社会经济、生活方式和心脏代谢因素对表观遗传年龄加速的因果效应的遗传证据。

Genetic Evidence for Causal Effects of Socioeconomic, Lifestyle, and Cardiometabolic Factors on Epigenetic-Age Acceleration.

作者信息

Kong Lijie, Ye Chaojie, Wang Yiying, Hou Tianzhichao, Zheng Jie, Zhao Zhiyun, Li Mian, Xu Yu, Lu Jieli, Chen Yuhong, Xu Min, Wang Weiqing, Ning Guang, Bi Yufang, Wang Tiange

机构信息

Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

J Gerontol A Biol Sci Med Sci. 2023 Jul 8;78(7):1083-1091. doi: 10.1093/gerona/glad078.

DOI:10.1093/gerona/glad078

PMID:36869809

Abstract

GrimAge acceleration (GrimAgeAccel) and PhenoAge acceleration (PhenoAgeAccel) are DNA methylation-based markers of accelerated biological aging, standing out in predicting mortality and age-related cardiometabolic morbidities. Causal risk factors for GrimAgeAccel and PhenoAgeAccel are unclear. In this study, we performed 2-sample univariable and multivariable Mendelian randomization (MR) to investigate causal associations of 19 modifiable socioeconomic, lifestyle, and cardiometabolic factors with GrimAgeAccel and PhenoAgeAccel. Instrument variants representing 19 modifiable factors were extracted from genome-wide association studies (GWASs) with up to 1 million Europeans. Summary statistics for GrimAgeAccel and PhenoAgeAccel were derived from a GWAS of 34 710 Europeans. We identified 12 and 8 factors causally associated with GrimAgeAccel and PhenoAgeAccel, respectively. Smoking was the strongest risk factor (β [standard error {SE}]: 1.299 [0.107] year) for GrimAgeAccel, followed by higher alcohol intake, higher waist circumference, daytime napping, higher body fat percentage, higher body mass index, higher C-reactive protein, higher triglycerides, childhood obesity, and type 2 diabetes; whereas education was the strongest protective factor (β [SE]: -1.143 [0.121] year), followed by household income. Furthermore, higher waist circumference (β [SE]: 0.850 [0.269] year) and education (β [SE]: -0.718 [0.151] year) were the leading causal risk and protective factors for PhenoAgeAccel, respectively. Sensitivity analyses strengthened the robustness of these causal associations. Multivariable MR analyses further demonstrated independent effects of the strongest risk and protective factors on GrimAgeAccel and PhenoAgeAccel, respectively. In conclusion, our findings provide novel quantitative evidence on modifiable causal risk factors for accelerated epigenetic aging, suggesting promising intervention targets against age-related morbidity and improving healthy longevity.

摘要

GrimAge加速（GrimAgeAccel）和PhenoAge加速（PhenoAgeAccel）是基于DNA甲基化的生物衰老加速标志物，在预测死亡率和与年龄相关的心脏代谢疾病方面表现突出。GrimAgeAccel和PhenoAgeAccel的因果风险因素尚不清楚。在本研究中，我们进行了两样本单变量和多变量孟德尔随机化（MR），以研究19种可改变的社会经济、生活方式和心脏代谢因素与GrimAgeAccel和PhenoAgeAccel之间的因果关联。代表19种可改变因素的工具变量是从对多达100万欧洲人的全基因组关联研究（GWAS）中提取的。GrimAgeAccel和PhenoAgeAccel的汇总统计数据来自对34710名欧洲人的GWAS。我们分别确定了12个和8个与GrimAgeAccel和PhenoAgeAccel有因果关联的因素。吸烟是GrimAgeAccel最强的风险因素（β[标准误{SE}]：1.299[0.107]年），其次是较高的酒精摄入量、较高的腰围、白天小睡、较高的体脂百分比、较高的体重指数、较高的C反应蛋白、较高的甘油三酯、儿童期肥胖和2型糖尿病；而教育是最强的保护因素（β[SE]：-1.143[0.121]年），其次是家庭收入。此外，较高的腰围（β[SE]：0.850[0.269]年）和教育（β[SE]：-0.718[0.151]年）分别是PhenoAgeAccel的主要因果风险和保护因素。敏感性分析增强了这些因果关联的稳健性。多变量MR分析进一步证明了最强风险和保护因素分别对GrimAgeAccel和PhenoAgeAccel的独立影响。总之，我们的研究结果为加速表观遗传衰老的可改变因果风险因素提供了新的定量证据，表明针对与年龄相关疾病和改善健康长寿有前景的干预靶点。