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Gao et al. BMC Cardiovasc Disord (2021) 21:240 https://doi.org/10.1186/s12872-021-02001-w RESEARCH Open Access Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population Yan Gao1†, Huifang Pang1†, Bowang Chen1, ChaoQun Wu1, Yanping Wang1, Libo Hou1, Siming Wang1, Dianjianyi Sun2 and Xin Zheng1* Abstract Background: Systemic studies of association of genome-wide DNA methylated sites with cardiovascular disease (CVD) in prospective cohorts are lacking. Our aim was to identify DNA methylation sites associated with the risk of CVD and further investigate their potential predictive value in CVD development for high-risk subjects. Methods: We performed an epigenome-wide association study (EWAS) to identify CpGs related to CVD develop- ment in a Chinese population.We adopted a nested case–control design based on data from China PEACE Million Persons Project. A total of 83 cases who developed CVD events during follow-up and 83 controls who were matched with cases by age, sex, BMI, ethnicity, medications treatment and behavior risk factors were included in the discovery stage. Genome-wide DNA methylation from whole blood was detected using Infnium Human Methylation EPIC Beadchip (850 K). For signifcant CpGs [FDR(false discovery rate) < 0.005], we further validated in an independent cohort including 38 cases and 38 controls. Results: In discovery set, we identifed 8 signifcant CpGs (FDR < 0.005) associated with the risk of CVD after adjust- ment for cell components, demographic and cardiac risk factors and the frst 5 principal components. Two of these identifed CpGs (cg06901278 and cg09306458 in UACA ) were replicated in another independent set (p < 0.05). Enrich- ment analysis in 787 individual genes from 1036 CpGs in discovery set revealed a signifcant enrichment for anatomi- cal structure homeostasis as well as regulation of vesicle-mediated transport. Receiver operating characteristic (ROC) analysis showed that the model combined 8 CVD-related CpGs with baseline characteristics showed much better predictive efect for CVD occurrence compared with the model with baseline characteristics only [AUC (area under the curve) 0.967, 95% CI (0.942 0.991); AUC 0.621, 95% CI (0.536 0.706); p 9.716E-15]. = − = − = Conclusions: Our study identifed the novel CpGs associated with CVD development and revealed their additional predictive power in the risk of CVD for high-risk subjects. Keywords: EWAS, DNA methylation, CVD Introduction *Correspondence: [email protected] Cardiovascular disease (CVD), a complex disease that † Yan Gao and Huifang Pang: Co-frst author is attributed to the interaction between environmental 1 National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Chinese Academy of Medical and genetic factors, is the leading cause of death in most Sciences and Peking Union Medical College, Fuwai Hospital, National countries [1, 2]. It is necessary to elucidate the underlying Center for Cardiovascular Diseases, 167 Beilishi Road, Beijing 100037, biological mechanisms of CVD to enable early diagnosis People’s Republic of China Full list of author information is available at the end of the article and treatment of the disease. © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Gao et al. BMC Cardiovasc Disord (2021) 21:240 Page 2 of 10 For the development of CVD, it is widely accepted that community population if they were 35–75 years old age, sex, high blood pressure, smoking, dyslipidemia, and and could confrm their residence in a selected region diabetes are the major risk factors. Furthermore, over the including 141 primary health care sites (88 rural coun- past few years, many genome-wide association studies ties and 53 urban districts) from all 31 provinces in the (GWAS) have identifed relevant genetic polymorphisms mainland of China from September 15, 2014 to June as risk factors, but the results that known risk loci only 20, 2017. Te participants were initially screened for account for a small proportion of risk are not encourag- high-risk of CVD by measurements of blood pressure, ing for personal risk prediction based on genotyping [3]. height, weight and blood lipid, and a questionnaire on Tis suggests other risk factors possibly afect the devel- cardiovascular-related health status. Te subjects at opment of CVD between genetics and environmental high-risk of CVD were identifed if they met at least one factors, such as epigenetics. of four criteria: 1. Medical history of myocardial infarc- Epigenetics is based on stable and heritable alterations