中国成年人生活方式和心血管代谢因素与甲基化年龄加速的相关性分析

陈璐; 司佳卉; 孙点剑一; 余灿清; 郭彧; 裴培; 陈君石; 陈铮鸣; 吕筠; 李立明

Abstract

陈璐,司佳卉,孙点剑一,余灿清,郭彧,裴培,陈君石,陈铮鸣,吕筠,李立明.中国成年人生活方式和心血管代谢因素与甲基化年龄加速的相关性分析[J].Chinese journal of Epidemiology,2022,43(7):1019-1029

中国成年人生活方式和心血管代谢因素与甲基化年龄加速的相关性分析

Association of lifestyle and cardiometabolic risk factors with epigenetic age acceleration in adults in China

Received:October 20, 2021

DOI：10.3760/cma.j.cn112338-20211020-00806

KeyWord: 甲基化年龄加速生活方式心血管代谢性因素

English Key Word: Epigenetic age acceleration Lifestyle Cardiometabolic risk factors

FundProject:国家自然科学基金(81941018);国家重点研发计划(2016YFC0900500);中国香港Kadoorie Charitable基金;英国Wellcome Trust(212946/Z/18/Z,202922/Z/16/Z,104085/Z/14/Z,088158/Z/09/Z)

Author Name	Affiliation	E-mail
Chen Lu	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Si Jiahui	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Sun Dianjianyi	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Yu Canqing	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
Guo Yu	Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
Pei Pei	Chinese Academy of Medical Sciences, Beijing 100730, China
Chen Junshi	China National Center for Food Safety Risk Assessment, Beijing 100022, China
Chen Zhengming	Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
Lyu Jun	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China	lvjun@bjmu.edu.cn
Li Liming	Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China

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Abstract:

目的比较分析5种甲基化年龄加速指标与生活方式和心血管代谢因素间的相关性。方法基于中国慢性病前瞻性研究中有基线外周血全基因组甲基化检测数据的研究对象980人，计算Horvath时钟、Hannum时钟、DNAm PhenoAge、GrimAge和Li时钟5种甲基化年龄。根据甲基化年龄对实足年龄回归的残差值计算甲基化年龄加速。研究的生活方式因素包括吸烟、饮酒、饮食习惯、体力活动、经BMI和腰围联合定义的体型。心血管代谢因素包括血压、血糖和TC。利用一般线性模型分析生活方式和心血管代谢因素与各甲基化年龄加速指标的相关性［β值（95%CI）］。结果 GrimAge加速指标与吸烟、饮酒、体力活动水平及BMI存在关联。与不吸烟、不饮酒或BMI为18.5~23.9 kg/m²者相比，吸烟者（每天吸烟1~14、15~24、≥25支者对应的β值依次为0.71（95%CI：0.57~0.86）、0.88（95%CI：0.73~1.03）、0.99（95%CI：0.81~1.18）、重度饮酒者［每日纯乙醇量≥60 g：0.33（95%CI：0.11~0.55）］、BMI<18.5 kg/m²者［0.23（95%CI：0.03~0.43）］表现为加速衰老；与体力活动水平低者相比，中、较高、高体力活动者表现为减速衰老［β值依次为-0.14（95%CI：-0.27~-0.00）、-0.12（95%CI：-0.26~0.02）、-0.13（95%CI：-0.26~0.01）］。随着健康生活方式数量的增加，GrimAge加速指标呈现下降趋势（P<0.001）；与具有0~1个健康生活方式者相比，具有2、3、或4~5个健康生活方式者的β值依次为-0.30（95%CI：-0.47~-0.12）、-0.47（95%CI：-0.65~-0.30）、-0.72 （95%CI：-0.90~-0.53）。其他4个指标与多数生活方式因素不存在有统计学显著性的关联。5种甲基化年龄加速指标与血压、血糖和TC均不存在关联。结论生活方式不健康者表现出表观遗传年龄的加速，即DNA甲基化预测年龄老于实足年龄。

English Abstract:

Objective To explore the association of lifestyle and cardiometabolic risk factors with five epigenetic age acceleration (AA) indices. Methods This study included 980 participants of China Kadoorie Biobank, for whom genome-wide DNA methylation of peripheral blood cells had been detected in baseline survey. Five indices of DNA methylation age (DNAm age) were calculated, i.e. Horvath clock, Hannum clock, DNAm PhenoAge, GrimAge and Li clock. Epigenetic AA was defined as the residual of regressing DNAm age on chronological age. Lifestyle factors studied included smoking status, alcohol consumption, eating habits, physical activity level and body shape defined by a combination of BMI and waist circumference. Cardiometabolic risk factors included blood pressure, blood glucose level and total cholesterol level. Linear regression model was used to analyze the association of lifestyle and cardiometabolic risk factors with AA (β). Results GrimAge_AA was associated with smoking status, alcohol consumption, physical activity level and BMI. Compared with non-smokers, non-drinkers, or participants with BMI of 18.5- 23.9 kg/m², the smokers who smoked 1-14 cigarettes/day (β=0.71, 95%CI:0.57-0.86), 15-24 cigarettes/day (β=0.88, 95%CI:0.73-1.03), and ≥ 25 cigarettes/day (β=0.99, 95%CI:0.81-1.18), respectively, heavy drinkers with daily pure alcohol consumption ≥ 60 g (β=0.33, 95%CI:0.11-0.55) and participants with BMI<18.5 kg/m² (β=0.23, 95%CI:0.03-0.43) showed accelerated aging. Compared with those in the lowest quintile of physical activity level, participants in the top three quintile of physical activity level showed decelerated aging (β=-0.13, 95%CI:-0.26-0.01, β=-0.12, 95%CI:-0.26-0.02, and β=-0.14, 95%CI:-0.27- -0.00, respectively). GrimAge_AA decreased with the increase of the number of healthy lifestyle factors (P<0.001). Compared with the participants with 0 to 1 healthy lifestyle factor, the β of those with 2, 3, or 4 to 5 healthy lifestyle factors were -0.30 (95%CI:-0.47- -0.12), -0.47 (95%CI:-0.65- -0.30) and -0.72 (95%CI:-0.90- -0.53), respectively. The other four indices were not statistically significantly associated with most lifestyle factors. None of the five indices of AA was associated with blood pressure, blood glucose level or total cholesterol level. Conclusion People with unhealthy lifestyle showed accelerated epigenetic aging, that is, the predicted DNAm age is older than their own chronological age.

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