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Erschienen in: Diabetologia 11/2016

11.08.2016 | Article

Metabolic signatures and risk of type 2 diabetes in a Chinese population: an untargeted metabolomics study using both LC-MS and GC-MS

verfasst von: Yonghai Lu, Yeli Wang, Choon-Nam Ong, Tavintharan Subramaniam, Hyung Won Choi, Jian-Min Yuan, Woon-Puay Koh, An Pan

Erschienen in: Diabetologia | Ausgabe 11/2016

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Abstract

Aims/hypothesis

Metabolomics has provided new insight into diabetes risk assessment. In this study we characterised the human serum metabolic profiles of participants in the Singapore Chinese Health Study cohort to identify metabolic signatures associated with an increased risk of type 2 diabetes.

Methods

In this nested case–control study, baseline serum metabolite profiles were measured using LC-MS and GC-MS during a 6-year follow-up of 197 individuals with type 2 diabetes but without a history of cardiovascular disease or cancer before diabetes diagnosis, and 197 healthy controls matched by age, sex and date of blood collection.

Results

A total of 51 differential metabolites were identified between cases and controls. Of these, 35 were significantly associated with diabetes risk in the multivariate analysis after false discovery rate adjustment, such as increased branched-chain amino acids (leucine, isoleucine and valine), non-esterified fatty acids (palmitic acid, stearic acid, oleic acid and linoleic acid) and lysophosphatidylinositol (LPI) species (16:1, 18:1, 18:2, 20:3, 20:4 and 22:6). A combination of six metabolites including proline, glycerol, aminomalonic acid, LPI (16:1), 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid and urea showed the potential to predict type 2 diabetes in at-risk individuals with high baseline HbA1c levels (≥6.5% [47.5 mmol/mol]) with an AUC of 0.935. Combined lysophosphatidylglycerol (LPG) (12:0) and LPI (16:1) also showed the potential to predict type 2 diabetes in individuals with normal baseline HbA1c levels (<6.5% [47.5 mmol/mol]; AUC = 0.781).

Conclusions/interpretation

Our findings show that branched-chain amino acids and NEFA are potent predictors of diabetes development in Chinese adults. Our results also indicate the potential of lysophospholipids for predicting diabetes.
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Metadaten
Titel
Metabolic signatures and risk of type 2 diabetes in a Chinese population: an untargeted metabolomics study using both LC-MS and GC-MS
verfasst von
Yonghai Lu
Yeli Wang
Choon-Nam Ong
Tavintharan Subramaniam
Hyung Won Choi
Jian-Min Yuan
Woon-Puay Koh
An Pan
Publikationsdatum
11.08.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Diabetologia / Ausgabe 11/2016
Print ISSN: 0012-186X
Elektronische ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-016-4069-2

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