPM012176 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS009205|
European Ancestry|
329 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.1797 [0.0695, 0.2855] sex, age, birth date, deprivation index, 16 PCs
PPM012177 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS008759|
European Ancestry|
487 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2307 [0.143, 0.3149] sex, age, birth date, deprivation index, 16 PCs
PPM012178 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS008533|
Greater Middle Eastern Ancestry|
50 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2134 [-0.1591, 0.5327] sex, age, birth date, deprivation index, 16 PCs
PPM012179 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS008311|
South Asian Ancestry|
305 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.2354 [0.1226, 0.3422] sex, age, birth date, deprivation index, 16 PCs
PPM012180 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS008088|
East Asian Ancestry|
137 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.0367 [-0.1458, 0.2168] sex, age, birth date, deprivation index, 16 PCs
PPM012181 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS007875|
African Ancestry|
77 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.1029 [-0.162, 0.354] sex, age, birth date, deprivation index, 16 PCs
PPM012182 PGS002166
(portability-ldpred2_log_ECG_QRS_duration)
PSS008979|
African Ancestry|
140 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: QRS duration Partial Correlation (partial-r): 0.0257 [-0.1542, 0.204] sex, age, birth date, deprivation index, 16 PCs
PPM012391 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS009464|
European Ancestry|
18,718 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.271 [0.2576, 0.2842] sex, age, birth date, deprivation index, 16 PCs
PPM012393 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS008792|
European Ancestry|
6,338 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2684 [0.2453, 0.2911] sex, age, birth date, deprivation index, 16 PCs
PPM012394 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS008566|
Greater Middle Eastern Ancestry|
1,151 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2709 [0.216, 0.3241] sex, age, birth date, deprivation index, 16 PCs
PPM012395 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS008344|
South Asian Ancestry|
6,098 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2393 [0.2155, 0.2629] sex, age, birth date, deprivation index, 16 PCs
PPM012396 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS008121|
East Asian Ancestry|
1,719 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.2011 [0.1551, 0.2463] sex, age, birth date, deprivation index, 16 PCs
PPM012397 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS007908|
African Ancestry|
2,438 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.1463 [0.1071, 0.1851] sex, age, birth date, deprivation index, 16 PCs
PPM012398 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS009012|
African Ancestry|
3,850 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.1406 [0.1094, 0.1715] sex, age, birth date, deprivation index, 16 PCs
PPM012392 PGS002193
(portability-ldpred2_log_pulse_rate)
PSS009238|
European Ancestry|
3,930 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Pulse rate, automated reading Partial Correlation (partial-r): 0.243 [0.2132, 0.2722] sex, age, birth date, deprivation index, 16 PCs
PPM012439 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS009469|
European Ancestry|
1,711 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.1563 [0.1094, 0.2024] sex, age, birth date, deprivation index, 16 PCs
PPM012440 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS009243|
European Ancestry|
329 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.1975 [0.0879, 0.3024] sex, age, birth date, deprivation index, 16 PCs
PPM012441 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS008797|
European Ancestry|
490 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.1785 [0.0894, 0.2646] sex, age, birth date, deprivation index, 16 PCs
PPM012442 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS008571|
Greater Middle Eastern Ancestry|
50 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): -0.2917 [-0.59, 0.0766] sex, age, birth date, deprivation index, 16 PCs
PPM012443 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS008349|
South Asian Ancestry|
307 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.066 [-0.0501, 0.1804] sex, age, birth date, deprivation index, 16 PCs
PPM012445 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS007913|
African Ancestry|
78 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.0201 [-0.2394, 0.277] sex, age, birth date, deprivation index, 16 PCs
PPM012446 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS009017|
African Ancestry|
140 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): -0.0905 [-0.2655, 0.0902] sex, age, birth date, deprivation index, 16 PCs
PPM012444 PGS002199
(portability-ldpred2_log_ventricular_rate)
PSS008126|
East Asian Ancestry|
137 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Ventricular rate Partial Correlation (partial-r): 0.0478 [-0.1349, 0.2274] sex, age, birth date, deprivation index, 16 PCs
PPM012908 PGS002267
(PRS89_AA)
PSS009608|
European Ancestry|
385,621 individuals
PGP000296 |
Pirruccello JP et al. Nat Genet (2021)
Reported Trait: Incident thoracic aortic aneurysm or dissection HR: 1.43 [1.32, 1.54] Sex, prevalent diagnoses of type 2 diabetes or hypertension, tobacco smoking history (the number of pack years of tobacco smoking), body mass (the cubic natural spline of body mass index) and age (the cubic natural spline of age at enrollment).
PPM012944 PGS002274
(LDL-PRS)
PSS009627|
European Ancestry|
4,416 individuals
PGP000303 |
Groenland EH et al. Atherosclerosis (2022)
Reported Trait: Low-density lipoprotein cholesterol β: 0.18 [0.15, 0.21] Age, sex, the first 5 principal components, BMI, T2DM, smoking, alcohol use, systolic blood pressure, eGFR, triglycerides, lipid-lowering medication
PPM012946 PGS002276
(QTc_PRS-CS)
PSS009628|
Multi-ancestry (including European)|
26,976 individuals
PGP000304 |
Nauffal V et al. Circulation (2022)
Reported Trait: QTc : 0.087 age, sex, beta blocker use, calcium channel blocker use, heart failure, myocardial infarction, first 12 principal components of genetic ancestry (PC1-12) PRS performance was overall similar across the individual genetic ancestries in TOPMed. (European R²: 0.074; African R²:0.077, Admixed American R²:0.148; Amish R²:0.197; Asian R²:0.245; Undetermined Genetic Ancestry R²:0.106)
PPM012952 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: All-cause mortality HR (top 10% vs bottom 10%): 1.11 [1.04, 1.18] Age, sex, body mass index (BMI; except for obesity),10 principal components of ancestry
PPM012954 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: All-cause mortality (with heart failure) HR (top 10% vs bottom 10%): 1.26 [1.05, 1.5] Age, sex, body mass index (BMI; except for obesity),10 principal components of ancestry
PPM012956 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: All-cause mortality (without heart failure) HR (top 10% vs bottom 10%): 1.09 [1.02, 1.17] Age, sex, body mass index (BMI; except for obesity),10 principal components of ancestry
PPM012957 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Heart failure diagnosis OR: 0.97 [0.95, 0.99] Age, sex, body mass index,10 principal components of ancestry
PPM012958 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Brain natriuretic peptide level Median (top 10% vs bottom 10%): 146.0 [79, 228] pg/ml
PPM012959 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Prevalence of dyspnoea OR (top 10% vs bottom 10%): 1.17 [1.01, 1.37]
PPM012960 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Exertional dyspnoea OR (top 10% vs bottom 10%): 1.39 [1.12, 1.74]
PPM012961 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Peperipheral oedema OR (top 10% vs bottom 10%): 1.07 [1.01, 1.13]
PPM012962 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Medication for heart failure (loop diuretics) OR (top 10% vs bottom 10%): 1.03 [1.01, 1.05]
PPM012963 PGS002278
(GRS16_snLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: Medication for heart failure (mineralocorticoid receptor antagonists) OR (top 10% vs bottom 10%): 1.04 [1.01, 1.09]
PPM012953 PGS002279
(GRS22_rLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: All-cause mortality HR (top 10% vs bottom 10%): 1.1 [1.02, 1.12] Age, sex, body mass index (BMI; except for obesity),10 principal components of ancestry
PPM012955 PGS002279
(GRS22_rLVEF)
PSS009631|
Multi-ancestry (including European)|
486,754 individuals
PGP000307 |
Forrest IS et al. Eur J Heart Fail (2022)
Reported Trait: All-cause mortality (with heart failure) HR (top 10% vs bottom 10%): 1.31 [1.09, 1.58] Age, sex, body mass index (BMI; except for obesity),10 principal components of ancestry
PPM012983 PGS002285
(GRS_286_LDL)
PSS009639|
African Ancestry|
2,569 individuals
PGP000313 |
Kamiza AB et al. Nat Med (2022)
Reported Trait: Low density lipoprotein cholesterol levels : 0.0814 age, sex, type 2 diabetes, PC1, PC2, PC3, PC4, PC5 Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment)
PPM013102 PGS002337
(biochemistry_LDLdirect.BOLT-LMM)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0733 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013151 PGS002337
(biochemistry_LDLdirect.BOLT-LMM)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0681 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013200 PGS002337
(biochemistry_LDLdirect.BOLT-LMM)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.11 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013249 PGS002337
(biochemistry_LDLdirect.BOLT-LMM)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0479 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013281 PGS002369
(biochemistry_LDLdirect.BOLT-LMM-BBJ)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0314 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013304 PGS002369
