Trait: lipoprotein A measurement

Experimental Factor Ontology (EFO) Information
Identifier EFO_0006925
Description quantification of some lipoprotein A in a sample
Trait category
Lipid or lipoprotein measurement
Synonym Lp(a) measurement

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000313
(GRS49_Lp(a))
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Lipoprotein(a) lipoprotein A measurement 49
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000313/ScoringFiles/PGS000313.txt.gz
PGS000667
(LPA_GRS43)
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Lipoprotein A lipoprotein A measurement 43
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000667/ScoringFiles/PGS000667.txt.gz
PGS000689
(snpnet.Lipoprotein_A)
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Lipoprotein A [nmol/L] lipoprotein A measurement 8,308
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000689/ScoringFiles/PGS000689.txt.gz - Check Terms/Licenses
PGS000752
(PGS_Lpa)
PGP000157 |
Dron JS et al. Circ Genom Precis Med (2021)
Lipoprotein(a) concentration [nmol/L] lipoprotein A measurement 11,446
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000752/ScoringFiles/PGS000752.txt.gz
PGS001963
(portability-PLR_log_lipoA)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Lipoprotein A lipoprotein A measurement 7,887
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001963/ScoringFiles/PGS001963.txt.gz
PGS002181
(portability-ldpred2_log_lipoA)
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Lipoprotein A lipoprotein A measurement 31,355
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002181/ScoringFiles/PGS002181.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
PPM000783 PGS000313
(GRS49_Lp(a))
PSS000376|
European Ancestry|
1,354 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Lipoprotein(a) (mg/l) : 0.3959 Sex, age, age^2
PPM001390 PGS000667
(LPA_GRS43)
PSS000607|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident coronary artery disease HR: 1.07 [1.0, 1.14] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry, measured lipoprotein(a)
PPM001391 PGS000667
(LPA_GRS43)
PSS000610|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident peripheral arterial disease HR: 1.15 [1.02, 1.28] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry, measured lipoprotein(a)
PPM001378 PGS000667
(LPA_GRS43)
PSS000613|
African Ancestry|
6,521 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Measured levels of lipoprotein(a) : 0.038
Pearson correlation coefficient: 0.07
Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001379 PGS000667
(LPA_GRS43)
PSS000614|
East Asian Ancestry|
2,774 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Measured levels of lipoprotein(a) : 0.078
Pearson correlation coefficient: 0.281
Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001380 PGS000667
(LPA_GRS43)
PSS000615|
European Ancestry|
350,903 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Measured levels of lipoprotein(a) : 0.595
Pearson correlation coefficient: 0.717
Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001381 PGS000667
(LPA_GRS43)
PSS000616|
South Asian Ancestry|
6,203 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Measured levels of lipoprotein(a) : 0.11
Pearson correlation coefficient: 0.371
Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001382 PGS000667
(LPA_GRS43)
PSS000611|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident composite atherosclerotic cardiovascular disease HR: 1.29 [1.26, 1.33] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001383 PGS000667
(LPA_GRS43)
PSS000608|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident cardiovascular disease mortality HR: 1.09 [1.02, 1.16] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001384 PGS000667
(LPA_GRS43)
PSS000609|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident myocardial infarction HR: 1.38 [1.33, 1.43] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001385 PGS000667
(LPA_GRS43)
PSS000607|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident coronary artery disease HR: 1.45 [1.41, 1.5] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001386 PGS000667
(LPA_GRS43)
PSS000612|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident stroke HR: 1.12 [1.04, 1.19] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001387 PGS000667
(LPA_GRS43)
