PGS Catalog - PGS004199 / Coronary artery disease (Polygenic Score)

Polygenic Score (PGS) ID: PGS004199

Predicted Trait
Reported Trait	Coronary artery disease
Mapped Trait(s)	coronary artery disease (EFO_0001645)
Additional Trait Information	UK Biobank codes: non-cancer codes: 1075; ICD9: 410, 4109, 412, 4129; ICD10: I21, I210-I214, I219, I21X, I22, I220, I221, I228, I229, I23, I230-I236, I238, I241, I252; OPCS4: K401-K404, K411-K414, K451-K455, K491, K492, K498, K499, K502, K751-K754, K758, K759

Released in PGS Catalog: Dec. 15, 2023

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Score Details

Score Construction
PGS Name	cad_4
Development Method
Name	LASSO
Parameters	To reduce the number of candidate SNPs to a computationally feasible set, a gwas was performed on the raw phenotype and the 50,000 snps with smallest p-value were retained. The raw phenotype was regressed on age, sex, and the top 20 UK Biobank PCs and a residual phenotype was then built. The LASSO model was trained using these 50k SNPs and the adjusted phenotype.
Variants
Original Genome Build	GRCh37
Number of Variants	6,085
Effect Weight Type	beta

PGS Source
PGS Catalog Publication (PGP) ID	PGP000520
Citation (link to publication)	Raben TG et al. Sci Rep (2023)

Ancestry Distribution
Score Development/Training	European: 100% 200,000 individuals (100%)
PGS Evaluation	European: 100% 1 Sample Sets

Development Samples

Score Development/Training

Study Identifiers	Sample Numbers	Sample Ancestry	Cohort(s)	Phenotype Definitions & Methods	Age of Study Participants	Participant Follow-up Time	Additional Ancestry Description	Additional Sample/Cohort Information
—	200,000 individuals [ 21,091 cases , 178,909 controls ] , 47.9 % Male samples	European	NR	UK Biobank codes: non-cancer codes: 1075; ICD9: 410, 4109, 412, 4129; ICD10: I21, I210-I214, I219, I21X, I22, I220, I221, I228, I229, I23, I230-I236, I238, I241, I252; OPCS4: K401-K404, K411-K414, K451-K455, K491, K492, K498, K499, K502, K751-K754, K758, K759		—	used UK self report 'white' category and then used an adjusted phenotype that includes a regression on the top 20 PCs	—

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)	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
PPM020133	PSS011296\| European Ancestry\| 45,334 individuals	PGP000520 \| Raben TG et al. Sci Rep (2023)	Reported Trait: Coronary artery disease	—	AUROC: 0.75031	—	year of birth, sex	—

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
PSS011296	22,667 sibling pairs	—	45,334 individuals	—	European	—	UKB	—