(biochemistry_LDLdirect.BOLT-LMM-BBJ)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.037 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013327 PGS002369
(biochemistry_LDLdirect.BOLT-LMM-BBJ)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0112 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013350 PGS002369
(biochemistry_LDLdirect.BOLT-LMM-BBJ)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0091 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013390 PGS002409
(biochemistry_LDLdirect.P+T.0.0001)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0019 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013439 PGS002409
(biochemistry_LDLdirect.P+T.0.0001)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0268 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013488 PGS002409
(biochemistry_LDLdirect.P+T.0.0001)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0733 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013537 PGS002409
(biochemistry_LDLdirect.P+T.0.0001)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0203 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013586 PGS002458
(biochemistry_LDLdirect.P+T.0.001)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0011 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013635 PGS002458
(biochemistry_LDLdirect.P+T.0.001)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0162 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013684 PGS002458
(biochemistry_LDLdirect.P+T.0.001)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0672 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013733 PGS002458
(biochemistry_LDLdirect.P+T.0.001)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0065 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013782 PGS002507
(biochemistry_LDLdirect.P+T.0.01)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0002 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013831 PGS002507
(biochemistry_LDLdirect.P+T.0.01)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0016 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013929 PGS002507
(biochemistry_LDLdirect.P+T.0.01)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0002 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013880 PGS002507
(biochemistry_LDLdirect.P+T.0.01)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0127 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013978 PGS002556
(biochemistry_LDLdirect.P+T.1e-06)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0407 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014027 PGS002556
(biochemistry_LDLdirect.P+T.1e-06)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0185 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014076 PGS002556
(biochemistry_LDLdirect.P+T.1e-06)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0705 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014125 PGS002556
(biochemistry_LDLdirect.P+T.1e-06)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0205 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014174 PGS002605
(biochemistry_LDLdirect.P+T.5e-08)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0428 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014223 PGS002605
(biochemistry_LDLdirect.P+T.5e-08)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0167 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014272 PGS002605
(biochemistry_LDLdirect.P+T.5e-08)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0679 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014321 PGS002605
(biochemistry_LDLdirect.P+T.5e-08)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0195 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014370 PGS002654
(biochemistry_LDLdirect.PolyFun-pred)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1091 age, sex, age*sex, assessment center, genotyping array, 10 PCs See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014419 PGS002654
(biochemistry_LDLdirect.PolyFun-pred)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0724 age, sex, age*sex, assessment center, genotyping array, 10 PCs See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014468 PGS002654
(biochemistry_LDLdirect.PolyFun-pred)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1195 age, sex, age*sex, assessment center, genotyping array, 10 PCs See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014517 PGS002654
(biochemistry_LDLdirect.PolyFun-pred)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0528 age, sex, age*sex, assessment center, genotyping array, 10 PCs See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014566 PGS002703
(biochemistry_LDLdirect.SBayesR)
PSS009791|
African Ancestry|
6,068 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0612 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014664 PGS002703
(biochemistry_LDLdirect.SBayesR)
PSS009793|
European Ancestry|
41,139 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.1011 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014713 PGS002703
(biochemistry_LDLdirect.SBayesR)
PSS009794|
South Asian Ancestry|
7,638 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0377 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014615 PGS002703
(biochemistry_LDLdirect.SBayesR)
PSS009792|
East Asian Ancestry|
875 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: LDL Cholesterol Incremental R2 (full model vs. covariates alone): 0.0478 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014797 PGS002730
(GRSlipid_35)
PSS009892|
European Ancestry|
75,973 individuals
PGP000337 |
Mayerhofer E et al. Brain (2022)
Reported Trait: On-statin LDL decrease β: -0.05 [-0.07, -0.02]
PPM014798 PGS002730
(GRSlipid_35)
PSS009892|
European Ancestry|
75,973 individuals
PGP000337 |
Mayerhofer E et al. Brain (2022)
Reported Trait: Incident intracerebral hemorrhage HR: 1.16 [1.05, 1.28]
PPM014799 PGS002730
(GRSlipid_35)
PSS009892|
European Ancestry|
75,973 individuals
PGP000337 |
Mayerhofer E et al. Brain (2022)
Reported Trait: Incident myocardial infarction HR: 0.98 [0.96, 0.99]
PPM014800 PGS002730
(GRSlipid_35)
PSS009892|
European Ancestry|
75,973 individuals
PGP000337 |
Mayerhofer E et al. Brain (2022)
Reported Trait: Incident Peripheral Artery Disease HR: 0.93 [0.87, 0.99]
PPM016162 PGS002782
(GLGC_2021_ALL_nonHDL_PRS_weights_PRS-CS)
PSS010052|
Multi-ancestry (including European)|
461,918 individuals
PGP000366 |
Kanoni S et al. medRxiv (2021)
|Pre
Reported Trait: Baseline nonHDL cholesterol : 0.14 sex, batch, age at initial assessment, PCs1-4
PPM015918 PGS003029
(ExPRSweb_LDL_30780-irnt_LASSOSUM_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.06 (0.286) : 0.0594 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015921 PGS003030
(ExPRSweb_LDL_30780-irnt_PT_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.07 (0.283) : 0.061 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015919 PGS003031
(ExPRSweb_LDL_30780-irnt_PLINK_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.23 (0.283) : 0.0635 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015917 PGS003032
(ExPRSweb_LDL_30780-irnt_DBSLMM_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.6 (0.282) : 0.0687 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015920 PGS003033
(ExPRSweb_LDL_30780-irnt_PRSCS_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.36 (0.284) : 0.0649 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015923 PGS003034
(ExPRSweb_LDL_30780-raw_LASSOSUM_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.06 (0.286) : 0.0593 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015926 PGS003035
(ExPRSweb_LDL_30780-raw_PT_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.09 (0.283) : 0.0612 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015924 PGS003036
(ExPRSweb_LDL_30780-raw_PLINK_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.17 (0.283) : 0.0625 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015922 PGS003037
(ExPRSweb_LDL_30780-raw_DBSLMM_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.9 (0.281) : 0.0753 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM015925 PGS003038
(ExPRSweb_LDL_30780-raw_PRSCS_MGI_20211120)
PSS010010|
European Ancestry|
9,288 individuals
PGP000393 |
Ma Y et al. Am J Hum Genet (2022)
Reported Trait: LDL β: 7.42 (0.285) : 0.0656 SEX,AGE,Batch,PC1,PC2,PC3,PC4
PPM016178 PGS003339
(CVGRS_LDL)
PSS010055|
East Asian Ancestry|
22,608 individuals
PGP000405 |
Kim YJ et al. Nat Commun (2022)
Reported Trait: LDL cholesterol level β: 0.31083
PPM016195 PGS003339
(CVGRS_LDL)
PSS010055|
East Asian Ancestry|
22,608 individuals
PGP000405 |
Kim YJ et al. Nat Commun (2022)
Reported Trait: Type 2 diabetes OR: 0.99947
PPM016187 PGS003348
(ALLGRS_LDL)
PSS010055|
East Asian Ancestry|
22,608 individuals
PGP000405 |
Kim YJ et al. Nat Commun (2022)
Reported Trait: LDL cholesterol level β: 0.31961
PPM017041 PGS003403
(PRS28_LDL)
PSS010102|
European Ancestry|
626 individuals
PGP000420 |
Trinder M et al. J Am Coll Cardiol (2019)
Reported Trait: LDL-C levels pvalue (High >=80 percentile vs lower <80th percentile): 0.03
PPM017046 PGS003403
(PRS28_LDL)
PSS010104|
European Ancestry|
89,528 individuals
PGP000422 |
Vanhoye X et al. Transl Res (2022)
|Ext.
Reported Trait: LDL-c blood concentration β: 0.18 [0.18, 0.18] AUROC: 0.6233 [0.617, 0.63] : 0.1055 Age, BMI, sex, age
PPM017042 PGS003403
(PRS28_LDL)
PSS010102|
European Ancestry|
626 individuals
PGP000420 |
Trinder M et al. J Am Coll Cardiol (2019)
Reported Trait: Cardiovascular disease events in patients with monogenic familial hypercholesterolemia Adjusted Hazard Ratio (aHR; top 20% vs. remaining): 3.06 [1.56, 5.99] age, sex, LDL-C, diabetes mellitus, and hypertension
PPM017043 PGS003404
(wGRS)
PSS010103|
Multi-ancestry (including European)|
313 individuals
PGP000421 |
Wang J et al. Arterioscler Thromb Vasc Biol (2016)
Reported Trait: FH mutation-negative with severe hypercholesterolemia OR: 3.02 [1.61, 5.68]
PPM017047 PGS003404
(wGRS)
PSS010104|
European Ancestry|
89,528 individuals
PGP000422 |
Vanhoye X et al. Transl Res (2022)
|Ext.
