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Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts – published online 04/10/2019

Fig from Ahola-Olli paper

Ari V. Ahola-Olli, Linda Mustelin, Maria Kalimeri, Johannes Kettunen, Jari Jokelainen, Juha Auvinen, Katri Puukka, Aki S. Havulinna, Terho Lehtimäki, Mika Kähönen, Markus Juonala, Sirkka Keinänen-Kiukaanniemi, Veikko Salomaa, Markus Perola, Marjo-Riitta Järvelin, Mika Ala-Korpela, Olli Raitakari, Peter Würtz

Increased risk for type 2 diabetes is consistently associated with widespread metabolic aberrations in young adults from multiple cohorts with a mean age of 31–36 years at baseline. Among the strongest predictors of incident type 2 diabetes are circulating branched-chain amino acids, VLDL-particle measures and enrichment of triacylglycerol in all lipoprotein subclasses. Previous animal studies and Mendelian randomisation studies performed in humans have suggested causal relationships between increased concentrations of branched-chain amino acids and type 2 diabetes. In this issue, Ahola-Olli et al ( used NMR metabolomics to quantify 229 circulating metabolic measures in individuals from four Finnish observational cohorts (n=11,896; baseline age 24–45 years) and tested associations with risk of developing diabetes, fasting glucose, 2 h glucose and HOMA-IR at follow-up (range 8–15 years). The authors explain that their results extend previously detected epidemiological associations (in middle-aged and older individuals) to young adults and demonstrate that branched-chain amino acids can predict the development of type 2 diabetes up to 15 years prior to disease onset. By summarising the information from multiple metabolic measures, the authors were able to derive and validate a multi-metabolite score identifying a subgroup of patients with a greatly increased risk for type 2 diabetes after adjusting for BMI and fasting glucose (OR 10.1 for individuals in upper vs lower fifth of the multi-metabolite score). They conclude that comprehensive metabolic profiling may eventually help target interventions for young people at increased risk for developing type 2 diabetes.

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