Scholarlink

Background <p>Gestational diabetes mellitus (GDM) diagnosed early in pregnancy (before 20 weeks’ gestation) is associated with increased metabolic risk, yet its molecular profile remains poorly defined. While disrupted lipid metabolism is an important feature of GDM, no previous study has characterized the lipidomic profile of women with early GDM (eGDM).</p> Methods <p>We performed untargeted liquid chromatography mass spectrometry on maternal plasma samples from a cohort of 180 women at risk of GDM, enrolled in the Treatment of Booking GDM (TOBOGM) multicenter randomized controlled trial. Oral glucose tolerance tests (OGTT) were conducted before 20 weeks’ gestation to diagnose eGDM using World Health Organization (2013) criteria. Lipidomic data were analyzed using multivariable linear regression, unsupervised clustering, weighted gene co-expression network analysis (WGCNA), and logistic regression-based risk modeling.</p> Results <p>In 89 eGDM and 91 non-GDM controls, we quantify 543 lipid species across 18 lipid classes. We identify a distinct lipidomic signature of eGDM, comprising elevated concentrations of glycerolipids (diacylglycerols), fatty acids, and ethanolamine-containing glycerophospholipids (phosphatidylethanolamine and lysophosphatidylethanolamine), alongside lower concentrations of choline-containing glycerophospholipids (lysophosphatidylcholine and ether-linked phosphatidylcholine) and glycosphingolipids (hexosylceramides). Fatty acid and diacylglycerol species are the strongest and most consistent lipid predictors of eGDM and glycemic indices, independent of clinical risk factors. Lipid ontology-based enrichment analysis reveals perturbations in pathways related to lipid storage, membrane remodeling, and signaling.</p> Conclusion <p>To our knowledge, this is the first study to characterize the lipidomic profile of women with eGDM. We identify a distinct lipidomic signature associated with eGDM, offering molecular insights into pathophysiology and highlighting candidate lipid biomarkers for future investigation and validation in this context.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Lipidomic profiling reveals a distinct lipidomic signature of early gestational diabetes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月4日

查看全文
  • Saeede Saadati,
  • Rasoul Godini,
  • Eveline Jona,
  • Christopher K. Barlow,
  • Adriana CH Neven,
  • Christopher J. Nolan,
  • David Simmons,
  • Helena Teede,
  • Aya Mousa,
  • William Hague,
  • Wah Cheung,
  • Michael Peek,
  • Jeff Flack,
  • Mark Mclean,
  • Vincent Wong,
  • Emily Hibbert

摘要

Background

Gestational diabetes mellitus (GDM) diagnosed early in pregnancy (before 20 weeks’ gestation) is associated with increased metabolic risk, yet its molecular profile remains poorly defined. While disrupted lipid metabolism is an important feature of GDM, no previous study has characterized the lipidomic profile of women with early GDM (eGDM).

Methods

We performed untargeted liquid chromatography mass spectrometry on maternal plasma samples from a cohort of 180 women at risk of GDM, enrolled in the Treatment of Booking GDM (TOBOGM) multicenter randomized controlled trial. Oral glucose tolerance tests (OGTT) were conducted before 20 weeks’ gestation to diagnose eGDM using World Health Organization (2013) criteria. Lipidomic data were analyzed using multivariable linear regression, unsupervised clustering, weighted gene co-expression network analysis (WGCNA), and logistic regression-based risk modeling.

Results

In 89 eGDM and 91 non-GDM controls, we quantify 543 lipid species across 18 lipid classes. We identify a distinct lipidomic signature of eGDM, comprising elevated concentrations of glycerolipids (diacylglycerols), fatty acids, and ethanolamine-containing glycerophospholipids (phosphatidylethanolamine and lysophosphatidylethanolamine), alongside lower concentrations of choline-containing glycerophospholipids (lysophosphatidylcholine and ether-linked phosphatidylcholine) and glycosphingolipids (hexosylceramides). Fatty acid and diacylglycerol species are the strongest and most consistent lipid predictors of eGDM and glycemic indices, independent of clinical risk factors. Lipid ontology-based enrichment analysis reveals perturbations in pathways related to lipid storage, membrane remodeling, and signaling.

Conclusion

To our knowledge, this is the first study to characterize the lipidomic profile of women with eGDM. We identify a distinct lipidomic signature associated with eGDM, offering molecular insights into pathophysiology and highlighting candidate lipid biomarkers for future investigation and validation in this context.