Reported Trait: LDL-c blood concentration β: 0.16 [0.15, 0.16] AUROC: 0.6072 [0.6, 0.614] : 0.09317 Age, BMI, sex, age
PPM017044 PGS003405
(165SNP_PRS)
PSS010104|
European Ancestry|
89,528 individuals
PGP000422 |
Vanhoye X et al. Transl Res (2022)
Reported Trait: LDL-c blood concentration β: 0.31 [0.3, 0.31] AUROC: 0.6901 [0.684, 0.696] : 0.1979 Age, BMI, sex, age
PPM017101 PGS003427
(lvmi)
PSS010124|
Multi-ancestry (including European)|
29,354 individuals
PGP000434 |
Khurshid S et al. Nat Commun (2023)
Reported Trait: incident implantable cardioverter-defibrillator implant HR: 1.05 age, sex, PC 1-5
PPM017100 PGS003427
(lvmi)
PSS010123|
Multi-ancestry (including European)|
443,326 individuals
PGP000434 |
Khurshid S et al. Nat Commun (2023)
Reported Trait: incident implantable cardioverter-defibrillator implant HR: 1.07 age, sex, PC 1-5
PPM017282 PGS003472
(LDPred2_HrRt)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index β: 0.019 (0.01) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017305 PGS003472
(LDPred2_HrRt)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea β: 0.032 (0.024) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017284 PGS003474
(LDPred2_LDL)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index β: 0.001 (0.01) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017307 PGS003474
(LDPred2_LDL)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea β: -0.023 (0.025) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017287 PGS003477
(LDPred2_PP)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index β: -0.022 (0.01) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017310 PGS003477
(LDPred2_PP)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea β: -0.032 (0.024) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017354 PGS003477
(LDPred2_PP)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index in obsese β: -0.013 (0.017) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017374 PGS003477
(LDPred2_PP)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea in obsese β: -0.012 (0.034) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017375 PGS003477
(LDPred2_PP)
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: -0.057 (0.035) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017355 PGS003477
(LDPred2_PP)
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: -0.024 (0.012) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017399 PGS003477
(LDPred2_PP)
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: -0.001 (0.999) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017409 PGS003477
(LDPred2_PP)
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: 1.028 (0.05) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017427 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010860|
European Ancestry|
995 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017511 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010776|
European Ancestry|
180 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM017595 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010608|
European Ancestry|
213 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017679 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010524|
Greater Middle Eastern Ancestry|
25 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.32 sex, age, deprivation index, PC1-16
PPM017763 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010188|
European Ancestry|
103 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017847 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010440|
South Asian Ancestry|
159 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017931 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010356|
East Asian Ancestry|
73 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM018015 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010272|
African Ancestry|
49 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM018099 PGS003499
(cont-decay-ECG_PQ_interval)
PSS010692|
African Ancestry|
61 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: PQ interval partial-R2: 0.01 sex, age, deprivation index, PC1-16
PPM017428 PGS003500
(cont-decay-ECG_QT_interval)
PSS010861|
European Ancestry|
1,040 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017512 PGS003500
(cont-decay-ECG_QT_interval)
PSS010777|
European Ancestry|
192 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017596 PGS003500
(cont-decay-ECG_QT_interval)
PSS010609|
European Ancestry|
220 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017680 PGS003500
(cont-decay-ECG_QT_interval)
PSS010525|
Greater Middle Eastern Ancestry|
26 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM017764 PGS003500
(cont-decay-ECG_QT_interval)
PSS010189|
European Ancestry|
107 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM017848 PGS003500
(cont-decay-ECG_QT_interval)
PSS010441|
South Asian Ancestry|
165 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM017932 PGS003500
(cont-decay-ECG_QT_interval)
PSS010357|
East Asian Ancestry|
73 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM018016 PGS003500
(cont-decay-ECG_QT_interval)
PSS010273|
African Ancestry|
49 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM018100 PGS003500
(cont-decay-ECG_QT_interval)
PSS010693|
African Ancestry|
61 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QT interval partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM017765 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010190|
European Ancestry|
107 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM017429 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010862|
European Ancestry|
1,040 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017513 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010778|
European Ancestry|
190 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.08 sex, age, deprivation index, PC1-16
PPM017597 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010610|
European Ancestry|
219 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.01 sex, age, deprivation index, PC1-16
PPM017681 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010526|
Greater Middle Eastern Ancestry|
26 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.01 sex, age, deprivation index, PC1-16
PPM017849 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010442|
South Asian Ancestry|
165 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM017933 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010358|
East Asian Ancestry|
72 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.01 sex, age, deprivation index, PC1-16
PPM018017 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010274|
African Ancestry|
49 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.09 sex, age, deprivation index, PC1-16
PPM018101 PGS003501
(cont-decay-ECG_QTC_interval)
PSS010694|
African Ancestry|
61 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QTC interval partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM017445 PGS003517
(cont-decay-LDL)
PSS010879|
European Ancestry|
19,077 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.11 sex, age, deprivation index, PC1-16
PPM017529 PGS003517
(cont-decay-LDL)
PSS010795|
European Ancestry|
3,935 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.12 sex, age, deprivation index, PC1-16
PPM017697 PGS003517
(cont-decay-LDL)
PSS010543|
Greater Middle Eastern Ancestry|
1,093 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.09 sex, age, deprivation index, PC1-16
PPM017781 PGS003517
(cont-decay-LDL)
PSS010207|
European Ancestry|
2,235 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017865 PGS003517
(cont-decay-LDL)
PSS010459|
South Asian Ancestry|
5,934 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017949 PGS003517
(cont-decay-LDL)
PSS010375|
East Asian Ancestry|
1,705 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.06 sex, age, deprivation index, PC1-16
PPM018033 PGS003517
(cont-decay-LDL)
PSS010291|
African Ancestry|
2,326 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.08 sex, age, deprivation index, PC1-16
PPM018117 PGS003517
(cont-decay-LDL)
PSS010711|
African Ancestry|
3,622 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.05 sex, age, deprivation index, PC1-16
PPM017613 PGS003517
(cont-decay-LDL)
PSS010627|
European Ancestry|
6,160 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: LDL direct partial-R2: 0.09 sex, age, deprivation index, PC1-16
PPM017457 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010893|
European Ancestry|
1,567 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017541 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010809|
European Ancestry|
299 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017625 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010641|
European Ancestry|
400 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.03 sex, age, deprivation index, PC1-16
PPM017709 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010557|
Greater Middle Eastern Ancestry|
42 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM017793 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010221|
European Ancestry|
186 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM017961 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010389|
East Asian Ancestry|
115 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.01 sex, age, deprivation index, PC1-16
PPM018129 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010725|
African Ancestry|
116 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM017877 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010473|
South Asian Ancestry|
