Validation of an Integrated Genetic‐Epigenetic Test for the Assessment of Coronary Heart Disease

Abstract

Background Coronary heart disease (CHD) is the leading cause of death in the world. Unfortunately, many of the key diagnostic tools for CHD are insensitive, invasive, and costly; require significant specialized infrastructure investments; and do not provide information to guide postdiagnosis therapy. In prior work using data from the Framingham Heart Study, we provided in silico evidence that integrated genetic–epigenetic tools may provide a new avenue for assessing CHD. Methods and Results In this communication, we use an improved machine learning approach and data from 2 additional cohorts, totaling 449 cases and 2067 controls, to develop a better model for ascertaining symptomatic CHD. Using the DNA from the 2 new cohorts, we translate and validate the in silico findings into an artificial intelligence–guided, clinically implementable method that uses input from 6 methylation‐sensitive digital polymerase chain reaction and 10 genotyping assays. Using this method, the overall average area under the curve, sensitivity, and specificity in the 3 test cohorts is 82%, 79%, and 76%, respectively. Analysis of targeted cytosine‐phospho‐guanine loci shows that they map to key risk pathways involved in atherosclerosis that suggest specific therapeutic approaches. Conclusions We conclude that this scalable integrated genetic–epigenetic approach is useful for the diagnosis of symptomatic CHD, performs favorably as compared with many existing methods, and may provide personalized insight to CHD therapy. Furthermore, given the dynamic nature of DNA methylation and the ease of methylation‐sensitive digital polymerase chain reaction methodologies, these findings may pave a pathway for precision epigenetic approaches for monitoring CHD treatment response.

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

“…As a result, our algorithm, which relies on the main effects of methylation and GxMeth interaction effects is robust to population stratification effects. Indeed, in the Iowa cohort from our 2023 Journal of the American Heart Association paper [ 16 ], there was no difference in the clustering of the non-White subjects. Still, to be certain, any metric must be broadly tested and we note our academic-commercial consortium is firmly committed to the understanding of the utility of epigenetic predictors in non-European populations [ 36 – 38 ].…”

“…Table 2 shows the parameters that differ for each test, including the sensitivity, specificity, and cost of each test [ 16 , 27 ]. The costs that do not depend on the outcome of the test are the cost of the test, the cost of the side effects of the test, and the costs of the appointments to order and discuss the results of the test.…”

“…Some of the most intriguing of these improvements are in the rapidly developing field of cardiac epigenetics [ 15 ]. 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 ].…”

A retrospective case-control study for Clinical Validation of mutated ZNF208 as a novel biomarker of fatal blast crisis in Chronic Myeloid Leukemia

“…We used NGS-based targeted resequencing and Sanger sequencing for clinical validation of ZNF G64A mutation as AP-/BC-CML. Targeted resequencing and Sanger sequencing along with other similar techniques are routinely being used for clinical validation of molecular biomarkers [38][39][40][41][42][43][44][45].…”

Menu Engineering on Food to Increase Revenue at Laku Café, Gading Serpong

“…Café is a place that millennials like as a place to hang out or a meeting place for business people. According to (Philibert et al, 2023), a café is a place to eat that provides snacks and drinks such as bread, iced chocolate and coffee.…”