Association of maternal blood metabolomics and gestational diabetes mellitus risk: a systematic review and meta-analysis.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that has short- and long-term adverse effects. Therefore, further exploration of the pathophysiology of GDM and related biomarkers is important. In this study, we performed a systematic review and meta-analysis to investigate the associations between metabolites in blood detected via metabolomics techniques and the risk of GDM and to identify possible biomarkers for predicting the occurrence of GDM. We retrieved case‒control and cohort studies of metabolomics and GDM published in PubMed, Embase, and Web of Science through March 29, 2024; extracted metabolite concentrations, odds ratios (ORs), or relative risks (RRs); and evaluated the integrated results with metabolites per-SD risk estimates and 95% CIs for GDM. We estimated the results via the random effects model and the inverse variance method. Our study is registered in PROSPERO (CRD42024539435). We included a total of 28 case‒control and cohort studies, including 17,370 subjects (4,372 GDM patients and 12,998 non-GDM subjects), and meta-analyzed 67 metabolites. Twenty-five of these metabolites were associated with GDM risk. Some amino acids (isoleucine, leucine, valine, alanine, aspartate, etc.), lipids (C16:0, C18:1n-9, C18:1n-7, lysophosphatidylcholine (LPC) (16:0), LPC (18:0), and palmitoylcarnitine), and carbohydrates and energy metabolites (glucose, pyruvate, lactate, 2-hydroxybutyrate, 3-hydroxybutyrate) were discovered to be associated with increased GDM risk (hazard ratio 1.06-2.77). Glutamine, histidine, C14:0, and sphingomyelin (SM) (34:1) were associated with lower GDM risk (hazard ratio 0.75-0.84). These findings suggest that these metabolites may play essential roles in GDM progression, and serve as biomarkers, contributing to the early diagnosis and prediction of GDM.