253 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM018045 PGS003529
(cont-decay-log_ECG_QRS_duration)
PSS010305|
African Ancestry|
67 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: QRS duration partial-R2: 0.0 sex, age, deprivation index, PC1-16
PPM017478 PGS003550
(cont-decay-log_pulse_rate)
PSS010916|
European Ancestry|
18,679 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.08 sex, age, deprivation index, PC1-16
PPM017562 PGS003550
(cont-decay-log_pulse_rate)
PSS010832|
European Ancestry|
3,920 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.06 sex, age, deprivation index, PC1-16
PPM017646 PGS003550
(cont-decay-log_pulse_rate)
PSS010664|
European Ancestry|
6,182 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017730 PGS003550
(cont-decay-log_pulse_rate)
PSS010580|
Greater Middle Eastern Ancestry|
1,122 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.08 sex, age, deprivation index, PC1-16
PPM017814 PGS003550
(cont-decay-log_pulse_rate)
PSS010244|
European Ancestry|
2,194 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.07 sex, age, deprivation index, PC1-16
PPM017898 PGS003550
(cont-decay-log_pulse_rate)
PSS010496|
South Asian Ancestry|
6,050 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.06 sex, age, deprivation index, PC1-16
PPM017982 PGS003550
(cont-decay-log_pulse_rate)
PSS010412|
East Asian Ancestry|
1,709 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.04 sex, age, deprivation index, PC1-16
PPM018066 PGS003550
(cont-decay-log_pulse_rate)
PSS010328|
African Ancestry|
2,424 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM018150 PGS003550
(cont-decay-log_pulse_rate)
PSS010748|
African Ancestry|
3,819 individuals
PGP000457 |
Ding Y et al. bioRxiv (2022)
|Pre
Reported Trait: Pulse rate, automated reading partial-R2: 0.02 sex, age, deprivation index, PC1-16
PPM018591 PGS003784
(LDL_EUR_CT)
PSS011045|
European Ancestry|
9,527 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.07541
PPM018592 PGS003785
(LDL_EUR_LDpred2)
PSS011045|
European Ancestry|
9,527 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.05473
PPM018593 PGS003786
(LDL_AFR_CT)
PSS011043|
African Ancestry|
4,292 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.08924
PPM018594 PGS003787
(LDL_AFR_LDpred2)
PSS011043|
African Ancestry|
4,292 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.03349
PPM018595 PGS003788
(LDL_AFR_weighted_LDpred2)
PSS011043|
African Ancestry|
4,292 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.04384
PPM018596 PGS003789
(LDL_AFR_PRSCSx)
PSS011043|
African Ancestry|
4,292 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.08679
PPM018597 PGS003790
(LDL_AFR_CTSLEB)
PSS011043|
African Ancestry|
4,292 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.11584
PPM018598 PGS003791
(LDL_EAS_CT)
PSS011044|
East Asian Ancestry|
970 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.02274
PPM018599 PGS003792
(LDL_EAS_LDpred2)
PSS011044|
East Asian Ancestry|
970 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.0184
PPM018600 PGS003793
(LDL_EAS_weighted_LDpred2)
PSS011044|
East Asian Ancestry|
970 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.03105
PPM018601 PGS003794
(LDL_EAS_PRSCSx)
PSS011044|
East Asian Ancestry|
970 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.0534
PPM018602 PGS003795
(LDL_EAS_CTSLEB)
PSS011044|
East Asian Ancestry|
970 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.0239
PPM018603 PGS003796
(LDL_SAS_CT)
PSS011046|
South Asian Ancestry|
5,137 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.02586
PPM018604 PGS003797
(LDL_SAS_LDpred2)
PSS011046|
South Asian Ancestry|
5,137 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.01341
PPM018605 PGS003798
(LDL_SAS_weighted_LDpred2)
PSS011046|
South Asian Ancestry|
5,137 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.02782
PPM018606 PGS003799
(LDL_SAS_PRSCSx)
PSS011046|
South Asian Ancestry|
5,137 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.04872
PPM018607 PGS003800
(LDL_SAS_CTSLEB)
PSS011046|
South Asian Ancestry|
5,137 individuals
PGP000489 |
Zhang H et al. Nat Genet (2023)
Reported Trait: Low-density lipoprotein cholesterol : 0.03323
PPM018687 PGS003855
(PRS44_LDL)
PSS011066|
East Asian Ancestry|
37,317 individuals
PGP000493 |
Li J et al. JAMA Netw Open (2023)
Reported Trait: Estimated annual change of LDL cholesterol p-value (inferior to): 0.001
PPM018691 PGS003855
(PRS44_LDL)
PSS011068|
East Asian Ancestry|
15,664 individuals
PGP000493 |
Li J et al. JAMA Netw Open (2023)
Reported Trait: Estimated annual change of LDL cholesterol p-value (inferior to): 0.001
PPM018695 PGS003855
(PRS44_LDL)
PSS011067|
East Asian Ancestry|
21,653 individuals
PGP000493 |
Li J et al. JAMA Netw Open (2023)
Reported Trait: Estimated annual change of LDL cholesterol p-value (inferior to): 0.001
PPM018761 PGS003869
(LDL_PRScsx_ARB_AFRweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM018762 PGS003870
(LDL_PRScsx_ARB_AMRweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM018763 PGS003871
(LDL_PRScsx_ARB_ARBweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM018764 PGS003872
(LDL_PRScsx_ARB_EASweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM018765 PGS003873
(LDL_PRScsx_ARB_EURweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM018766 PGS003874
(LDL_PRScsx_ARB_SASweights)
PSS011097|
Greater Middle Eastern Ancestry|
2,669 individuals
PGP000501 |
Shim I et al. Nature Communications (2023)
Reported Trait: LDL cholesterol β: 9.4 (1.1) : 0.0358 age, sex, array version, and the first 10 principal components of ancestry The reported performance was derived from a linearly combined score of 6 normalized ancestry-specific scores using the following coefficients: Score = (-0.1166049*zscoreAFR) + (0.812596*zscoreAMR) + (-2.1986549*zscoreARB) + (3.9764576*zscoreEAS) + (6.7068379*zscoreEUR) + (3.433336*zscoreSAS).
PPM019145 PGS003974
(AFR_without-UKB_LDL)
PSS011206|
African Ancestry|
3,802 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 9.2 %
PPM019140 PGS003975
(EAS_without-UKB_LDL)
PSS011203|
East Asian Ancestry|
1,480 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 8.6 %
PPM019142 PGS003975
(EAS_without-UKB_LDL)
PSS011201|
East Asian Ancestry|
68,978 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 9.3 %
PPM019138 PGS003976
(EUR_without-UKB_LDL)
PSS011207|
European Ancestry|
423,596 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 10.6 %
PPM019143 PGS003976
(EUR_without-UKB_LDL)
PSS011201|
East Asian Ancestry|
68,978 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 4.5 %
PPM019146 PGS003977
(SAS_without-UKB_LDL)
PSS011204|
South Asian Ancestry|
6,303 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 5.6 %
PPM019139 PGS003978
(meta_without-UKB_LDL)
PSS011207|
European Ancestry|
423,596 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 10.5 %
PPM019141 PGS003978
(meta_without-UKB_LDL)
PSS011203|
East Asian Ancestry|
1,480 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 7.8 %
PPM019144 PGS003978
(meta_without-UKB_LDL)
PSS011201|
East Asian Ancestry|
68,978 individuals
PGP000514 |
Hassanin E et al. medRxiv (2023)
|Pre
Reported Trait: LDL level : 6.7 %
PPM020442 PGS004327
(X4194.score)
PSS011364|
European Ancestry|
56,192 individuals
PGP000561 |
Jung H et al. Commun Biol (2024)
Reported Trait: Pulse rate PGS R2 (no covariates): 0.13579
PPM020485 PGS004370
(X102.score)
PSS011364|
European Ancestry|
56,192 individuals
PGP000561 |
Jung H et al. Commun Biol (2024)
Reported Trait: Pulse rate, automated reading PGS R2 (no covariates): 0.20361

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
PSS009158 3,563 individuals European Poland (NE Europe) UKB
PSS011441
[
  • 165 cases
  • , 339 controls
]
,
82.0 % Male samples
Mean = 27.5 years African unspecified PDAY
PSS011442
[
  • 181 cases
  • , 383 controls
]
,
77.0 % Male samples
Mean = 26.7 years European PDAY
PSS010188 103 individuals,
55.0 % Male samples
Mean = 56.0 years
Sd = 6.1 years
European Ashkenazi UKB
PSS010189 107 individuals,
54.0 % Male samples
Mean = 56.2 years
Sd = 6.4 years
European Ashkenazi UKB
PSS010190 107 individuals,
54.0 % Male samples
Mean = 56.2 years
Sd = 6.4 years
European Ashkenazi UKB
PSS009205 329 individuals European Poland (NE Europe) UKB
PSS010207 2,235 individuals,
45.0 % Male samples
Mean = 58.1 years
Sd = 7.1 years
European Ashkenazi UKB
PSS010221 186 individuals,
55.0 % Male samples
Mean = 56.5 years
Sd = 6.4 years
European Ashkenazi UKB
PSS009238 3,930 individuals European Poland (NE Europe) UKB
PSS009243 329 individuals European Poland (NE Europe) UKB
PSS010244 2,194 individuals,
45.0 % Male samples
Mean = 58.0 years
Sd = 7.1 years
European Ashkenazi UKB
PSS007331 3,863 individuals African unspecified UKB
PSS007332 807 individuals East Asian UKB
PSS007333 11,021 individuals European non-white British ancestry UKB
PSS007334 5,226 individuals South Asian UKB
PSS007335 26,777 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS007336 3,863 individuals African unspecified UKB
PSS007337 807 individuals East Asian UKB
PSS007338 11,021 individuals European non-white British ancestry UKB
PSS007339 5,226 individuals South Asian UKB
PSS007340 26,777 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS007341 3,863 individuals African unspecified UKB
PSS007342 807 individuals East Asian UKB
PSS007343 11,021 individuals European non-white British ancestry UKB
PSS007344 5,226 individuals South Asian UKB
PSS007345 26,777 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS010272 49 individuals,
31.0 % Male samples
Mean = 48.8 years
Sd = 6.4 years
African American or Afro-Caribbean Caribbean UKB
