Abstract P094: Genetic Risk, Incident Coronary Heart Disease Events, and the Benefits of a Healthy Lifestyle: Joint and Interacting Effects Across Four US Cohorts

Background: Recent GWAS revealed single nucleotide polymorphisms (SNPs) that cumulatively increase risk of CHD in those of European ancestry. We quantified the magnitude of preventive effects of healthy lifestyle against the countervailing effects of genetic risk on incident CHD, and assessed potential interactions. Methods: We extracted SNPs of genome-wide significance (<5 x 10 -8 ) for CHD from CARDIoGRAMplusC4 GWAS, and created a weighted 57-SNP genetic risk score (GRS). Baseline covariates, healthy lifestyle score (including diet pattern, physical activity, smoking and BMI), and incident CHD were harmonized across 4 US cohorts (WHI, ARIC, CHS, and MESA) using dbGaP data. Pooled analyses were run using one-step individual participant data multivariate regressions in Caucasians without prevalent CVD. Results: Among 22,412 adults, the GRS was associated with incident CHD (n = 3001 cases) across each cohort (pooled GRS quintile (Q)5 vs Q1, RR (95% CI): 1.59 (1.41-1.79)), independent of all demographic and lifestyle variables. The lifestyle score was more strongly associated with CHD (pooled Q1 vs Q5, RR: 1.94 (1.71-2.20)) than the GRS, and better discriminated those who had a CHD event ( P =0.025 for difference in AUROC curves). When compared to population-level analysis, joint effects analysis revealed significant heterogeneity within quartiles of lifestyle score on risk of incident CHD ( Table ). Interactions between the GRS and diet pattern ( P =0.022) and trans fats ( P =0.046) were observed. Effects of trans fats on CHD risk appear to be concentrated in those with a higher GRS: for trans fats >2.4% of energy, RRs for increasing GRS quartiles are 0.92 (0.62-1.36), 1.13 (0.79-1.62), 1.43 (1.01-2.01), and 1.84 (1.30-2.61), compared to those in the lowest quartile of trans fat (<1.3% of energy) and lowest GRS quartile. Conclusion: A joint effects approach reveals significant inter-individual variability in lifestyle on CHD risk by underlying genetic risk that is obscured by a conventional population-level effects approach.