Association between epigenetic age and type 2 diabetes mellitus or glycemic traits: A longitudinal twin study

Author:

Miao Ke12ORCID,Hong Xuanming12,Cao Weihua12,Lv Jun12,Yu Canqing12,Huang Tao12ORCID,Sun Dianjianyi12,Liao Chunxiao12,Pang Yuanjie12,Hu Runhua12,Pang Zengchang3,Yu Min4,Wang Hua5,Wu Xianping6,Liu Yu7,Gao Wenjing12,Li Liming12

Affiliation:

1. Department of Epidemiology and Biostatistics, School of Public Health Peking University Beijing China

2. Key Laboratory of Epidemiology of Major Diseases (Peking University) Ministry of Education Beijing China

3. Qingdao Center for Disease Control and Prevention Qingdao China

4. Zhejiang Center for Disease Control and Prevention Hangzhou China

5. Jiangsu Center for Disease Control and Prevention Nanjing China

6. Sichuan Center for Disease Control and Prevention Chengdu China

7. Heilongjiang Center for Disease Control and Prevention Harbin China

Abstract

AbstractEpigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow‐up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed‐effects and cross‐lagged modelling assessed the cross‐sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross‐sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross‐lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age‐related comorbidities.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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