PSS010273 49 individuals,
31.0 % Male samples
Mean = 48.8 years
Sd = 6.4 years
African American or Afro-Caribbean Caribbean UKB
PSS010274 49 individuals,
31.0 % Male samples
Mean = 48.8 years
Sd = 6.4 years
African American or Afro-Caribbean Caribbean UKB
PSS010291 2,326 individuals,
37.0 % Male samples
Mean = 52.5 years
Sd = 8.1 years
African American or Afro-Caribbean Caribbean UKB
PSS008692 217 individuals European Italy (South Europe) UKB
PSS010305 67 individuals,
30.0 % Male samples
Mean = 49.8 years
Sd = 6.5 years
African American or Afro-Caribbean Caribbean UKB
PSS008693 474 individuals European Italy (South Europe) UKB
PSS008694 225 individuals European Italy (South Europe) UKB
PSS008695 226 individuals European Italy (South Europe) UKB
PSS010328 2,424 individuals,
36.0 % Male samples
Mean = 52.5 years
Sd = 8.1 years
African American or Afro-Caribbean Caribbean UKB
PSS009363 1,036 individuals European UK (+ Ireland) UKB
PSS009364 992 individuals European UK (+ Ireland) UKB
PSS009365 1,622 individuals European UK (+ Ireland) UKB
PSS009366 1,040 individuals European UK (+ Ireland) UKB
PSS009367 1,042 individuals European UK (+ Ireland) UKB
PSS009368 1,042 individuals European UK (+ Ireland) UKB
PSS010356 73 individuals,
34.0 % Male samples
Mean = 50.3 years
Sd = 7.1 years
East Asian Chinese UKB
PSS010357 73 individuals,
34.0 % Male samples
Mean = 50.3 years
Sd = 7.1 years
East Asian Chinese UKB
PSS010358 72 individuals,
35.0 % Male samples
Mean = 50.2 years
Sd = 7.1 years
East Asian Chinese UKB
PSS009376 18,968 individuals European UK (+ Ireland) UKB
PSS009384 17,339 individuals European UK (+ Ireland) UKB
PSS010375 1,705 individuals,
33.0 % Male samples
Mean = 52.4 years
Sd = 7.8 years
East Asian Chinese UKB
PSS010389 115 individuals,
35.0 % Male samples
Mean = 51.1 years
Sd = 6.9 years
East Asian Chinese UKB
PSS007496 209 individuals African unspecified UKB
PSS007497 141 individuals East Asian UKB
PSS007498 2,103 individuals European non-white British ancestry UKB
PSS007499 381 individuals South Asian UKB
PSS007500 6,590 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS010412 1,709 individuals,
33.0 % Male samples
Mean = 52.5 years
Sd = 7.8 years
East Asian Chinese UKB
PSS009431 1,702 individuals European UK (+ Ireland) UKB
PSS010440 159 individuals,
65.0 % Male samples
Mean = 51.1 years
Sd = 8.2 years
South Asian Indian UKB
PSS010441 165 individuals,
66.0 % Male samples
Mean = 51.2 years
Sd = 8.1 years
South Asian Indian UKB
PSS010442 165 individuals,
66.0 % Male samples
Mean = 51.1 years
Sd = 8.1 years
South Asian Indian UKB
PSS009464 18,718 individuals European UK (+ Ireland) UKB
PSS009469 1,711 individuals European UK (+ Ireland) UKB
PSS010459 5,934 individuals,
54.0 % Male samples
Mean = 53.3 years
Sd = 8.4 years
South Asian Indian UKB
PSS000588 Derived from the Friedewald’s formula 426 individuals,
46.0 % Male samples
Mean = 43.3 years
Sd = 11.4 years
East Asian
(Chinese)
NR Adults
PSS000590 Derived from the Friedewald’s formula 1,941 individuals,
57.7 % Male samples
Mean = 58.2 years
Sd = 12.34 years
East Asian
(Chinese)
HKDB
PSS000592 Derived from the Friedewald’s formula 865 individuals,
57.6 % Male samples
Mean = 57.0 years
Sd = 12.08 years
East Asian
(Chinese)
HKDB
PSS000594 Derived from the Friedewald’s formula 4,917 individuals,
44.9 % Male samples
Mean = 56.3 years
Sd = 13.5 years
East Asian
(Chinese)
HKDR
PSS010473 253 individuals,
66.0 % Male samples
Mean = 51.4 years
Sd = 7.9 years
South Asian Indian UKB
PSS000096 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 1,355 individuals,
46.2 % Male samples
Mean = 61.68 years African American or Afro-Caribbean MESA MESA Classic Cohort
PSS000097 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 666 individuals,
50.15 % Male samples
Mean = 61.5 years East Asian MESA MESA Classic Cohort
PSS000098 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 2,063 individuals,
46.78 % Male samples
Mean = 62.09 years European MESA MESA Classic Cohort
PSS000099 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 1,256 individuals,
48.89 % Male samples
Mean = 60.65 years Hispanic or Latin American MESA MESA Classic Cohort
PSS000100 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 6,407 individuals,
44.0 % Male samples
Mean = 34.0 years Sub-Saharan African APCDR APCDR-Uganda study
PSS000101 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 21,295 individuals,
38.0 % Male samples
Mean = 60.0 years East Asian
(Chinese)
CKB - 20810 samples had HDL measurements - 17662 samples had LDL measurements - 20222 samples had triglyceride measurements
PSS000102 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 1,641 individuals,
58.0 % Male samples
Mean = 62.0 years European
(Greek)
Population isolate from the Pomak villages in the North of Greece HELIC - 1186 samples had HDL measurements - 1186 samples had LDL measurements - 1176 samples had triglyceride measurements
PSS000103 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 1,945 individuals,
66.0 % Male samples
Mean = 45.0 years European
(Greek)
Population isolate from the Mylopotamos villages in Crete HELIC - 1078 samples had HDL measurements - 1075 samples had LDL measurements - 1066 samples had triglyceride measurements
PSS000104 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 9,962 individuals,
56.0 % Male samples
Mean = 52.0 years European UKHLS - 9706 samples had HDL measurements - 9767 samples had LDL measurements - 9635 samples had triglyceride measurements
PSS010496 6,050 individuals,
54.0 % Male samples
Mean = 53.4 years
Sd = 8.4 years
South Asian Indian UKB
PSS010524 25 individuals,
64.0 % Male samples
Mean = 52.6 years
Sd = 6.8 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB
PSS010525 26 individuals,
65.0 % Male samples
Mean = 52.8 years
Sd = 6.8 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB
PSS010526 26 individuals,
65.0 % Male samples
Mean = 52.8 years
Sd = 6.8 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB
PSS010543 1,093 individuals,
60.0 % Male samples
Mean = 51.9 years
Sd = 7.9 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB
PSS010557 42 individuals,
62.0 % Male samples
Mean = 53.8 years
Sd = 6.7 years
Greater Middle Eastern (Middle Eastern, North African or Persian) Iranian UKB
PSS010580 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
PSS010608 213 individuals,
48.0 % Male samples
Mean = 53.8 years
Sd = 7.4 years
European Italian UKB
PSS010609 220 individuals,
48.0 % Male samples
Mean = 53.8 years
Sd = 7.4 years
European Italian UKB
PSS010610 219 individuals,
48.0 % Male samples
Mean = 53.8 years
Sd = 7.4 years
European Italian UKB
PSS000637 5,550 individuals African unspecified UKB
PSS000638 974 individuals East Asian UKB
PSS000639 21,403 individuals European Non-British White UKB
PSS000640 6,682 individuals South Asian UKB
PSS000641 57,932 individuals European
(British)
UKB
PSS010627 6,160 individuals,
45.0 % Male samples
Mean = 54.4 years
Sd = 8.4 years
European Italian UKB
PSS009577 Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. Median = 11.4 years
[
  • 3,565 cases
  • , 30,222 controls
]
,
58.5 % Male samples
Mean = 61.7 years European
(white British)
UKB
PSS009578 Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. Median = 11.4 years
[
  • 2,358 cases
  • , 31,429 controls
]
,
58.5 % Male samples
Mean = 61.7 years European
(white British)
UKB
PSS009579 Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. Median = 11.4 years
[
  • 1,207 cases
  • , 32,580 controls
]
,
58.5 % Male samples
Mean = 61.7 years European
(white British)
UKB
PSS009580 Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. Median = 11.4 years
[
  • 11,767 cases
  • , 22,020 controls
]
,
58.5 % Male samples
Mean = 61.7 years European
(white British)
UKB
PSS010641 400 individuals,
47.0 % Male samples
Mean = 53.6 years
Sd = 7.5 years
European Italian UKB
PSS010664 6,182 individuals,
45.0 % Male samples
Mean = 54.5 years
Sd = 8.4 years
European Italian UKB
PSS000714 6,003 individuals African unspecified UKB
PSS000715 1,082 individuals East Asian UKB
PSS000716 23,535 individuals European Non-British White UKB
PSS000717 7,319 individuals South Asian UKB
PSS000718 63,675 individuals European
(British)
UKB
PSS010692 61 individuals,
64.0 % Male samples
Mean = 49.5 years
Sd = 6.5 years
African unspecified Nigerian UKB
PSS010693 61 individuals,
64.0 % Male samples
Mean = 49.5 years
Sd = 6.5 years
African unspecified Nigerian UKB
PSS010694 61 individuals,
64.0 % Male samples
Mean = 49.5 years
Sd = 6.5 years
African unspecified Nigerian UKB
PSS010711 3,622 individuals,
46.0 % Male samples
Mean = 51.9 years
Sd = 8.1 years
African unspecified Nigerian UKB
PSS010725 116 individuals,
55.0 % Male samples
Mean = 49.4 years
Sd = 6.7 years
African unspecified Nigerian UKB
PSS010748 3,819 individuals,
46.0 % Male samples
Mean = 51.9 years
Sd = 8.1 years
African unspecified Nigerian UKB
PSS009608 Median = 11.2 yrs
[
  • 685 cases
  • , 384,936 controls
]
European
(British, Irish)
UKB
PSS000795 1,378 individuals European Participants self-identifying as white MESA
PSS000181 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 4,680 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
African unspecified UKB Genotyping Array Cohort
PSS000182 Cardiovascular disease events were defined as coronary and carotid revascularization, myocardial infarction, ischemic stroke, and all-cause mortality. The CVD events occurring before and after enrollment were included. Events occurring prior to enrollment were identified by either self-reported medical history and/or previous hospital admission documented in an electronic health record.
