Journal article
Validation of an Integrated Genetic-Epigenetic Test for the Assessment of Coronary Heart Disease
Journal of the American Heart Association, Vol.12(22), e030934
11/21/2023
DOI: 10.1161/JAHA.123.030934
PMCID: PMC10727271
PMID: 37982274
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.
Details
- Title: Subtitle
- Validation of an Integrated Genetic-Epigenetic Test for the Assessment of Coronary Heart Disease
- Creators
- Robert Philibert - University of IowaTimur K DoganStacey Knight - Intermountain HealthcareFerhaan Ahmad - University of IowaStanley Lau - Southern California Reproductive CenterGeorge Miles - Baylor College of MedicineKirk U Knowlton - Intermountain HealthcareMeeshanthini V Dogan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of the American Heart Association, Vol.12(22), e030934
- DOI
- 10.1161/JAHA.123.030934
- PMID
- 37982274
- PMCID
- PMC10727271
- NLM abbreviation
- J Am Heart Assoc
- eISSN
- 2047-9980
- Language
- English
- Date published
- 11/21/2023
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Molecular Physiology and Biophysics; Psychiatry; Iowa Neuroscience Institute; Cardiovascular Medicine; Fraternal Order of Eagles Diabetes Research Center; Internal Medicine
- Record Identifier
- 9984513359202771
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