PSS000610|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident peripheral arterial disease HR: 1.34 [1.26, 1.42] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry
PPM001388 PGS000667
(LPA_GRS43)
PSS000611|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident composite atherosclerotic cardiovascular disease HR: 1.06 [1.01, 1.11] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry, measured lipoprotein(a)
PPM001389 PGS000667
(LPA_GRS43)
PSS000609|
European Ancestry|
283,540 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident myocardial infarction HR: 1.09 [1.01, 1.17] Age, sex, assessment center, genotyping batch, PCs (1-5) of ancestry, measured lipoprotein(a)
PPM001392 PGS000667
(LPA_GRS43)
PSS000606|
European Ancestry|
144,350 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident atherosclerotic cardiovascular disease in individuals with borderline-intermediate risk of atherosclerotic cardiovascular disease AUROC: 0.642 [0.634, 0.649]
C-index: 0.641 (0.0004)
QRISK3
PPM001393 PGS000667
(LPA_GRS43)
PSS000606|
European Ancestry|
144,350 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident atherosclerotic cardiovascular disease in individuals with borderline-intermediate risk of atherosclerotic cardiovascular disease AUROC: 0.642 [0.635, 0.649]
C-index: 0.641 (0.0004)
QRISK3, measured lipoprotein(a)
PPM001394 PGS000667
(LPA_GRS43)
PSS000605|
European Ancestry|
113,703 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident atherosclerotic cardiovascular disease in individuals with borderline-intermediate risk ofatherosclerotic cardiovascular disease AUROC: 0.611 [0.603, 0.617]
C-index: 0.611 (0.004)
Pooled Cohort Equations
PPM001395 PGS000667
(LPA_GRS43)
PSS000605|
European Ancestry|
113,703 individuals
PGP000127 |
Trinder M et al. JAMA Cardiol (2020)
Reported Trait: Incident atherosclerotic cardiovascular disease in individuals with borderline-intermediate risk of atherosclerotic cardiovascular disease AUROC: 0.611 [0.603, 0.617]
C-index: 0.611 (0.004)
Pooled Cohort Equations, measured lipoprotein(a)
PPM001417 PGS000689
(snpnet.Lipoprotein_A)
PSS000719|
African Ancestry|
5,018 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Lipoprotein A [nmol/L] : 0.00769
Spearman's ρ: 0.058
Age, sex, PCs(1-40)
PPM001452 PGS000689
(snpnet.Lipoprotein_A)
PSS000720|
East Asian Ancestry|
980 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Lipoprotein A [nmol/L] : 0.06202
Spearman's ρ: 0.164
Age, sex, PCs(1-40)
PPM001487 PGS000689
(snpnet.Lipoprotein_A)
PSS000721|
European Ancestry|
19,003 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Lipoprotein A [nmol/L] : 0.48522
Spearman's ρ: 0.663
Age, sex, PCs(1-40)
PPM001522 PGS000689
(snpnet.Lipoprotein_A)
PSS000722|
South Asian Ancestry|
6,453 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Lipoprotein A [nmol/L] : 0.16668
Spearman's ρ: 0.375
Age, sex, PCs(1-40)
PPM001557 PGS000689
(snpnet.Lipoprotein_A)
PSS000723|
European Ancestry|
50,709 individuals
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
Reported Trait: Lipoprotein A [nmol/L] : 0.51648
Spearman's ρ: 0.692
Age, sex, PCs(1-40)
PPM007370 PGS000689
(snpnet.Lipoprotein_A)
PSS007176|
African Ancestry|
5,086 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Lipoprotein A : 0.0174 [0.0111, 0.0237]
Incremental R2 (full-covars): 0.00171
PGS R2 (no covariates): 0.00657 [0.00266, 0.01049]
age, sex, UKB array type, Genotype PCs
PPM007371 PGS000689
(snpnet.Lipoprotein_A)
PSS007177|
East Asian Ancestry|
1,452 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Lipoprotein A : 0.01457 [0.0033, 0.02585]
Incremental R2 (full-covars): 0.00715
PGS R2 (no covariates): 0.05715 [0.03579, 0.07851]
age, sex, UKB array type, Genotype PCs
PPM007372 PGS000689
(snpnet.Lipoprotein_A)
PSS007178|
European Ancestry|
19,197 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Lipoprotein A : 0.04874 [0.04353, 0.05396]
Incremental R2 (full-covars): 0.04393
PGS R2 (no covariates): 0.49585 [0.48704, 0.50467]
age, sex, UKB array type, Genotype PCs
PPM007373 PGS000689
(snpnet.Lipoprotein_A)
PSS007179|
South Asian Ancestry|
6,542 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Lipoprotein A : 0.02102 [0.01474, 0.02731]
Incremental R2 (full-covars): 0.01343
PGS R2 (no covariates): 0.13628 [0.12216, 0.1504]
age, sex, UKB array type, Genotype PCs
PPM007374 PGS000689
(snpnet.Lipoprotein_A)
PSS007180|
European Ancestry|
51,385 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
|Ext.
