American Heart Journal Plus (May 2022)

Sex-dimorphic gene effects on survival outcomes in people with coronary artery disease

  • Jennifer R. Dungan,
  • Xue Qin,
  • Simon G. Gregory,
  • Rhonda Cooper-Dehoff,
  • Julio D. Duarte,
  • Huaizhen Qin,
  • Martha Gulati,
  • Jacquelyn Y. Taylor,
  • Carl J. Pepine,
  • Elizabeth R. Hauser,
  • William E. Kraus

Journal volume & issue
Vol. 17
p. 100152

Abstract

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Background: Ischemic coronary heart disease (IHD) is the leading cause of death worldwide. Genetic variation is presumed to be a major factor underlying sex differences for IHD events, including mortality. The purpose of this study was to identify sex-specific candidate genes associated with all-cause mortality among people diagnosed with coronary artery disease (CAD). Methods: We performed a sex-stratified, exploratory genome-wide association (GWAS) screen using existing data from CAD-diagnosed males (n = 510) and females (n = 174) who reported European ancestry from the Duke Catheterization Genetics biorepository. Extant genotype data for 785,945 autosomal SNPs generated with the Human Omni1-Quad BeadChip (Illumina, CA, USA) were analyzed using an additive inheritance model. We estimated instantaneous risk of all-cause mortality by genotype groups across the 11-year follow-up using Cox multivariate regression, covarying for age and genomic ancestry. Results: The top GWAS hits associated with all-cause mortality among people with CAD included 8 SNPs among males and 15 among females (p = 1 × 10−6 or 10−7), adjusted for covariates. Cross-sex comparisons revealed distinct candidate genes. Biologically relevant candidates included rs9932462 (EMP2/TEKT5) and rs2835913 (KCNJ6) among males and rs7217169 (RAP1GAP2), rs8021816 (PRKD1), rs8133010 (PDE9A), and rs12145981 (LPGAT1) among females. Conclusions: We report 20 sex-specific candidate genes having suggestive association with all-cause mortality among CAD-diagnosed subjects. Findings demonstrate proof of principle for identifying sex-associated genetic factors that may help explain differential mortality risk in people with CAD. Replication and meta-analyses in larger studies with more diverse samples will strengthen future work in this area.

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