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IntroductionWe evaluated whether concentrations of serum acylcarnitines and amino acids are associated with risk of type 2 diabetes and can improve predictive diabetes models in an Asian population.Research design and methodsWe used data from 3313 male and female participants from the Singapore Prospective Study Program cohort who were diabetes-free at baseline. The average age at baseline was 48.0 years (SD: 11.9 years), and participants were of Chinese, Malay, and Indian ethnicity. Diabetes cases were identified through self-reported physician diagnosis, fasting glucose and glycated hemoglobin concentrations, and linkage to national disease registries. We measured fasting serum concentrations of 45 acylcarnitines and 14 amino acids. The association between metabolites and incident diabetes was modeled using Cox proportional hazards regression with adjustment for age, sex, ethnicity, height, and parental history of diabetes, and correction for multiple testing. Metabolites were added to the Atherosclerosis Risk in Communities (ARIC) predictive diabetes risk model to assess whether they could increase the area under the receiver operating characteristic curve (AUC).ResultsParticipants were followed up for an average of 8.4 years (SD: 2.1 years), during which time 314 developed diabetes. Branched-chain amino acids (HR: 1.477 per SD; 95% CI 1.325 to 1.647) and the alanine to glycine ratio (HR: 1.572; 95% CI 1.426 to 1.733) were most strongly associated with diabetes risk. Additionally, the acylcarnitines C4 and C16-OH, and the amino acids alanine, combined glutamate/glutamine, ornithine, phenylalanine, proline, and tyrosine were significantly associated with higher diabetes risk, and the acylcarnitine C8-DC and amino acids glycine and serine with lower risk. Adding selected metabolites to the ARIC model resulted in a significant increase in AUC from 0.836 to 0.846.ConclusionsWe identified acylcarnitines and amino acids associated with risk of type 2 diabetes in an Asian population. A subset of these modestly improved the prediction of diabetes when added to an established diabetes risk model.

Scope Coffee and tea are among the most popular beverages in the world. However, the association between habitual coffee, green tea, and black tea consumption with metabolomics profiles in Asian populations remain largely unknown. Methods and Results 158 metabolites (14 amino acids, 45 acylcarnitines, and 99 sphingolipids) in the blood plasma of participants are measured from the population‐based Singapore Prospective Study Program cohort using mass spectrometry (MS). Linear regression models are used to obtain the estimates for the association between coffee and tea consumption with metabolite levels, adjusted for potential confounders and false discovery rate (FDR). Coffee consumption is significantly associated with higher levels of 63 sphingolipids (29 sphingomyelins, 32 ceramides, a sphingosine‐1‐phosphate, and a sphingosine) and lower levels of 13 acylcarnitines and alanine. Black tea consumption is significantly associated with higher levels of eight sphingolipids, and lower levels of an amino acid, whereas green tea is significantly inversely associated with four metabolites (C8:1‐OH acylcarnitine, ganglioside GM3 d18:1/16:0, sphingomyelins d18:2/18:0 and d18:1/14:0). Conclusions Coffee, black tea, and green tea consumption are associated with plasma levels of certain classes of sphingolipids and acylcarnitines in an Asian population, particularly sphingomyelins, which may mediate the health benefits of these beverages.