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5-Hydroxymethylcytosine signatures in circulating cell-free DNA as diagnostic and predictive biomarkers for coronary artery disease

Authors :
Hang-Yu Chen
Jian Lin
Qianhui Zhu
Songnian Hu
Chaoran Dong
Haibo Zhu
Chuan He
Feng Gao
Jie Long
Jilin Zheng
Yida Tang
Tao Yu
Jiemei Chen
Zilong He
Yiming Liang
Yupeng Liu
Source :
Clinical Epigenetics
Publication Year :
2020
Publisher :
BioMed Central, 2020.

Abstract

Background The 5-hydroxymethylcytosine (5hmC) DNA modification is an epigenetic marker involved in a range of biological processes. Its function has been studied extensively in tumors, neurodegenerative diseases, and atherosclerosis. Studies have reported that 5hmC modification is closely related to the phenotype transformation of vascular smooth muscle cells and endothelial dysfunction. However, its role in coronary artery disease (CAD) has not been fully studied. Results To investigate whether 5hmC modification correlates with CAD pathogenesis and whether 5hmC can be used as a biomarker, we used a low-input whole-genome sequencing technology based on selective chemical capture (hmC-Seal) to firstly generate the 5hmC profiles in the circulating cell-free DNA(cfDNA) of CAD patients, including stable coronary artery disease (sCAD) patients and acute myocardial infarction (AMI) patients. We detected a significant difference of 5hmC enrichment in gene bodies from CAD patients compared with normal coronary artery (NCA) individuals. Our results showed that CAD patients can be well separated from NCA individuals by 5hmC markers. The prediction performance of the model established by differentially regulated 5hmc modified genes were superior to common clinical indicators for the diagnosis of CAD (AUC = 0.93) and sCAD (AUC = 0.93). Specially, we found that 5hmC markers in cfDNA showed prediction potential for AMI (AUC = 0.95), which was superior to that of cardiac troponin I, muscle/brain creatine kinase, and myoglobin. Conclusions Our results suggest that 5hmC markers derived from cfDNA can serve as effective epigenetic biomarkers for minimally noninvasive diagnosis and prediction of CAD.

Details

Language :
English
ISSN :
18687083 and 18687075
Volume :
12
Database :
OpenAIRE
Journal :
Clinical Epigenetics
Accession number :
edsair.doi.dedup.....f53905200041c1b01b6981eaf04e51fe