Reported Trait: Lipoprotein A : 0.17636 [0.17114, 0.18158]
Incremental R2 (full-covars): 0.17582
PGS R2 (no covariates): 0.53443 [0.5293, 0.53957]
age, sex, UKB array type, Genotype PCs
PPM001911 PGS000752
(PGS_Lpa)
PSS000954|
European Ancestry|
43,071 individuals
PGP000157 |
Dron JS et al. Circ Genom Precis Med (2021)
Reported Trait: Lipoprotein(a) concentration [nmol/L] Pearson correlation coefficient (r): 0.5
PPM010579 PGS001963
(portability-PLR_log_lipoA)
PSS009452|
European Ancestry|
15,154 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.6002 [0.5899, 0.6103] sex, age, birth date, deprivation index, 16 PCs
PPM010580 PGS001963
(portability-PLR_log_lipoA)
PSS009226|
European Ancestry|
3,133 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.5621 [0.5376, 0.5856] sex, age, birth date, deprivation index, 16 PCs
PPM010581 PGS001963
(portability-PLR_log_lipoA)
PSS008780|
European Ancestry|
5,176 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.4772 [0.4558, 0.498] sex, age, birth date, deprivation index, 16 PCs
PPM010582 PGS001963
(portability-PLR_log_lipoA)
PSS008554|
Greater Middle Eastern Ancestry|
925 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.2941 [0.2334, 0.3525] sex, age, birth date, deprivation index, 16 PCs
PPM010583 PGS001963
(portability-PLR_log_lipoA)
PSS008332|
South Asian Ancestry|
5,230 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.3014 [0.2766, 0.3259] sex, age, birth date, deprivation index, 16 PCs
PPM010584 PGS001963
(portability-PLR_log_lipoA)
PSS008109|
East Asian Ancestry|
1,541 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.1975 [0.1487, 0.2453] sex, age, birth date, deprivation index, 16 PCs
PPM010585 PGS001963
(portability-PLR_log_lipoA)
PSS007896|
African Ancestry|
1,926 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.1097 [0.0651, 0.1539] sex, age, birth date, deprivation index, 16 PCs
PPM010586 PGS001963
(portability-PLR_log_lipoA)
PSS009000|
African Ancestry|
3,050 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.0348 sex, age, birth date, deprivation index, 16 PCs
PPM012295 PGS002181
(portability-ldpred2_log_lipoA)
PSS009452|
European Ancestry|
15,154 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.5799 [0.5692, 0.5903] sex, age, birth date, deprivation index, 16 PCs
PPM012296 PGS002181
(portability-ldpred2_log_lipoA)
PSS009226|
European Ancestry|
3,133 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.5522 [0.5273, 0.5761] sex, age, birth date, deprivation index, 16 PCs
PPM012297 PGS002181
(portability-ldpred2_log_lipoA)
PSS008780|
European Ancestry|
5,176 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.4499 [0.4278, 0.4714] sex, age, birth date, deprivation index, 16 PCs
PPM012298 PGS002181
(portability-ldpred2_log_lipoA)
PSS008554|
Greater Middle Eastern Ancestry|
925 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.2534 [0.1913, 0.3133] sex, age, birth date, deprivation index, 16 PCs
PPM012299 PGS002181
(portability-ldpred2_log_lipoA)
PSS008332|
South Asian Ancestry|
5,230 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.2953 [0.2703, 0.3199] sex, age, birth date, deprivation index, 16 PCs
PPM012301 PGS002181
(portability-ldpred2_log_lipoA)
PSS007896|
African Ancestry|
1,926 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.0348 [-0.0101, 0.0796] sex, age, birth date, deprivation index, 16 PCs
PPM012302 PGS002181
(portability-ldpred2_log_lipoA)
PSS009000|
African Ancestry|
3,050 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.0087 [-0.0269, 0.0443] sex, age, birth date, deprivation index, 16 PCs
PPM012300 PGS002181
(portability-ldpred2_log_lipoA)
PSS008109|
East Asian Ancestry|
1,541 individuals
PGP000263 |
Privé F et al. Am J Hum Genet (2022)
Reported Trait: Lipoprotein A Partial Correlation (partial-r): 0.1432 [0.0936, 0.192] sex, age, birth date, deprivation index, 16 PCs

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
PSS008780 5,176 individuals European Italy (South Europe) UKB
PSS007896 1,926 individuals African American or Afro-Caribbean Carribean UKB
PSS000954 43,071 individuals European UKB
PSS008554 925 individuals Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB
PSS000719 5,018 individuals African unspecified UKB
PSS000720 980 individuals East Asian UKB
PSS000721 19,003 individuals European Non-British White UKB
PSS000722 6,453 individuals South Asian UKB
PSS000723 50,709 individuals European
(British)
UKB
PSS009452 15,154 individuals European UK (+ Ireland) UKB
PSS008109 1,541 individuals East Asian China (East Asia) UKB
PSS000376 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,354 individuals,
47.56 % Male samples
Mean = 16.22 years
Sd = 0.66 years
European TRAILS
PSS009226 3,133 individuals European Poland (NE Europe) UKB
PSS008332 5,230 individuals South Asian India (South Asia) UKB
PSS007176 5,086 individuals African unspecified UKB
PSS007177 1,452 individuals East Asian UKB
PSS007178 19,197 individuals European non-white British ancestry UKB
PSS007179 6,542 individuals South Asian UKB
PSS007180 51,385 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS009000 3,050 individuals African unspecified Nigeria (West Africa) UKB
PSS000605 This subgroup included individuals with complete and imputed data and were classified as having borderline-intermediate ASCVD risk (defined by the Pooled Cohorts Equation) without prevalent ASCVD, diabetes mellitus, severe hypercholesterolemia, or use of cholesterol-lowering medication (10-year risk of 5-20%). Cases included individuals who experienced myocardial infarction, an ischemic stroke or cardiovasulcar mortality events. Median = 11.1 years
