Polygenic Score (PGS) ID: PGS004190

Predicted Trait
Reported Trait Atrial fibrillation
Mapped Trait(s) atrial fibrillation (EFO_0000275)
Additional Trait Information UK Biobank codes: non-cancer codes: 1471, 1483; ICD9: 4273; ICD10: I480-I484, I489
Released in PGS Catalog: Dec. 15, 2023
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Terms and Licenses
PGS obtained from the Catalog should be cited appropriately, and used in accordance with any licensing restrictions set by the authors. See EBI Terms of Use (https://www.ebi.ac.uk/about/terms-of-use/) for additional details.

Score Details

Score Construction
PGS Name afib_5
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 1,972
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
—
[
  • 19,934 cases
  • , 180,066 controls
]
,
47.0 % Male samples
 European NR UK Biobank codes: non-cancer codes: 1471, 1483; ICD9: 4273; ICD10: I480-I484, I489 — 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
PPM020124 PSS011296|
European Ancestry|
45,334 individuals
 PGP000520 |
Raben TG et al. Sci Rep (2023)
 Reported Trait: Hypertension — AUROC: 0.69573 — 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 —