2020-06-02T06:25:35Z
2020-06-02T06:25:35Z
2019-04-01
2020-06-02T06:25:35Z
Aim. - To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. Methods. - A metabolomics analysis using the 1 H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. Results. - A total of 33 metabolites were significantly different (P < 0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. Conclusion. - The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine
Article
Accepted version
English
Dietoteràpia; Metabolisme; Marcadors bioquímics; Diabetis no-insulinodependent; Medicina preventiva; Metabolòmica; Factors de risc en les malalties; Diet therapy; Metabolism; Biochemical markers; Non-insulin-dependent diabetes; Preventive medicine; Metabolomics; Risk factors in diseases
Elsevier Masson SAS
Versió postprint del document publicat a: https://doi.org/10.1016/j.diabet.2018.02.006
Diabetes & Metabolism, 2019, vol. 45, num. 2, p. 167-174
https://doi.org/10.1016/j.diabet.2018.02.006
(c) Elsevier Masson SAS, 2019