Plasma lipidomics profile in pregnancy and gestational diabetes risk: a prospective study in a multiracial/ethnic cohort

Abstract

IntroductionDisruption of lipid metabolism is implicated in gestational diabetes (GDM). However, prospective studies on lipidomics and GDM risk in race/ethnically diverse populations are sparse. Here, we aimed to (1) identify lipid networks in early pregnancy to mid-pregnancy that are associated with subsequent GDM risk and (2) examine the associations of lipid networks with glycemic biomarkers to understand the underlying mechanisms.Research design and methodsThis study included 107 GDM cases confirmed using the Carpenter and Coustan criteria and 214 non-GDM matched controls from the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort, untargeted lipidomics data of 420 metabolites (328 annotated and 92 unannotated), and information on glycemic biomarkers in maternal plasma at visit 0 (10–14 weeks) and visit 1 (15–26 weeks). We constructed lipid networks using weighted correlation network analysis technique. We examined prospective associations of lipid networks and individual lipids with GDM risk using linear mixed effect models. Furthermore, we calculated Pearson’s partial correlation for GDM-related lipid networks and individual lipids with plasma glucose, insulin, C-peptide and glycated hemoglobin at both study visits.ResultsLipid networks primarily characterized by elevated plasma diglycerides and short, saturated/low unsaturated triglycerides and lower plasma cholesteryl esters, sphingomyelins and phosphatidylcholines were associated with higher risk of developing GDM (false discovery rate (FDR) <0.05). Among individual lipids, 58 metabolites at visit 0 and 96 metabolites at visit 1 (40 metabolites at both time points) significantly differed between women who developed GDM and who did not (FDR <0.05). Furthermore, GDM-related lipid networks and individual lipids showed consistent correlations with maternal glycemic markers particularly in early pregnancy at visit 0.ConclusionsPlasma lipid metabolites in early pregnancy both individually and interactively in distinct networks were associated with subsequent GDM risk in race/ethnically diverse US women. Future research is warranted to assess lipid metabolites as etiologic markers of GDM.

Metabolites involved in purine degradation, insulin resistance, and fatty acid oxidation are associated with prediction of Gestational diabetes in plasma

“…The decrease in SMs’ 14:0, 15:0, 16:1, and 22:0 indicates dysregulated sphingolipid metabolism. Past early-pregnancy GDM studies have noted SMs to be lower in GDM cases compared to non-GDM cases ( Furse et al, 2019 ; Rahman et al, 2021 ), and a study by Lai et al found decreased SM levels in women with GDM to be associated with increased risk of developing type 2 diabetes ( Lai et al, 2020 ). Sphingomyelins may play an indirect role in impaired insulin signaling, as increased levels of ceramides, a sphingolipid that can be derived from sphingomyelins, have been reported to inhibit the insulin signaling pathway, while also disturbing mitochondrial respiration ( Roszczyc-Owsiejczuk & Zabielski, 2021 ).…”

The influence of lipids on adverse pregnancy outcomes differs between normal glucose tolerance and gestational diabetes mellitus women: a retrospective study

“…Consistent with the study by Bao et al [25], we found that elevated lipid levels in the middle of pregnancy, especially TG levels, were associated with the risk of GDM. In addition, Daniel et al and Mohammad et al examined that elevated maternal TG levels in early pregnancy were associated with the risk of GDM [9,10]. Yazıcı et al demonstrated that increased lipid levels and altered intracellular signaling metabolism have been associated with insulin resistance, which is mediated by different pathways, such as the novel protein kinase c pathway and the JNK-1 pathway [26].…”

“…To our knowledge, maternal age, obesity, pre-pregnancy body mass index (BMI), and polycystic ovary syndrome (PCOS) history have been generally regarded as the risk factors for GDM [7]. Recent studies have also suggested that abnormal maternal lipid metabolism, especially elevated triglycerides, served as a risk factor for the development of GDM [8][9][10][11]. Actually, the appropriate increase of maternal triglycerides (TG) and cholesterol during pregnancy, considered as a physiological adaptation, has positive impact on the maintenance of pregnancy and fetal growth [7].…”

An anchored experimental design and meta-analysis approach to address batch effects in large-scale metabolomics

“…Metabolomics is a powerful tool in biomarker discovery and holds great promise for precision medicine ( Peng et al, 2015 ; Burgess, 2021 ; Schmidt et al, 2021 ). Targeted metabolomics is common in studies exploring human health questions that range from aging ( Jones et al, 2012 ; Hastings et al, 2019 ) to complex diseases ( Lewis et al, 2008 ; van der Sijde et al, 2014 ; Menni et al, 2017 ; Barupal et al, 2018 ; Rahman et al, 2021 ; Sindelar et al, 2021 ). An advantage of untargeted metabolomics for these questions is the ability to reach beyond sets of well-studied compounds to explore differences in an unbiased way ( Cajka and Fiehn, 2016 ).…”