The Reversion of the Epigenetic Signature of Coronary Heart Disease in Response to Smoking Cessation

Abstract

Coronary heart disease (CHD) is the leading cause of death worldwide. However, current diagnostic tools for CHD, such as coronary computed tomography angiography (CCTA), are poorly suited for monitoring treatment response. Recently, we have introduced an artificial-intelligence-guided integrated genetic–epigenetic test for CHD whose core consists of six assays that determine methylation in pathways known to moderate the pathogenesis of CHD. However, whether methylation at these six loci is sufficiently dynamic to guide CHD treatment response is unknown. To test that hypothesis, we examined the relationship of changes in these six loci to changes in cg05575921, a generally accepted marker of smoking intensity, using DNA from a cohort of 39 subjects undergoing a 90-day smoking cessation intervention and methylation-sensitive digital PCR (MSdPCR). We found that changes in epigenetic smoking intensity were significantly associated with reversion of the CHD-associated methylation signature at five of the six MSdPCR predictor sites: cg03725309, cg12586707, cg04988978, cg17901584, and cg21161138. We conclude that methylation-based approaches could be a scalable method for assessing the clinical effectiveness of CHD interventions, and that further studies to understand the responsiveness of these epigenetic measures to other forms of CHD treatment are in order.

The Use of Precision Epigenetic Methods for the Diagnosis and Care of Stable Coronary Heart Disease Reduces Healthcare Costs

“…Furthermore, the contribution of abnormal lipid levels to any individual CHD presentation is somewhat speculative. However, because the methylation signal captured by the six MSdPCR is dynamic and can change in as little as 90 days after the initiation of treatment [ 17 ], it is very possible that precision epigenetic approaches will both inform treatment selection while also serving as a mechanism to determine the effectiveness of treatment.…”

“…Specifically, our commercial-academic consortium has recently shown in three independent cohorts that a method (trade name, PrecisionCHD™) that uses artificial intelligence to interpret the genetically contextual methylation signals from six methylation-sensitive digital polymerase chain reaction assays (MSdPCR) is capable of determining the presence of CHD with an overall area under the curve of 0.82, and with sensitivities and specificities of 79% and 76%, respectively [ 16 ]. Critically for those interested in using precision epigenetics to guide clinical care, each of those six MSdPCR assays maps to pathways known to be critical in the pathogenesis of CHD with changes in their methylation status occurring as a function of therapy [ 17 ]. Although much work needs to be conducted, these and similar findings [ 18 ] suggest that clinical epigenetic approaches have the potential for becoming a common method for assessing, diagnosing, and monitoring CHD care [ 19 ].…”