The genetic basis for survivorship in coronary artery disease

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

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.

Genome-Wide Variants Associated With Longitudinal Survival Outcomes Among Individuals With Coronary Artery Disease

Objective

Coronary artery disease (CAD) is an age-associated condition that greatly increases the risk of mortality. The purpose of this study was to identify gene variants associated with all-cause mortality among individuals with clinically phenotyped CAD using a genome-wide screening approach.

Approach and Results

We performed discovery (n = 684), replication (n = 1,088), and meta-analyses (N = 1,503) for association of genomic variants with survival outcome using secondary data from White participants with CAD from two GWAS sub-studies of the Duke Catheterization Genetics Biorepository. We modeled time from catheterization to death or last follow-up (median 7.1 years, max 12 years) using Cox multivariable regression analysis. Target statistical screening thresholds were p × 10^–8 for the discovery phase and Bonferroni-calculated p-values for the replication (p < 5.3 × 10^–4) and meta-analysis (p < 1.6 × 10^–3) phases. Genome-wide analysis of 785,945 autosomal SNPs revealed two SNPs (rs13007553 and rs587936) that had the same direction of effect across all three phases of the analysis, with suggestive p-value association in discovery and replication and significant meta-analysis association in models adjusted for clinical covariates. The rs13007553 SNP variant, LINC01250, which resides between MYTIL and EIPR1, conferred increased risk for all-cause mortality even after controlling for clinical covariates [HR 1.47, 95% CI 1.17–1.86, p(adj) = 1.07 × 10^–3 (discovery), p(adj) = 0.03 (replication), p(adj) = 9.53 × 10^–5 (meta-analysis)]. MYT1L is involved in neuronal differentiation. TSSC1 is involved in endosomal recycling and is implicated in breast cancer. The rs587936 variant annotated to DAB2IP was associated with increased survival time [HR 0.65, 95% CI 0.51–0.83, p(adj) = 4.79 × 10^–4 (discovery), p(adj) = 0.02 (replication), p(adj) = 2.25 × 10^–5 (meta-analysis)]. DAB2IP is a ras/GAP tumor suppressor gene which is highly expressed in vascular tissue. DAB2IP has multiple lines of evidence for protection against atherosclerosis.

Conclusion

Replicated findings identified two candidate genes for further study regarding association with survival in high-risk CAD patients: novel loci LINC01250 (rs13007553) and biologically relevant candidate DAB2IP (rs587936). These candidates did not overlap with validated longevity candidate genes. Future research could further define the role of common variants in survival outcomes for people with CAD and, ultimately, improve longitudinal outcomes for these patients.

Case-Only Survival Analysis Reveals Unique Effects of Genotype, Sex, and Coronary Disease Severity on Survivorship

Survival bias may unduly impact genetic association with complex diseases; gene-specific survival effects may further complicate such investigations. Coronary artery disease (CAD) is a complex phenotype for which little is understood about gene-specific survival effects; yet, such information can offer insight into refining genetic associations, improving replications, and can provide candidate genes for both mortality risk and improved survivorship in CAD. Building on our previous work, the purpose of this current study was to: evaluate LSAMP SNP-specific hazards for all-cause mortality post-catheterization in a larger cohort of our CAD cases; and, perform additional replication in an independent dataset. We examined two LSAMP SNPs—rs1462845 and rs6788787—using CAD case-only Cox proportional hazards regression for additive genetic effects, censored on time-to-all-cause mortality or last follow-up among Caucasian subjects from the Catheterization Genetics Study (CATHGEN; n = 2,224) and the Intermountain Heart Collaborative Study (IMHC; n = 3,008). Only after controlling for age, sex, body mass index, histories of smoking, type 2 diabetes, hyperlipidemia and hypertension (HR = 1.11, 95%CI = 1.01–1.22, p = 0.032), rs1462845 conferred significantly increased hazards of all-cause mortality among CAD cases. Even after controlling for multiple covariates, but in only the primary cohort, rs6788787 conferred significantly improved survival (HR = 0.80, 95% CI = 0.69–0.92, p = 0.002). Post-hoc analyses further stratifying by sex and disease severity revealed replicated effects for rs1462845: even after adjusting for aforementioned covariates and coronary interventional procedures, males with severe burden of CAD had significantly amplified hazards of death with the minor variant of rs1462845 in both cohorts (HR = 1.29, 95% CI = 1.08–1.55, p = 0.00456; replication HR = 1.25, 95% CI = 1.05–1.49, p = 0.013). Kaplan-Meier curves revealed unique cohort-specific genotype effects on survival. Additional analyses demonstrated that the homozygous risk genotype (‘A/A’) fully explained the increased hazard in both cohorts. None of the post-hoc analyses in control subjects were significant for any model. This suggests that genetic effects of rs1462845 on survival are unique to CAD presence. This represents formal, replicated evidence of genetic contribution of rs1462845 to increased risk for all-cause mortality; the contribution is unique to CAD case status and specific to males with severe burden of CAD.

A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience

The CATHeterization GENetics (CATHGEN) biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010, we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date, race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations included interim information: vital status (verified via National Death Index search and supplemented by Social Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.