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

SUBMITTER: Philibert R 

PROVIDER: S-EPMC10727271 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature