Association Between DNA Methylation and Blood Pressure: A 5-Year Longitudinal Twin Study

Author:

Hong Xuanming1ORCID,Miao Ke1,Cao Weihua1,Lv Jun1,Yu Canqing1ORCID,Huang Tao1ORCID,Sun Dianjianyi1,Liao Chunxiao1,Pang Yuanjie1,Pang Zengchang2,Yu Min3,Wang Hua4,Wu Xianping5,Liu Yu6,Gao Wenjing1ORCID,Li Liming1ORCID

Affiliation:

1. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.).

2. Qingdao Center for Disease Control and Prevention, China (Z.P.).

3. Zhejiang Center for Disease Control and Prevention, Hangzhou, China (M.Y.).

4. Jiangsu Center for Disease Control and Prevention, Nanjing, China (H.W.).

5. Sichuan Center for Disease Control and Prevention, Chengdu, China (X.W.).

6. Heilongjiang Center for Disease Control and Prevention, Harbin, China (Y.L.).

Abstract

Background: Previous EWASs (Epigenome-Wide Association Studies) have reported hundreds of blood pressure (BP) associated 5′-cytosine-phosphate-guanine-3′ (CpG) sites. However, their results were inconsistent. Longitudinal observations on the temporal relationship between DNA methylation and BP are lacking. Methods: A candidate CpG site association study for BP was conducted on 1072 twins in the Chinese National Twin Registry. PubMed and EMBASE were searched for candidate CpG sites. Cross-lagged models were used to assess the temporal relationship between BP and DNA methylation in 308 twins who completed 2 surveys in 2013 and 2018. Then, the significant cross-lagged associations were validated by adopting the Inference About Causation From Examination of Familial Confounding approach. Finally, to evaluate the cumulative effects of DNA methylation on the progression of hypertension, we established methylation risk scores based on BP-associated CpG sites and performed Markov multistate models. Results: 16 and 20 CpG sites were validated to be associated with systolic BP and diastolic BP, respectively. In the cross-lagged analysis, we detected that methylation of 2 CpG sites could predict subsequent systolic BP, and systolic BP predicted methylation at another 3 CpG sites. For diastolic BP, methylation at 3 CpG sites had significant cross-lagged effects for predicting diastolic BP levels, while the prediction from the opposite direction was observed at one site. Among these, 3 associations were validated in the Inference About Causation From Examination of Familial Confounding analysis. Using the Markov multistate model, we observed that methylation risk scores were associated with the development of hypertension. Conclusions: Our findings suggest the significance of DNA methylation in the development of hypertension.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Internal Medicine

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