Serum Metabolomic Profiling of Incident Type 2 Diabetes Mellitus in the Multi-ethnic Study of Atherosclerosis and Rotterdam Study

被引:0
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作者
Jiang, Xuanwei [1 ]
Zhu, Fang [2 ]
Graca, Goncalo [3 ]
Du, Xihao [1 ]
Ran, Jinjun [1 ]
Ahmadizar, Fariba [2 ,4 ]
Wood, Alexis C. [5 ]
Zhou, Yanqiu [1 ]
Scholtens, Denise M. [6 ]
Farzaneh, Ali [2 ]
Ikram, M. Arfan [2 ]
Kuang, Alan [6 ]
le Roux, Carel W. [7 ]
Gadgil, Meghana D. [8 ]
Cornelis, Marilyn C. [6 ]
Taylor, Kent D. [9 ]
Guo, Xiuqing [9 ]
Ghanbari, Mohsen [2 ]
Rasmussen-Torvik, Laura J. [6 ]
Tracy, Russell P. [10 ]
Bertoni, Alain G. [11 ]
Rotter, Jerome, I [9 ]
Herrington, David M. [12 ]
Greenland, Philip [6 ]
Kavousi, Maryam [2 ]
Zhong, Victor W. [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Med, Sch Publ Hlth, Dept Epidemiol & Biostat, Shanghai 200025, Shanghai, Peoples R China
[2] Univ Med Ctr Rotterdam, Erasmus MC, Dept Epidemiol, Off Na 2714 POB 2040, NL-3000 CA Rotterdam, Netherlands
[3] Imperial Coll London, Dept Metab Digest & Reprod, Sect Bioinformat, London W12 0NN, England
[4] Univ Med Ctr Utrecht, Julius Global Hlth, Data Sci & Biostat Dept, NL-3584 CG Utrecht, Netherlands
[5] USDA ARS, Childrens Nutr Res Ctr, Baylor Coll Med, Houston, TX 77030 USA
[6] Northwestern Univ, Feinberg Sch Med, Dept Prevent Med, 680 N Lake Shore Dr Suite 1400, Chicago, IL 60611 USA
[7] Univ Coll Dublin, Diabet Complicat Res Ctr, Dublin, Ireland
[8] Univ Calif San Francisco, Dept Med, Div Gen Internal Med, San Francisco, CA 94143 USA
[9] Harbor UCLA Med Ctr, Lundquist Inst Biomed Innovat, Inst Translat Genom & Populat Sci, Dept Pediat, Torrance, CA 90502 USA
[10] Univ Vermont, Coll Med, Dept Pathol & Lab Med, Burlington, VT 05401 USA
[11] Wake Forest Sch Med, Dept Epidemiol & Prevent, Div Publ Hlth Sci, Winston Salem, NC 27157 USA
[12] Wake Forest Sch Med, Sect Cardiovasc Med, Winston Salem, NC 27157 USA
基金
中国国家自然科学基金; 美国国家卫生研究院; 国家重点研发计划;
关键词
metabolomics; type 2 diabetes mellitus; prediction; CHAIN AMINO-ACIDS; MENDELIAN RANDOMIZATION; RISK; INSTRUMENTS; SIGNATURE; HEALTH;
D O I
10.1210/clinem/dgae812
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective This study aimed to investigate serum metabolomic biomarkers associated with incident type 2 diabetes mellitus (T2DM) and evaluate their performance in improving T2DM risk prediction. Methods Untargeted proton nuclear magnetic resonance (1H NMR) spectroscopy-based metabolomics analyses were conducted in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 3460; discovery cohort) and The Rotterdam Study (RS; n = 1556; replication cohort). Multivariable cause-specific hazards models were used to analyze the associations between 23 571 serum metabolomic spectral variables and incident T2DM. Replicated metabolites required an false discovery rate-adjusted P < .01 in MESA, P < .05 in RS, and consistent direction of association. Pathway and network analyses were conducted to elucidate biological mechanisms underlying T2DM development. The utility of the replicated metabolites in improving T2DM risk prediction was assessed based on the Framingham Diabetes Risk Score. A 2-sample Mendelian randomization was conducted to assess causal associations. Results Nineteen metabolites were significantly associated with incident T2DM. Pathway analyses revealed disturbances in aminoacyl-tRNA biosynthesis, metabolism of branched-chain amino acids (BCAAs), glycolysis/gluconeogenesis, and glycerolipid metabolism. Network analyses identified interactions with upstream regulators including p38 mitogen-activated protein kinases, c-Jun N-terminal kinase, and mammalian target of rapamycin signaling pathways. Adding replicated metabolites to the Framingham Diabetes Risk Score showed modest to moderate improvements in prediction performance in MESA and RS, with Delta C-statistic of 0.05 [95% confidence interval (CI), 0.04-0.07] in MESA and 0.03 (95% CI, 0.01-0.05) in RS. Genetically increased BCAAs and mannose were associated with T2DM. Conclusion H-1 NMR measured metabolites involved in aminoacyl-tRNA biosynthesis, BCAA metabolism, glycolysis/gluconeogenesis, and glycerolipid metabolism were significantly associated with incident T2DM and provided modest to moderate predictive utility beyond traditional risk factors.
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页数:11
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