[
  • 5,397 cases
  • , 42,448 controls
]
,
43.36 % Male samples
Mean = 56.64 years
Sd = 7.99 years
European, East Asian, African unspecified UKB Genotyping Array & Exome Sequencing Cohort
PSS000183 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 10,640 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
East Asian UKB Genotyping Array Cohort
PSS000184 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 439,871 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
European UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 439,871 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
European UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 10,640 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
East Asian UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 4,680 individuals,
45.8 % Male samples
Mean = 56.6 years
Sd = 8.1 years
African unspecified UKB Genotyping Array Cohort
PSS010776 180 individuals,
41.0 % Male samples
Mean = 53.2 years
Sd = 6.5 years
European Polish UKB
PSS010777 192 individuals,
42.0 % Male samples
Mean = 53.2 years
Sd = 6.4 years
European Polish UKB
PSS010778 190 individuals,
42.0 % Male samples
Mean = 53.2 years
Sd = 6.4 years
European Polish UKB
PSS010795 3,935 individuals,
38.0 % Male samples
Mean = 54.4 years
Sd = 7.5 years
European Polish UKB
PSS009627 4,416 individuals,
75.0 % Male samples
European UCC-SMART UCC-SMART
PSS000824 2,097 individuals European Participants self-identifying as white MESA
PSS000825 1,987 individuals European Participants self-identifying as white MESA
PSS009628 Bazzet formula QT-corrected interval calculated from automated QT interval obtained from 12-lead electrocardiograms in TOPMed 26,976 individuals,
65.4 % Male samples
Mean = 59.8 years
Sd = 12.5 years
European, African unspecified, Asian unspecified, Other admixed ancestry, Not reported Combined analysis of European (59.6%), African (18.1%), Asian (2.9%), Admixed American (2.2%), Amish (3.7%) and Undetermined (13.5%) genetic ancestries 9 cohorts
  • ARIC
  • ,BioMe
  • ,CFS
  • ,CHS
  • ,FHS
  • ,JHS
  • ,MESA
  • ,OOA
  • ,WHI
PSS010809 299 individuals,
38.0 % Male samples
Mean = 52.9 years
Sd = 6.6 years
European Polish UKB
PSS009631 ICD-10 diagnosis code for hypertensive heart disease with heart failure, hypertensive heart and chronic kidney disease with heart failure and stage 1 through stage 4 chronic kidney disease, hypertensive heart and chronic kidney disease with heart failure and with stage 5 chronic kidney disease, or heart failure (I11.0, I13.0, I13.2, I50) in BioMe biobank and ICD-10 diagnosis code for hypertensive heart disease with heart failure, hypertensive heart and chronic kidney disease with heart failure and stage 1 through stage 4 chronic kidney disease, hypertensive heart and chronic kidney disease with heart failure and with stage 5 chronic kidney disease, or heart failure (I11.0, I13.0, I13.2, I50) in UKB; ICD-10 diagnosis code for exertional dyspnea (R06.09) and/or physician-documented exertional dyspnea in the problem list; ICD-10 diagnosis code for peripheral edema (R60) and/or physician-documented peripheral edema in the problem list (e.g., “ankle swelling”, “lower extremity swelling”); (e.g., “shortness of breath”, “difficulty breathing”; and “on exertion”, “when exercising”); ICD-10 diagnosis code for dyspnea (R06.0) and/or physician-documented dyspnea in the problem list (e.g., “shortness of breath”, “trouble breathing”) 486,754 individuals,
46.0 % Male samples
Median = 58.0 years African unspecified, Hispanic or Latin American, European, Asian unspecified, NR African, Hispanic/Latino, European, Asian, Other ancestry BioMe, UKB
PSS009637
[
  • 875 cases
  • , 644 controls
]
Not reported NR LIPIGEN (Lipid TransPort Disorders italian Genetic Network) database
PSS010832 3,920 individuals,
38.0 % Male samples
Mean = 54.3 years
Sd = 7.5 years
European Polish UKB
PSS009639 Non-fasting serum lipid levels were measured using the Cobas Integra 400 Plus Chemistry analyser, an automated analyser that employs four different technologies: absorption photometry, fluorescence polarization immunoassay, immune-turbidimetry, and potentiometry for accurate analysis. LDL-C were measured using the homogeneous enzymatic colorimetric assays 2,569 individuals,
42.9 % Male samples
Mean = 33.1 years
Ci = [18.0, 48.2] years
Sub-Saharan African
(South Africans)
SAZ
PSS007809 49 individuals African American or Afro-Caribbean Carribean UKB
PSS007810 49 individuals African American or Afro-Caribbean Carribean UKB
PSS007811 76 individuals African American or Afro-Caribbean Carribean UKB
PSS007812 49 individuals African American or Afro-Caribbean Carribean UKB
PSS007813 49 individuals African American or Afro-Caribbean Carribean UKB
PSS007814 49 individuals African American or Afro-Caribbean Carribean UKB
PSS007820 2,338 individuals African American or Afro-Caribbean Carribean UKB
PSS010860 995 individuals,
51.0 % Male samples
Mean = 55.4 years
Sd = 7.5 years
European white British UKB
PSS010861 1,040 individuals,
51.0 % Male samples
Mean = 55.5 years
Sd = 7.5 years
European white British UKB
PSS007828 2,151 individuals African American or Afro-Caribbean Carribean UKB
PSS010862 1,040 individuals,
51.0 % Male samples
Mean = 55.5 years
Sd = 7.5 years
European white British UKB
PSS010879 19,077 individuals,
46.0 % Male samples
Mean = 56.9 years
Sd = 7.9 years
European white British UKB
PSS009666 7,016 individuals,
54.3 % Male samples
Median = 53.0 years
IQR = [46.0, 60.0] years
South Asian UKB
PSS009667 7,082 individuals,
43.3 % Male samples
Median = 59.0 years
IQR = [45.0, 58.0] years
African American or Afro-Caribbean Black/Caribbean UKB
PSS009668 353,166 individuals,
46.2 % Male samples
Median = 58.0 years
IQR = [51.0, 63.0] years
European White UKB
PSS010893 1,567 individuals,
50.0 % Male samples
Mean = 55.5 years
Sd = 7.4 years
European white British UKB
PSS007875 77 individuals African American or Afro-Caribbean Carribean UKB
PSS010916 18,679 individuals,
46.0 % Male samples
Mean = 56.9 years
Sd = 7.9 years
European white British UKB
PSS000903 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.14 295 individuals European Amsterdam
PSS000904 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.12 1,257 individuals European Amsterdam
PSS000905 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.15 1,185 individuals European Amsterdam
PSS000906 Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.13 1,193 individuals European Amsterdam
PSS007908 2,438 individuals African American or Afro-Caribbean Carribean UKB
PSS007913 78 individuals African American or Afro-Caribbean Carribean UKB
PSS008023 73 individuals East Asian China (East Asia) UKB
PSS008024 73 individuals East Asian China (East Asia) UKB
PSS008025 134 individuals East Asian China (East Asia) UKB
PSS008026 72 individuals East Asian China (East Asia) UKB
PSS008027 73 individuals East Asian China (East Asia) UKB
PSS008028 73 individuals East Asian China (East Asia) UKB
PSS008034 1,716 individuals East Asian China (East Asia) UKB
PSS008042 1,543 individuals East Asian China (East Asia) UKB
PSS009791 6,068 individuals African unspecified UKB
PSS009792 875 individuals East Asian UKB
PSS009793 41,139 individuals European Non-British European UKB
PSS009794 7,638 individuals South Asian UKB
PSS008088 137 individuals East Asian China (East Asia) UKB
PSS000987 Cases are individuals with a clinical diagnosis of long QT syndrome. Of the 1238 cases, 1115 were genotype positive meaning they carried a single rare variant in 1 of the 3 established major LQTS genes (KCNQ1 [LQT1], KCNH2 [LQT2] and SCN5A [LQT3]). 123 cases were genotype negative meaning no rare variant was identified in genes unequivocally associated with nonsyndromic LQTS (KCNQ1, KCNH2, SCN5A, CALM1-3, and TRDN).
[
  • 1,238 cases
  • , 8,219 controls
]
European NR
PSS000988 Cases are individuals with a clinical diagnosis of long QT syndrome. Of the 418 cases, 356 were genotype positive meaning they carried a single rare variant in 1 of the 3 established major LQTS genes (KCNQ1 [LQT1], KCNH2 [LQT2] and SCN5A [LQT3]). 62 cases were genotype negative meaning no rare variant was identified in genes unequivocally associated with nonsyndromic LQTS (KCNQ1, KCNH2, SCN5A, CALM1-3, and TRDN).
