Coronary artery disease effector gene predictions
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Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.
Aragam KG, Jiang T, Goel A, Kanoni S, Wolford B, et al.
Submitted for publication, 2021.
This study integrated eight similarity-based or locus-based predictors of causal genes in order to systematically prioritize likely causal genes for 241 genome-wide association signals found in a large GWAS of nearly 1.2 million participants, including over 180,000 CAD cases. The predictors considered were:
- polygenic priority score generated using the PoPS method
- eQTLs in CAD-relevant tissues from the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) eQTL study or the Genotype-Tissue Expression (GTEx) study
- protein-altering variants that are in strong LD (r2≥0.8) with the CAD sentinel variant
- genes harboring variants responsible for monogenic disorders of cardiovascular relevance according to ClinVar
- genes containing rare coding variants that have been associated with CAD risk in previous whole-exome sequencing or array-based studies
- genes encoding proteins of causal relevance to CAD per Mendelian randomization studies, or that are targets for established cardiovascular drugs
- genes that display cardiovascular-relevant phenotypes in knock-out mice from the International Mouse Phenotyping Consortium or Mouse Genome Informatics database
- the nearest gene to the CAD sentinel variant
Find more details on the Research method tab of the CAD effector predictions interface.