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Background <p>Gestational diabetes mellitus (GDM) is a complex metabolic disorder with a substantial genetic component; however, whether lipid species mediate the impact of genetic susceptibility on GDM risk remains unclear. This study aimed to characterize genetic architecture of GDM and evaluate whether lipid species mediate the genetic risk.</p> Methods <p>A cohort and case-cohort design were implemented within the Anqing Pregnant Women Cohort. Maternal blood was collected at 15–20 gestational weeks, and GDM was diagnosed at 24–28 weeks. A Meta-GWAS of GDM was performed using regression-based methods, and polygenic risk score (PRS) was constructed. Lipidomic analysis was performed to identity differential lipid species. Risk Ratios (RRs) and 95% confidence interval (CI) were estimated via weighted Poisson regression. Weighted co-abundance network analysis (WGCNA) was applied to cluster lipids into co-abundance modules. Mediation analyses were used to estimate the extent to which lipid species statistically accounted for the association between genetic risk and GDM. A nested 5-fold cross-validation framework was used to explore predictive models and to evaluate the incremental value of PRS and lipid features.</p> Results <p>The Meta-GWAS of 536 GDM and 2,051 controls identified one genome-wide significant risk locus (<i>LIPF</i>) and eight suggestive loci, including two novel signals (<i>IL17B</i>, <i>RPL15P2</i>). Implicated genes were enriched in glycerolipid metabolism pathways. Lipidomic analysis in a case-cohort of 102 GDM and 111 controls identified 134 differential lipid species. WGCNA yielded 14 distinct co-abundance modules, five of which were significantly associated with GDM. Lipid mediators, including specific triacylglycerols, phosphatidylethanolamines, and hexosylceramides, collectively accounted for approximately 31.10% of the overall genetic effect on GDM. Modules enriched for these lipids showed varying degrees of statistical mediation for <i>rs16885782</i> (<i>CDKAL1</i>), <i>rs11236507</i> (<i>DGAT2</i>) and <i>rs10830963</i> (<i>MTNR1B</i>), with mediation effect ranging from 10.30% to 22.07%. The incorporation of lipid biomarkers significantly improved GDM prediction (AUC = 0.849, <i>P</i> = 0.001), whereas further adding PRS did not show significant improvement (AUC = 0.858, <i>P</i> = 0.095).</p> Conclusions <p>Genes involved in lipid metabolism are associated with GDM susceptibility. Lipids potentially mediate the genetic risk of GDM, and lipid biomarkers showed potential for improving predictive performance. These findings require further validation in independent cohorts.</p>

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Genomic and lipidomic analysis reveals lipid mediation of genetic risk in gestational diabetes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Yao Dong,
  • An-qun Hu,
  • Bai-xue Han,
  • Qing Li,
  • Hai-yan Liu,
  • Jin-jin Liu,
  • Zong-guang Li,
  • Zi-qiang Qian,
  • Meng-ting Cao,
  • Long-nan Pan,
  • Yun-yun Xu,
  • Yao Pei,
  • Fang Wu,
  • Yan Tan,
  • Yong-fu Yu,
  • Ying-jie Zheng

摘要

Background

Gestational diabetes mellitus (GDM) is a complex metabolic disorder with a substantial genetic component; however, whether lipid species mediate the impact of genetic susceptibility on GDM risk remains unclear. This study aimed to characterize genetic architecture of GDM and evaluate whether lipid species mediate the genetic risk.

Methods

A cohort and case-cohort design were implemented within the Anqing Pregnant Women Cohort. Maternal blood was collected at 15–20 gestational weeks, and GDM was diagnosed at 24–28 weeks. A Meta-GWAS of GDM was performed using regression-based methods, and polygenic risk score (PRS) was constructed. Lipidomic analysis was performed to identity differential lipid species. Risk Ratios (RRs) and 95% confidence interval (CI) were estimated via weighted Poisson regression. Weighted co-abundance network analysis (WGCNA) was applied to cluster lipids into co-abundance modules. Mediation analyses were used to estimate the extent to which lipid species statistically accounted for the association between genetic risk and GDM. A nested 5-fold cross-validation framework was used to explore predictive models and to evaluate the incremental value of PRS and lipid features.

Results

The Meta-GWAS of 536 GDM and 2,051 controls identified one genome-wide significant risk locus (LIPF) and eight suggestive loci, including two novel signals (IL17B, RPL15P2). Implicated genes were enriched in glycerolipid metabolism pathways. Lipidomic analysis in a case-cohort of 102 GDM and 111 controls identified 134 differential lipid species. WGCNA yielded 14 distinct co-abundance modules, five of which were significantly associated with GDM. Lipid mediators, including specific triacylglycerols, phosphatidylethanolamines, and hexosylceramides, collectively accounted for approximately 31.10% of the overall genetic effect on GDM. Modules enriched for these lipids showed varying degrees of statistical mediation for rs16885782 (CDKAL1), rs11236507 (DGAT2) and rs10830963 (MTNR1B), with mediation effect ranging from 10.30% to 22.07%. The incorporation of lipid biomarkers significantly improved GDM prediction (AUC = 0.849, P = 0.001), whereas further adding PRS did not show significant improvement (AUC = 0.858, P = 0.095).

Conclusions

Genes involved in lipid metabolism are associated with GDM susceptibility. Lipids potentially mediate the genetic risk of GDM, and lipid biomarkers showed potential for improving predictive performance. These findings require further validation in independent cohorts.