Aims: Fasting plasma glucose, oral glucose tolerance test, and glycated hemoglobin are diagnostic markers for type 2 diabetes mellitus (T2DM). However, it is necessary to detect physiological changes in T2DM rapidly and stratify diabetic stage using other biomarkers. We performed a systematic review and meta-analysis to contribute to the development of objective and sensitive diagnostic indicators by integrating metabolite biomarkers derived from large-scale cohort studies.
Methods: We searched for metabolomics studies of T2DM cohort in PubMed, Scopus, and Web of Science for studies published within the last 10 years from January 2008 to February 2017. The concentrations of metabolites and odds ratios (ORs) were integrated and risk ratio (RR) values were estimated to distinguish subjects with T2DM and normal participants.
Results: Fourteen cohort studies were investigated in this meta-analysis. There were 4592 patients in the case group and 11,492 participants in the control group. We noted a 1.89-, 1.63-, and 1.87-fold higher risk of T2DM associated with leucine (RR 1.89 [95% CI 1.57-2.29]), alanine (RR 1.63 [95% CI 1.48-1.79]), and oleic acid (RR 1.87 [95% CI 1.62-2.17]), respectively. Lysophosphatidylcholine C18:0 (RR 0.80 [95% CI 0.72-0.90]) and creatinine (RR 0.63 [95% CI 0.53-0.74]) were associated with 20% and 37% decreased T2DM risks, respectively.
Conclusions: Most amino acids in patients were positively related to diabetes, while creatinine and some lysophosphatidylcholines showed a negative relationship. This suggests that diabetic risk prediction using metabolites that sensitively reflect changes in the body will improve individual diagnosis and personalize medicine.
Keywords: Cohort; Glucose intolerance; Metabolite; Type 2 diabetes mellitus.
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