Objectively measured physical activity and plasma metabolomics in the Shanghai Physical Activity Study

被引:55
|
作者
Xiao, Qian [1 ]
Moore, Steven C. [1 ]
Keadle, Sarah K. [1 ]
Xiang, Yong-Bing [2 ]
Zheng, Wei [3 ,4 ]
Peters, Tricia M. [5 ]
Leitzmann, Michael F. [6 ]
Ji, Bu-Tian [7 ]
Sampson, Joshua N. [8 ]
Shu, Xiao-Ou [3 ,4 ]
Matthews, Charles E. [1 ]
机构
[1] NCI, Nutr Epidemiol Branch, Div Canc Epidemiol & Genet, Rockville, MD USA
[2] Shanghai Canc Inst, Dept Epidemiol, Shanghai, Peoples R China
[3] Vanderbilt Univ, Sch Med, Vanderbilt Epidemiol Ctr, Nashville, TN 37212 USA
[4] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Canc Ctr, Nashville, TN 37212 USA
[5] McGill Univ, Ctr Hlth, Dept Internal Med, Montreal, PQ, Canada
[6] Univ Regensburg, Dept Epidemiol & Prevent Med, Regensburg, Germany
[7] NCI, Occupat & Environm Epidemiol Branch, Rockville, MD USA
[8] NCI, Biostat Branch, Div Canc Epidemiol & Genet, Rockville, MD USA
基金
美国国家卫生研究院;
关键词
sleep timing; chronotype; sleep duration; metabolomics; GAMMA-GLUTAMYL-TRANSFERASE; CHAIN AMINO-ACIDS; POTENTIAL ROLE; UNITED-STATES; RISK; METAANALYSIS; TIME; METABOLISM; HEALTH; MASS;
D O I
10.1093/ije/dyw033
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Physical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities. Methods: In a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity). Results: We identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns. Conclusions: Overall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity.
引用
收藏
页码:1433 / 1444
页数:12
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