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Objective: Type 2 diabetes (T2D) can be prevented, but the risk is heterogeneous even among high-risk individuals. We aimed to create a metabolite T2D risk model and evaluate its utility compared to a genetic risk score (GRS) and traditional clinical factors in 1,635 participants with available genomics and metabolomics. Methods: Predictors were picked using elastic net from 3,145 mass spectrometry measured metabolites in baseline fasting plasma. Predictive performance after 3.2 years follow-up was assessed using AUC and IDI of Cox models that included the metabolites, the 120-SNP GRS, and clinical factors. Results: The composite monosaccharide measurement of glucose/fructose/galactose and a 50 carbon:1 double bond triacylglycerol (TG 50:1) were selected and minimally increased the AUC beyond the clinical model (AUC=0.71 vs AUC=0.69, Fig1A). There was no change with the addition of the GRS (AUC=0.69). When added to FPG, TG 50:1 provided the same increase in the integrated discrimination index (IDI) as with clinical triglycerides (Fig1B), but glucose/fructose/galactose provided a significant increase in IDI beyond clinical FPG. Conclusion: Metabolites minimally improve DM prediction beyond clinical risk factors in a high-risk adult population. A glucose/fructose/galactose composite metabolite significantly improves IDI. Disclosure Z. Chen: None. R. Shu: None. M. Tripputi: None. X. Shi: None. J. Avila: None. W.C. Knowler: None. S.E. Kahn: Advisory Panel; AltPep, Boehringer-Ingelheim, Eli Lilly and Company, Intarcia Therapeutics, Inc., Merck Novo Nordisk. Other Relationship; Novo Nordisk, AstraZeneca. R.E. Gerszten: None. M. Temprosa: None. D. Research Group: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (UDK048489, UDK048339, UDK048377, UDK048349, UDK048381, UDK048468, UDK048434, UDK048485, UDK048375, UDK048514, UDK048437, UDK048413, UDK048411, UDK048406, UDK048380, UDK048397, UDK048412, UDK048404, UDK048387, UDK048407, UDK048443, UDK048400)
CHEN et al. (Fri,) studied this question.