tion (MI), percutaneous coronary intervention (PCI), in gene expression without changes in the DNA sequence coronary artery bypass grafting (CABG) treatment, or itself [4]. DNA methylation is a crucial type of epigenetic stroke; 2. High blood pressure defned as systolic blood modifcation, by which a methyl group covalent bonds pressure (SBP) ≥ 160 mmHg or diastolic blood pressure ′ ′ to the C5 position of cytosine in 5 -C-phosphate-G-3 (DBP) ≥ 100 mmHg; 3. Dyslipidemia defned as low- (CpG) dinucleotides, ultimately regulating the gene tran- density lipoprotein cholesterol (LDL-C) ≥ 160 mg/dL scription activity and alter biological functions [5]. Pre- (4.14 mmol/L) or high-density lipoprotein cholesterol vious studies have demonstrated associations of DNA (HDL-C) < 30 mg/dL (0.78 mmol/L); 4. Risk of CVD in methylation with atherosclerosis [6, 7], ischemic heart 10 years ≥ 20% based on WHO/ISH Cardiovascular Risk disease [8], coronary heart disease (CHD) [8], coronary Prediction Charts for the Western Pacifc Region B [13]. artery disease [9] and acute coronary syndrome (ACS) Te high-risk participants received further health assess- [10]. Besides, DNA methylation is suggested as a bio- ments, including electrocardiography, ultrasound scan, marker for CVD risk [11]. However, the previous evi- blood and urine analysis, and a questionnaire on lifestyle dences were based on cross-sectional studies, lack of the and medical history and were followed up every year to rationale of temperal causality. Systemic identifcation collect information on medication adherence, risk fac- of genome-wide DNA diferential CpGs and analysis of tor control, and any hospitalization. Te data were col- their association with CVD risk are lacking. lected from standardized in-person interviews by trained In the present study, our main objective is to identify medical staf. Te central ethics committee at the China CpGs associated with the risk of CVD and further inves- National Center for Cardiovascular Disease (NCCD) tigate their potential predictive value in CVD devel- approved this project. All participants had completed opment for high-risk subjects. We frst examined the a written informed consent before participation in the association of genome-wide DNA methylation patterns project. from whole blood samples in 83 pairs of case–control In the present study, we performed a nested case–con- participants at high-risk of CVD using Infnium Human trol study based on the high-risk participants from the Methylation EPIC Beadchip (850 K). For identifed sig- MPP cohort to examine and validate the association of nifcant CpGs, we further validated their association with genome-wide CpGs with the development of CVD. Te the development of CVD in another independent cohort. inclusion criteria: 1. Blood samples were collected after And enrichment analysis in Gene Ontology (GO) terms January 1, 2016; 2. Two years follow-up data was avail- was conducted to identify signifcantly enriched catego- able; 3. Te questionnaire for the high-risk participants ries. Finally, we performed the ROC analysis to assess the was available. Patients were excluded if they have self- predictive value of genome-wide signifcant CpGs for the reported any of medical history of cancer, chronic liver risk of CVD. and kidney disease, infectious diseases, or any CVD at baseline. Methods Among the above eligible population, case (subjects Study design and study samples who developed cardiovascular events) and control (sub- Te study samples were collected from the China jects who did not develop cardiovascular events) were 1:1 PEACE Million Persons Project (MPP) cohort. Te matched for age (within 1 year), sex, BMI, the month of design and conduct of the project pilot have been pre- blood collection (within 1 month), medications treatment viously described in detail [12]. In brief, the China- (antiplatelet medications and statins), ethnicity (han or PEACE MPP is a national, population-based screening non-han), current smoking status, and current alcohol project funded by the Chinese government to identify intake at baseline. Ten, 121 pairs were randomly sam- individuals at high-risk of CVD. Te project enrolled pled from the above eligible case–control pairs. Among Gao et al. BMC Cardiovasc Disord (2021) 21:240 Page 3 of 10 them, 83 pairs case–control and 38 pairs case–control meal or random blood glucose greater than 11.1 mmol/L, were randomly selected and regarded as the discovery set or any kind of hypoglycemic agents.
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