Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts

Abstract

Objective: Advances in metabolomics now allow high-throughput biomarker profiling of large population studies. We aimed to identify circulating metabolic biomarkers predictive of type 2 diabetes in young adults.Methods: Nuclear magnetic resonance metabolomics was used to quantify 229 metabolic measures in 11,896 individuals from four Finnish cohorts (mean age 33 years, range 24-45). Associations between baseline metabolites and risk of type 2 diabetes onset during 8-15 years of follow-up (392 incident cases) were assessed by logistic regression adjusted for sex, age, body mass index, and fasting glucose.Results: Out of 229 metabolic measures, 113 were associated with incident diabetes in metaanalysis of the four cohorts (P<0.0009; odds ratios per 1-SD: 0.59-1.50). Among the strongest predictors of diabetes risk were branched-chained and aromatic amino acids (odds ratios 1.31-1.33), triglyceride fractions within the largest very-low-density lipoprotein particles (VLDL; odds ratios 1.33-1.50)), as well as linoleic omega-6 fatty acids (odds ratio 0.75) and free cholesterol in large high-density lipoprotein particles (HDL; odds ratio 0.59). A biomarker score comprised of phenylalanine, free cholesterol in large HDL, and the ratio of cholesteryl esters to total lipids in large VLDL was predictive of the risk for future diabetes in an independent validation cohort (odds ratio 10.1 [95% confidence intervals 4.2-24.1] comparing individuals in upper vs lower fifth of biomarker score). Adjustment for routine lipids and insulin attenuated the odds ratio to 5.8 [2.2-15.1]. Conclusions:Metabolic aberrations across multiple molecular pathways are predictive of the longterm risk of type 2 diabetes in young adults. Comprehensive metabolic profiling may potentially help targeting preventive interventions for young asymptomatic individuals at increased risk for type 2 diabetes.

Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug–metabolite atlas

“…1), our analysis shows that the direction and significance of drug-metabolite associations are not always the same among different metabolites in the same cluster, and this is especially true for VLDL and HDL particles. This is consistent with previous studies on the role of lipid particle profiles and diseases 4,6,[31][32][33][34]44,45 , and is also true for amino acids. In Rotterdam Study, histon clusters strongly with leucine, valine and isoleucine (in correlation tests, P = 3.3 × 10 −23 ).…”

“…The aim of the present study was to develop a comprehensive atlas of the associations between a wide range of commonly prescribed drugs (Supplementary Table 1) and 150 plasma-based metabolites as measured by the proton nuclear magnetic resonance ( 1 H-NMR) platform of Nightingale Health (Supplementary Table 2). This platform allows rapid and cost-effective characterization of metabolites in human blood, and it has been successfully used globally to discover and validate disease-metabolite associations 29 including diabetes 30 , dementia 6 , cardiovascular diseases 31,32 , migraine 33 , Graves' disease 34 and mortality 35,36 . Nightingale Health is now being validated for use in clinical care, which makes it timely to develop a pharmacological metabolomics atlas for this platform that can be used in both research and clinical care.…”

Acarbose Protects From Central and Peripheral Metabolic Imbalance Induced by Benzene Exposure

“…Diabetes is a major public health problem that is approaching epidemic proportions globally, and pollutants in the air or at home have been associated with diabetes [54]. Benzene exposure through the human lifespan is inevitable [6][7][8][9][10]. Drinking contaminated water or eating food that has been exposed to contaminated water, smoking cigarettes, or breathing secondhand cigarette smoke, exposure to e-cigarettes vaping, use of paint or detergent products, vehicle exhaust or gasoline, it's all part of the daily routine [55].…”

“…Benzene concentrations vary depending on geographic location [4,5], duration or route of exposure, and individual susceptibility factors such as age, gender or lifestyle. Various sources of benzene exposure include drinking contaminated water or food, smoking cigarettes, breathing secondhand cigarette smoke, vehicle exhaust or petroleum fuels, vaping e-cigarettes, using paint or detergent products [6][7][8][9][10][11][12][13][14]. While values of ambient benzene air concentrations in the U.S. have typically been <1 ppm (parts per million), significantly higher levels can be experienced as a result of various environmental factors [15] [16].…”

Urinary metabolite profiling identifies biomarkers for risk of progression of diabetic nephropathy in 2,670 individuals with type 1 diabetes

“…21 These amino acids also represent the most consistent biomarkers identified by blood metabolomics to be predictive of future type 2 diabetes risk. [22][23][24] In physiological studies and human genetics, there is even evidence that links them causally to insulin resistance. [25][26][27] Furthermore, insulin resistance has been observed in individuals with type 1 diabetes and linked to the increasing prevalence of obesity in type 1 diabetes.…”