[
  • 418 cases
  • , 1,671 controls
]
East Asian
(Japanese)
NR
PSS000989 Cases are individuals with a clinical diagnosis of long QT syndrome. Of the 1238 cases, 1115 were genotype positive meaning they carried a single rare variant in 1 of the 3 established major LQTS genes (KCNQ1 [LQT1], KCNH2 [LQT2] and SCN5A [LQT3]). 123 cases were genotype negative meaning no rare variant was identified in genes unequivocally associated with nonsyndromic LQTS (KCNQ1, KCNH2, SCN5A, CALM1-3, and TRDN).
[
  • 1,238 cases
  • , 8,219 controls
]
European NR
PSS000989 Cases are individuals with a clinical diagnosis of long QT syndrome. Of the 418 cases, 356 were genotype positive meaning they carried a single rare variant in 1 of the 3 established major LQTS genes (KCNQ1 [LQT1], KCNH2 [LQT2] and SCN5A [LQT3]). 62 cases were genotype negative meaning no rare variant was identified in genes unequivocally associated with nonsyndromic LQTS (KCNQ1, KCNH2, SCN5A, CALM1-3, and TRDN).
[
  • 418 cases
  • , 1,671 controls
]
East Asian
(Japanese)
NR
PSS008121 1,719 individuals East Asian China (East Asia) UKB
PSS008126 137 individuals East Asian China (East Asia) UKB
PSS011043 4,292 individuals,
42.0 % Male samples
Mean = 51.82 years
Sd = 8.06 years
African American or Afro-Caribbean
(African American)
UKB
PSS011044 970 individuals,
32.0 % Male samples
Mean = 52.47 years
Sd = 7.81 years
East Asian UKB
PSS011045 9,527 individuals,
47.0 % Male samples
Mean = 56.86 years
Sd = 8.05 years
European UKB
PSS011046 5,137 individuals,
53.0 % Male samples
Mean = 53.37 years
Sd = 8.43 years
South Asian UKB
PSS000292 Composite end point of cardiovascular events was defined as myocardial infarction, ischemic stroke, and death from coronary heart disease. Death from coronary heart disease was defined on the basis of codes 412 and 414 (ICD-9) or I22–I23 and I25 (ICD-10) in the Swedish Cause of Death Register. Myocardial infarction was defined on the basis of codes 410 and I21 in the International Classification of Diseases, 9th Revision and 10th Revision (ICD-9 and ICD-10), respectively. Ischemic stroke was defined on the basis of codes 434 or 436 (ICD-9) and I63 or I64 (ICD-10). Median = 10.6 years
[
  • 238 cases
  • , 3,994 controls
]
European MDC
PSS011066 37,317 individuals,
41.98 % Male samples
Mean = 51.37 years
Sd = 10.82 years
East Asian InterASIA China MUCA, CIMIC
PSS011067 21,653 individuals,
41.98 % Male samples
Mean = 51.22 years
Sd = 10.78 years
East Asian InterASIA China MUCA, CIMIC
PSS011068 15,664 individuals,
41.98 % Male samples
Mean = 51.57 years
Sd = 10.87 years
East Asian InterASIA China MUCA, CIMIC
PSS009892 75,973 individuals,
57.2 % Male samples
Mean = 60.4 years
Sd = 6.6 years
European UKB
PSS008245 165 individuals South Asian India (South Asia) UKB
PSS008246 159 individuals South Asian India (South Asia) UKB
PSS008247 299 individuals South Asian India (South Asia) UKB
PSS008248 165 individuals South Asian India (South Asia) UKB
PSS008249 165 individuals South Asian India (South Asia) UKB
PSS008250 166 individuals South Asian India (South Asia) UKB
PSS008256 5,987 individuals South Asian India (South Asia) UKB
PSS008264 5,470 individuals South Asian India (South Asia) UKB
PSS011097 2,669 individuals Greater Middle Eastern (Middle Eastern, North African or Persian)
(Arab)
NR N total after excluding missing values = 2,553
PSS008311 305 individuals South Asian India (South Asia) UKB
PSS008344 6,098 individuals South Asian India (South Asia) UKB
PSS008349 307 individuals South Asian India (South Asia) UKB
PSS008465 25 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008466 25 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008467 49 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008468 26 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008469 26 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008470 26 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS008478 1,122 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS001058 3,020 individuals,
76.0 % Male samples
Mean = 49.0 years
Sd = 6.0 years
European Whitehall
PSS001059 Cases are individuals with familial hypercholesterolaemia (FH). For the Simon Broome British Heart Foundation Study (SBFH), the diagnostic criteria for FH were defined by the Simon Broome Register criteria as an untreated total cholesterol above 7.5mmol/L or an LDL-C above 4.9mmol/L, and a family history of hypercholesterolaemia and/or early coronary heart disease for “possible FH”, and when together with the presence of tendon xanthomas either in the patient or in a first degree relative, as “definite FH”. Of the 640 FH individuals, 321 have FH with no known mutation, whilst 319 have FH with a known mutation.
[
  • 640 cases
  • , 3,020 controls
]
European Whitehall Cases from the Oxford FH study (OXFH) and the Simon Broome British Heart Foundation Study (SBFH)
PSS008486 1,033 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS001072 Cases were individuals with hypobetalipoproteinemia (HBL). Of the 111 individuals with HBL, 38 had polygenic HBL, 40 had monogenic HBL and 33 had HBL from an unknown cause. Polgenic HBL was defined by a polygenic risk score (PRS) < 10th percentile of controls (PRS < 0.5925). For the 40 monogenic HBL individuals, 38 carried heterozygous APOB loss of fucntion variants and 2 carried heterozygous PCSK9 loss of function variants. In a subset of HBL cases, 7 polygenic cases , 26 monogenic cases and 13 uknown cause cases had liver steatosis. Whilst 17, 6 and 9 individuals did not have liver steatosis, respectively. Liver steatosis was diagnosed by abdominal ultrasonography. Alanine aminotransferase (ALT), aspartate aminotransferase, and gamma-glutamyl transpeptidase were determined by IFCC-standardized enzymatic methods using dedicated commercial kits. Individuals with ALT >1 upper limit of normal (>97.5th percentile) were considered to likely have liver injury.
[
  • 111 cases
  • , 856 controls
]
Not reported NR Cases were obtained from the HYPOCHOL and GENLIP studies. Controls were obtained from the PREGO and GAZEL cohorts and the Finstère area, which are part of the FranceGenRef Consortium.
PSS011201 68,978 individuals,
31.2 % Male samples
East Asian TWB
PSS011203 1,480 individuals,
36.8 % Male samples
East Asian UKB
PSS011204 6,303 individuals,
54.1 % Male samples
South Asian UKB
PSS011206 3,802 individuals,
45.9 % Male samples
African American or Afro-Caribbean UKB
PSS011207 423,596 individuals,
45.9 % Male samples
European UKB
PSS008533 50 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS001083 Of the 2,531 participants, 1,809 had longitudinal observations for total cholesterol (mg/dL), high density lipoprotein cholesterol (mg/dL) and trigycerides (mg/dL), 1,801 had longitudinal observations for low density lipoprotein cholesterol (mg/dL), 1,325 had longitudinal observations for waist circumference (inches), 2,355 had longitudinal observations for body mass index (kg/m^2) and 1,572 had longitudinal observations for homocysteine (μmol/L). 2,531 individuals,
40.0 % Male samples
Mean = 48.0 years
Sd = 12.0 years
European, Asian unspecified, Hispanic or Latin American, African unspecified, NR European = 1,999, Asian unspecified = 228, Hispanic or Latin American = 101, African unspecified = 51, Not reported = 152 NR Participants were obtained from the Scientific Wellness Program.
