Abstract 13530: Epi+Gen CHD: A More Sensitive and Cost-Effective Tool to Assess Risk and Monitor Treatment Response for Coronary Heart Disease

Abstract

Coronary heart disease (CHD) is preventable, but current lipid-based risk assessment tools such as The Framingham Risk Score (FRS) and ASCVD Pooled Cohort Equation (PCE) have limitations. Using DNA-based genetic and epigenetic biomarkers, we have developed a more sensitive and cost-effective incident CHD risk assessment tool, Epi+Gen CHD, that can provide actionable insights and monitor treatment response. This test can be administered remotely via telemedicine using at-home sampling, or in a clinical setting. Epi+Gen CHD was developed and validated using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM). It incorporates five SNPs and three methylation markers for predicting 3-year incident CHD. It was more sensitive than FRS and PCE and had high generalizability across cohorts with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. In contrast, the sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for the PCE. To assess cost effectiveness, we conducted cost-utility analyses of Epi+Gen CHD. As compared to the PCE, we found that the use of Epi+Gen CHD was associated with both better survival and highly competitive negative incremental cost-effective ratios (cost savings) ranging from -$42,000 to -$-8,000 per quality-adjusted life year with and without accounting for a secondary test. Finally, to understand if the epigenetic biomarkers in Epi+Gen CHD could be leveraged to monitor treatment response, we performed a proof-of-concept study that assessed the three Epi+Gen CHD methylation sites in 39 subjects before and after 3 months of biochemically verified smoking cessation, then analyzed the relationship between change in methylation at each of the sites to the change in smoking intensity (cg05575921 methylation). We showed that in those who quit smoking, methylation change at one Epi+Gen CHD site (cg00300879) was significantly associated with change in smoking intensity (p < 0.04). We conclude that Epi+Gen CHD can identify patients at risk for CHD, save more lives, reduce more healthcare spending and guide prevention interventions better than current methods.