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Metabolic profiling detection was performed by high-performance liquid chromatography\u2012mass spectrometry (HPLC-MS) by an untargeted strategy and 20 single nucleotide polymorphisms (SNPs) associated with T2D were genotyped using the Iplex Sequenom MassARRAY platform. Machine learning methods were used to identify metabolites associated with future T2D risk.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We found that abnormal levels of 5 metabolites were associated with increased risk of future T2D: riboflavin, cnidioside A, 2-methoxy-5-(1H-1, 2, 4-triazol-5-yl)- 4-(trifluoromethyl) pyridine, 7-methylxanthine, and mestranol. The genetic risk score (GRS) based on 20 SNPs was significantly associated with T2D risk (OR\u2005=\u20051.35; 95% CI, 1.08-1.70 per SD). The area under the receiver operating characteristic curve (AUC) was greater for the model containing metabolites, GRS, and clinical traits than for the model containing clinical traits only (0.960 vs 0.798, P\u2005=\u20057.91\u2005\u00d7\u200510-16).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>In individuals with normal fasting glucose levels, abnormal levels of 5 metabolites were associated with future T2D. The combination of newly discovered metabolic markers and genetic markers could improve the prediction of incident T2D.<\/jats:p><\/jats:sec>","DOI":"10.1210\/clinem\/dgac487","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T18:17:26Z","timestamp":1660760246000},"page":"3120-3127","source":"Crossref","is-referenced-by-count":11,"title":["Metabolic and Genetic Markers Improve Prediction of Incident Type 2 Diabetes: A Nested Case-Control Study in Chinese"],"prefix":"10.1210","volume":"107","author":[{"given":"Jia","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Health Promotion & Chronic Non-Communicable Disease Control, Wuxi Center for Disease Control and Prevention (The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University ), Wuxi 214023, Jiangsu , 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