PSS000369 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). 334 individuals,
69.2 % Male samples
Mean = 11.1 years
Sd = 0.48 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
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
PSS000374 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). 1,318 individuals,
47.6 % Male samples
Mean = 11.1 years European TRAILS
PSS008566 1,151 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) 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
PSS001084 Moderate Age-Related Diabetes (MARD) vs. controls
[
  • 2,853 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001085 Moderate Obesity-related Diabetes (MOD) vs. controls
[
  • 1,372 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001086 Severe Autoimmune Diabetes (SAID) vs. controls
[
  • 450 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001087 Severe Insulin-Deficient Diabetes (SIDD) vs. controls
[
  • 1,186 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001088 Severe Insulin-Resistant Diabetes (SIRD) vs. controls
[
  • 1,125 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS008571 50 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS010124 29,354 individuals,
45.5 % Male samples
Mean = 55.4 years European, NR 85% European PHB
PSS001124 Individuals with severe hypercholesterolemia (HC) had a LDL-C level > 4.9 mmol/L. 124 individuals had severe HC, based on this criteria. Individuals with intermediate HC had a LDL-C level 3.0 ≤ LDL‐C ≤ 4.9 mmol/L. 1927 individuals had intermediate HC, based on this criteria. Individuals classified as having normal LDL-C levels had LDL-C levels < 3.0 mmol/L. 2733 individuals had normal LDL-C levels, based on this criteria. 4,787 individuals,
48.0 % Male samples
Mean = 31.0 years
Sd = 0.2 years
European NFBC
PSS001144 4,273 individuals African unspecified AADM
PSS001145 707 individuals African unspecified AADM
PSS001146 3,566 individuals African unspecified AADM
PSS001147 10,460 individuals African unspecified AWI-Gen
PSS001148 1,745 individuals African unspecified AWI-Gen
PSS001149 4,972 individuals Sub-Saharan African AWI-Gen
PSS001150 3,743 individuals African unspecified AWI-Gen
PSS001151 15,242 individuals South Asian G&H
PSS001152 118,260 individuals East Asian KoGES
PSS001153 1,341 individuals African American or Afro-Caribbean MGI
PSS001154 17,190 individuals European MGI
PSS008691 225 individuals European Italy (South Europe) UKB
PSS001156 18,251 individuals African American or Afro-Caribbean MVP Subset not used in discovery dataset
PSS001157 4,155 individuals Asian unspecified MVP Subset not used in discovery dataset
PSS001158 68,381 individuals European MVP Subset not used in discovery dataset
PSS001159 7,669 individuals Hispanic or Latin American MVP Subset not used in discovery dataset
PSS001160 2,138 individuals African American or Afro-Caribbean PMB
PSS001161 28,217 individuals East Asian ToMMo Only participants from Miyagi Prefecture were included
PSS001162 461,918 individuals European, African unspecified, East Asian, South Asian UKB
PSS001163 6,863 individuals African unspecified UKB
PSS001164 1,441 individuals East Asian UKB
PSS001165 389,158 individuals European UKB
PSS001166 6,814 individuals South Asian UKB
PSS008696 226 individuals European Italy (South Europe) UKB
PSS008704 6,312 individuals European Italy (South Europe) UKB
PSS010010 LOW DENSITY LIPOPROTEIN CHOL (LOINC: 13457-7); Quantitative 9,288 individuals European MGI
PSS008712 5,765 individuals European Italy (South Europe) UKB
PSS001175 Cases were individuals with atrial fibrillation. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 14,812 cases
  • , 294,457 controls
]
European UKB
PSS001176 Cases were individuals with atrioventricular preexcitation. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 307 cases
  • , 308,734 controls
]
European UKB
PSS001177 Cases were individuals with congential artery disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 27,072 cases
  • , 282,174 controls
]
European UKB
PSS001178 Cases were individuals with distal conduction disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 2,789 cases
  • , 287,463 controls
]
European UKB
PSS001179 Cases were individuals with implantable cardioverter defibrillators. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 633 cases
  • , 308,608 controls
]
European UKB
PSS001180 Cases were individuals with mitral valve prolapse. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 529 cases
  • , 308,717 controls
]
European UKB
PSS001181 Cases were individuals with non-ischemic cardiomyopathy. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 1,703 cases
  • , 303,768 controls
]
European UKB
PSS001182 Cases were individuals with a pacemaker. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 3,975 cases
  • , 305,295 controls
]
European UKB
PSS001183 Cases were individuals with valve disease. Disease status was ascertained based on data from baseline interviews, hospital diagnosis codes (ICD-9 and ICD-10), cause of death codes (ICD-10), and operation codes. Details of individual selections and disease definitions are described in Supplementary Data 23.
[
  • 6,244 cases
  • , 303,011 controls
]
European UKB
PSS004781 6,409 individuals African unspecified UKB
PSS004782 1,634 individuals East Asian UKB
PSS004783 23,727 individuals European non-white British ancestry UKB
PSS004784 7,640 individuals South Asian UKB
PSS004785 63,825 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS008759 487 individuals European Italy (South Europe) UKB
PSS004806 203 individuals African unspecified UKB
PSS004807 102 individuals East Asian UKB
PSS004808 1,601 individuals European non-white British ancestry UKB
PSS004809 315 individuals South Asian UKB
PSS004810 5,223 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS010052 461,918 individuals European, African unspecified, East Asian, South Asian UKB
PSS010055 22,608 individuals East Asian KBA, KoGES
PSS010056 6,140 individuals,
43.0 % Male samples
Median = 39.0 years Greater Middle Eastern (Middle Eastern, North African or Persian)
(Middle Eastern Arabs)
QBB
PSS008792 6,338 individuals European Italy (South Europe) UKB
PSS010058 Cases are potential clinical FH cases
[
  • 120 cases
  • , 117 controls
]
Not reported NR
PSS008797 490 individuals European Italy (South Europe) UKB
PSS000465 Individuals ≥18 years with clinically diagnosed heterozygous familial hypercholesterolemia (FH) from the BCFH cohort. Individuals who were positive for the common French Canadian variant in the LDLR gene including del.15 kb of the promoter and exon 1, del.5 kb of exons 2 and 3, p.W66G (exon 3), p.E207K (exon 4), p.Y468X (exon 10), or p.C646Y (exon 14) in this study. Fasting clinical lipid profiles were obtained following a 4-week washout of any cholesterol-lowering medications from the CNMA cohort. Individuals who were positive for a LDLR, APOB, or PCSK9 variant that was deemed to cause FH in the UKB cohort.Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes 1,120 individuals,
40.4 % Male samples
Mean = 41.36 years European, NR European (94%), Not reported (6%) BCFH, CNMA, UKB
PSS000466 Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes 389,127 individuals European UKB
PSS010102 626 individuals,
49.4 % Male samples
Mean = 46.2 years European BCFH
PSS010103 313 individuals,
41.5 % Male samples
Mean = 51.0 years South Asian, European, African unspecified, NR South Asian, European, African, NR NR Ontario hypercholesterolemia cohort
PSS010104 89,528 individuals European UKB
PSS008913 61 individuals African unspecified Nigeria (West Africa) UKB
PSS008914 61 individuals African unspecified Nigeria (West Africa) UKB
PSS008915 138 individuals African unspecified Nigeria (West Africa) UKB
PSS008916 61 individuals African unspecified Nigeria (West Africa) UKB
PSS008917 61 individuals African unspecified Nigeria (West Africa) UKB
PSS008918 61 individuals African unspecified Nigeria (West Africa) UKB
PSS008924 3,651 individuals African unspecified Nigeria (West Africa) UKB
PSS008932 3,389 individuals African unspecified Nigeria (West Africa) UKB
PSS010123 443,326 individuals,
45.5 % Male samples
Mean = 57.2 years European, NR 94% European UKB
PSS004966 120 individuals African unspecified UKB
PSS004967 68 individuals East Asian UKB
PSS004968 834 individuals European non-white British ancestry UKB
PSS004969 193 individuals South Asian UKB
PSS004970 3,353 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004971 120 individuals African unspecified UKB
PSS004972 68 individuals East Asian UKB
PSS004973 872 individuals European non-white British ancestry UKB
PSS004974 201 individuals South Asian UKB
PSS004975 3,523 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004976 120 individuals African unspecified UKB
PSS004977 68 individuals East Asian UKB
PSS004978 872 individuals European non-white British ancestry UKB
PSS004979 201 individuals South Asian UKB
PSS004980 3,523 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004986 192 individuals African unspecified UKB
PSS004987 110 individuals East Asian UKB
PSS004988 1,708 individuals European non-white British ancestry UKB
PSS004989 319 individuals South Asian UKB
PSS004990 5,528 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004991 192 individuals African unspecified UKB
PSS004992 110 individuals East Asian UKB
PSS004993 1,708 individuals European non-white British ancestry UKB
PSS004994 319 individuals South Asian UKB
PSS004995 5,528 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004996 192 individuals African unspecified UKB
PSS004997 110 individuals East Asian UKB
PSS004998 1,708 individuals European non-white British ancestry UKB
PSS004999 319 individuals South Asian UKB
PSS005000 5,528 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS008979 140 individuals African unspecified Nigeria (West Africa) UKB
PSS011364 56,192 individuals European UKB
PSS009012 3,850 individuals African unspecified Nigeria (West Africa) UKB
PSS007086 5,632 individuals African unspecified UKB
PSS007087 1,462 individuals East Asian UKB
PSS007088 21,609 individuals European non-white British ancestry UKB
PSS007089 6,776 individuals South Asian UKB
PSS007090 58,749 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS009017 140 individuals African unspecified Nigeria (West Africa) UKB
PSS001155 360 individuals Hispanic or Latin American MGI
PSS010185 1,115 individuals,
41.1 % Male samples
Mean = 46.18 years Hispanic or Latin American HCHS, SOL
PSS007171 6,086 individuals African unspecified UKB
PSS007172 1,615 individuals East Asian UKB
PSS007173 23,728 individuals European non-white British ancestry UKB
PSS007174 7,407 individuals South Asian UKB
PSS007175 64,356 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS009137 191 individuals European Poland (NE Europe) UKB
PSS009138 181 individuals European Poland (NE Europe) UKB
PSS009139 310 individuals European Poland (NE Europe) UKB
PSS009140 191 individuals European Poland (NE Europe) UKB
PSS009141 193 individuals European Poland (NE Europe) UKB
PSS009142 193 individuals European Poland (NE Europe) UKB
PSS009150 3,946 individuals European Poland (NE Europe) UKB