TY - JOUR

T1 - In silico genome-wide gene-based association analysis reveals new genes predisposing to coronary artery disease

AU - Zorkoltseva, Irina

AU - Shadrina, Alexandra

AU - Belonogova, Nadezhda

AU - Kirichenko, Anatoly

AU - Tsepilov, Yakov

AU - Axenovich, Tatiana

N1 - Funding Information: budget project of the Institute of Cytology and Genetics, Grant/Award Number: 0259‐2021‐0009/AAAA‐A17‐117092070032‐4; Ministry of Science and Higher Education of the Russian Federation, Grant/Award Number: 5‐100 Best Universities Funding information Publisher Copyright: © 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

PY - 2022/1

Y1 - 2022/1

N2 - Genome-wide association study (GWAS) have identified more than 300 single nucleotide polymorphisms at 163 independent loci associated with coronary artery disease (CAD). However, there is no full understanding about the causal genes for CAD and the mechanisms of their action. We aimed to perform a post GWAS analysis to identify genes whose polymorphism may influence the risk of CAD. Using the UK Biobank GWAS summary statistics, we performed a gene-based association analysis. We found 63 genes significantly associated with CAD due to their within-gene polymorphisms. Many of these genes are well known. Some known CAD genes such as FURIN and SORT1 did not show the gene-based association because their variants had low GWAS signals or gene-based association was inflated by the strong GWAS signal outside the gene. For several known CAD genes, we demonstrated that their effects could be explained not only or not at all by their own variants but by the variants within the neighboring genes controlling their expression. Using several bioinformatics techniques, we suggested potential mechanisms underlying gene-CAD associations. Three genes, CDK19, NCALD, and ARHGEF12 were not previously associated with CAD. The role of these genes should be clarified in further studies.

AB - Genome-wide association study (GWAS) have identified more than 300 single nucleotide polymorphisms at 163 independent loci associated with coronary artery disease (CAD). However, there is no full understanding about the causal genes for CAD and the mechanisms of their action. We aimed to perform a post GWAS analysis to identify genes whose polymorphism may influence the risk of CAD. Using the UK Biobank GWAS summary statistics, we performed a gene-based association analysis. We found 63 genes significantly associated with CAD due to their within-gene polymorphisms. Many of these genes are well known. Some known CAD genes such as FURIN and SORT1 did not show the gene-based association because their variants had low GWAS signals or gene-based association was inflated by the strong GWAS signal outside the gene. For several known CAD genes, we demonstrated that their effects could be explained not only or not at all by their own variants but by the variants within the neighboring genes controlling their expression. Using several bioinformatics techniques, we suggested potential mechanisms underlying gene-CAD associations. Three genes, CDK19, NCALD, and ARHGEF12 were not previously associated with CAD. The role of these genes should be clarified in further studies.

KW - coronary artery disease

KW - gene-based association analysis

KW - GWAS summary statistics

UR - http://www.scopus.com/inward/record.url?scp=85118356967&partnerID=8YFLogxK

U2 - 10.1111/cge.14073

DO - 10.1111/cge.14073

M3 - Article

C2 - 34687547

AN - SCOPUS:85118356967

VL - 101

SP - 78

EP - 86

JO - Clinical Genetics

JF - Clinical Genetics

SN - 0009-9163

IS - 1

ER -