Xuanwei Jiang, Fang Zhu, Gonçalo Graça, Xihao Du, Jinjun Ran, Fariba Ahmadizar, Alexis C Wood, Yanqiu Zhou, Denise M Scholtens, Ali Farzaneh, M Arfan Ikram, Alan Kuang, Carel Le Roux, Meghana D Gadgil, Marilyn C Cornelis, Kent D Taylor, Xiuqing Guo, Mohsen Ghanbari, Laura J Rasmussen-Torvik, Russell P Tracy, Alain G Bertoni, Jerome I Rotter, David M Herrington, Philip Greenland, Maryam Kavousi, Victor W Zhong
{"title":"多种族动脉粥样硬化研究和鹿特丹研究中 2 型糖尿病发病者的血清代谢组学分析。","authors":"Xuanwei Jiang, Fang Zhu, Gonçalo Graça, Xihao Du, Jinjun Ran, Fariba Ahmadizar, Alexis C Wood, Yanqiu Zhou, Denise M Scholtens, Ali Farzaneh, M Arfan Ikram, Alan Kuang, Carel Le Roux, Meghana D Gadgil, Marilyn C Cornelis, Kent D Taylor, Xiuqing Guo, Mohsen Ghanbari, Laura J Rasmussen-Torvik, Russell P Tracy, Alain G Bertoni, Jerome I Rotter, David M Herrington, Philip Greenland, Maryam Kavousi, Victor W Zhong","doi":"10.1210/clinem/dgae812","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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 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 FDR-adjusted P<0.01 in MESA, P<0.05 in RS, and consistent direction of association. Pathway and network analyses were conducted to elucidate biological mechanisms underlying T2DM development. 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.</p><p><strong>Results: </strong>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 MAPK, c-JNK, and mTOR signaling pathways. Adding replicated metabolites to the Framingham Diabetes Risk Score showed modest to moderate improvements in prediction performance in MESA and RS, with Δ c-statistic of 0.05 (95% 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.</p><p><strong>Conclusions: </strong>1H 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.</p>","PeriodicalId":50238,"journal":{"name":"Journal of Clinical Endocrinology & Metabolism","volume":" ","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Serum metabolomic profiling of incident type 2 diabetes mellitus in the Multi-Ethnic Study of Atherosclerosis and Rotterdam Study.\",\"authors\":\"Xuanwei Jiang, Fang Zhu, Gonçalo Graça, Xihao Du, Jinjun Ran, Fariba Ahmadizar, Alexis C Wood, Yanqiu Zhou, Denise M Scholtens, Ali Farzaneh, M Arfan Ikram, Alan Kuang, Carel Le Roux, Meghana D Gadgil, Marilyn C Cornelis, Kent D Taylor, Xiuqing Guo, Mohsen Ghanbari, Laura J Rasmussen-Torvik, Russell P Tracy, Alain G Bertoni, Jerome I Rotter, David M Herrington, Philip Greenland, Maryam Kavousi, Victor W Zhong\",\"doi\":\"10.1210/clinem/dgae812\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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 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 FDR-adjusted P<0.01 in MESA, P<0.05 in RS, and consistent direction of association. Pathway and network analyses were conducted to elucidate biological mechanisms underlying T2DM development. 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.</p><p><strong>Results: </strong>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 MAPK, c-JNK, and mTOR signaling pathways. Adding replicated metabolites to the Framingham Diabetes Risk Score showed modest to moderate improvements in prediction performance in MESA and RS, with Δ c-statistic of 0.05 (95% CI, 0.04-0.07) in MESA and 0.03 (95% CI, 0.01-0.05) in RS. 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Serum metabolomic profiling of incident type 2 diabetes mellitus in the Multi-Ethnic Study of Atherosclerosis and Rotterdam Study.
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 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 FDR-adjusted P<0.01 in MESA, P<0.05 in RS, and consistent direction of association. Pathway and network analyses were conducted to elucidate biological mechanisms underlying T2DM development. 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 MAPK, c-JNK, and mTOR signaling pathways. Adding replicated metabolites to the Framingham Diabetes Risk Score showed modest to moderate improvements in prediction performance in MESA and RS, with Δ c-statistic of 0.05 (95% 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.
Conclusions: 1H 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.
期刊介绍：
The Journal of Clinical Endocrinology & Metabolism is the world"s leading peer-reviewed journal for endocrine clinical research and cutting edge clinical practice reviews. Each issue provides the latest in-depth coverage of new developments enhancing our understanding, diagnosis and treatment of endocrine and metabolic disorders. Regular features of special interest to endocrine consultants include clinical trials, clinical reviews, clinical practice guidelines, case seminars, and controversies in clinical endocrinology, as well as original reports of the most important advances in patient-oriented endocrine and metabolic research. According to the latest Thomson Reuters Journal Citation Report, JCE&M articles were cited 64,185 times in 2008.
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