[
  • 5,938 cases
  • , 107,765 controls
]
European UKB
PSS000606 This subgroup included individuals with complete and imputed data and were classified as having borderline-intermediate ASCVD risk (defined by QRISK3) without prevalent ASCVD, diabetes mellitus, severe hypercholesterolemia, or use of cholesterol-lowering medication (10-year risk of 5-20%). Cases included individuals who experienced myocardial infarction, an ischemic stroke or cardiovasulcar mortality events. Median = 11.1 years
[
  • 5,505 cases
  • , 138,845 controls
]
European UKB
PSS000607 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. Coronary artery disease defined as: ICD-9 (410, 411, 412, 42979), ICD-10 (I21, I22, I23, I24.1, I25.2) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75) Median = 11.1 years
[
  • 7,771 cases
  • , 275,769 controls
]
European UKB
PSS000608 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. Cardiovascular mortality defined as: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Median = 11.1 years
[
  • 3,539 cases
  • , 280,001 controls
]
European UKB
PSS000609 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. Myocardial infarction defined as: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Median = 11.1 years
[
  • 5,666 cases
  • , 277,874 controls
]
European UKB
PSS000610 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. Peripheral artery disease (non-coronary or cerebrovascular events) defined as: ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Median = 11.1 years
[
  • 2,283 cases
  • , 281,257 controls
]
European UKB
PSS000611 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes. Myocardial infarction: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Ischemic stroke: ICD-9 (434, 436) and ICD-10 (I63, I64). Cardiovascular mortality: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Coronary artery disease: ICD-9 (same as myocardial infarction codes), ICD-10 (same as myocardial infarction codes) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75). Peripheral artery disease (non-coronary or cerebrovascular events): ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up. Median = 11.1 years
[
  • 14,697 cases
  • , 268,843 controls
]
European UKB
PSS000612 At the time of enrollment, particpants were without ASCVD. Participants were not using cholesterol-lowering medication. Ischemic stroke defined as: ICD-9 (434, 436) and ICD-10 (I63, I64) Median = 11.1 years
[
  • 2,938 cases
  • , 280,602 controls
]
European UKB
PSS000613 The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes. Myocardial infarction: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Ischemic stroke: ICD-9 (434, 436) and ICD-10 (I63, I64). Cardiovascular mortality: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Coronary artery disease: ICD-9 (same as myocardial infarction codes), ICD-10 (same as myocardial infarction codes) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75). Peripheral artery disease (non-coronary or cerebrovascular events): ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up. 6,521 individuals African unspecified UKB
PSS000614 The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes. Myocardial infarction: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Ischemic stroke: ICD-9 (434, 436) and ICD-10 (I63, I64). Cardiovascular mortality: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Coronary artery disease: ICD-9 (same as myocardial infarction codes), ICD-10 (same as myocardial infarction codes) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75). Peripheral artery disease (non-coronary or cerebrovascular events): ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up. 2,774 individuals East Asian UKB
PSS000615 The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes. Myocardial infarction: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Ischemic stroke: ICD-9 (434, 436) and ICD-10 (I63, I64). Cardiovascular mortality: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Coronary artery disease: ICD-9 (same as myocardial infarction codes), ICD-10 (same as myocardial infarction codes) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75). Peripheral artery disease (non-coronary or cerebrovascular events): ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up. 350,903 individuals European UKB
PSS000616 The outcomes of myocardial infarction, coronary artery disease, ischemic stroke, peripheral arterial disease, cardiovascular mortality, and a composite of the aforementioned outcomes were based on International Statistical Classification of Diseases and Related Health Problems and Office of Population Censuses and Surveys Classification of Interventions and Procedures codes. Myocardial infarction: ICD-9 (410, 411, 412, 42979) and ICD-10 (I21, I22, I23, I24.1, I25.2). Ischemic stroke: ICD-9 (434, 436) and ICD-10 (I63, I64). Cardiovascular mortality: ICD-10 (any diagnosis code for causes of death related to chapter IX diseases of the circulatory system). Coronary artery disease: ICD-9 (same as myocardial infarction codes), ICD-10 (same as myocardial infarction codes) and OCPS-4 (K40, K41, K42, K43, K44, K45, K46, K47, K48, K49, K50 and K75). Peripheral artery disease (non-coronary or cerebrovascular events): ICD-9 (440, 444, 4438, 4439), ICD-10 (I70, I74, I73.8, I73.9) and OCPS-4 (L50, L51, L52, L54, L58, L59, L60, L63, X09). Incident events were defined as the first event occurring between the date of enrollment and the end of follow-up. 6,203 individuals South Asian UKB