Adiposity, metabolomic biomarkers, and risk of nonalcoholic fatty liver disease: a case-cohort study

被引:16
作者
Pang, Yuanjie [1 ]
Kartsonaki, Christiana [2 ,3 ,4 ]
Lv, Jun [1 ,5 ]
Millwood, Iona Y. [2 ,3 ,4 ]
Fairhurst-Hunter, Zammy [2 ,3 ]
Turnbull, Iain [2 ,3 ]
Bragg, Fiona [2 ,3 ,4 ]
Hill, Michael R. [2 ,3 ]
Yu, Canqing [1 ,5 ]
Guo, Yu [6 ]
Chen, Yiping [2 ,3 ,4 ]
Yang, Ling [2 ,3 ,4 ]
Clarke, Robert [2 ,3 ]
Walters, Robin G. [2 ,3 ,4 ]
Wu, Ming [7 ]
Chen, Junshi [8 ]
Li, Liming [1 ,5 ]
Chen, Zhengming [2 ,3 ,4 ]
Holmes, Michael, V [2 ,3 ,4 ,9 ]
机构
[1] Peking Univ, Sch Publ Hlth, Dept Epidemiol & Biostat, Beijing, Peoples R China
[2] Univ Oxford, Nuffield Dept Populat Hlth, Clin Trial Serv Unit, Oxford, England
[3] Univ Oxford, Nuffield Dept Populat Hlth, Epidemiol Studies Unit CTSU, Oxford, England
[4] Univ Oxford, Populat Hlth Res Unit, Nuffield Dept Populat Hlth, Med Res Council,MRC PHRU, Oxford, England
[5] Peking Univ, Peking Univ Ctr Publ Hlth & Epidem Preparedness &, Beijing, Peoples R China
[6] Chinese Acad Med Sci, Beijing, Peoples R China
[7] Jiangsu Ctr Dis Control & Prevent, Nanjing, Peoples R China
[8] Natl Ctr Food Safety Risk Assessment, Beijing, Peoples R China
[9] Natl Inst Hlth Res Oxford Biomed Res Ctr, Oxford Univ Hosp, Oxford, England
基金
中国国家自然科学基金; 国家重点研发计划; 英国惠康基金; 中国博士后科学基金;
关键词
adiposity; nonalcoholic fatty liver disease; metabolomics; Mendelian randomization; Chinese; CHAIN AMINO-ACIDS; BODY-MASS INDEX; INSULIN-RESISTANCE; SCORING MODEL; OBESITY; PREDICTION; NAFLD; EPIDEMIOLOGY; ASSOCIATION; VALIDATION;
D O I
10.1093/ajcn/nqab392
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Background: Globally, the burden of obesity and associated nonalcoholic fatty liver disease (NAFLD) are rising, but little is known about the role that circulating metabolomic biomarkers play in mediating their association. Objectives: We aimed to examine the observational and genetic associations of adiposity with metabolomic biomarkers and the observational associations of metabolomic biomarkers with incident NAFLD. Methods: A case-subcohort study within the prospective China Kadoorie Biobank included 176 NAFLD cases and 180 subcohort individuals and measured 1208 metabolites in stored baseline plasma using a Metabolon assay. In the subcohort the observational and genetic associations of BMI with biomarkers were assessed using linear regression, with adjustment for multiple testing. Cox regression was used to estimate adjusted HRs for NAFLD associated with biomarkers. Results: In observational analyses, BMI (kg/m(2); mean: 23.9 in the subcohort) was associated with 199 metabolites at a 5% false discovery rate. The effects of genetically elevated BMI with specific metabolites were directionally consistent with the observational associations. Overall, 35 metabolites were associated with NAFLD risk, of which 15 were also associated with BMI, including glutamate (HR per 1-SD higher metabolite: 1.95; 95% CI: 1.48, 2.56), cysteine-glutathione disulfide (0.44; 0.31. 0.62), diaclyglycerol (C32:1) (1.71; 1.24, 2.35), behenoyl dihydrosphingomyelin (C40:0) (1.92; 1.42, 2.59), butyrylcarnitine (C4) (1.91; 1.38, 2.35). 2-hydroxybehenate (1.81; 1.34, 2.45), and 4-cholesten-3-one (1.79; 1.27, 2.54). The discriminatory performance of known risk factors was increased when 28 metabolites were also considered simultaneously in the model (weighted C-statistic: 0.84 to 0.90: P < 0.001). Conclusions: Among relatively lean Chinese adults, a range of metabolomic biomarkers arc associated with NAFLD risk and these biomarkers may lie on the pathway between adiposity and NAFLD.
引用
收藏
页码:799 / 810
页数:12
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