Genomic and lipidomic analysis reveals lipid mediation of genetic risk in gestational diabetes
5 affiliations
- 1Department of Epidemiology, School of Public Health, Fudan University
- 2Department of Clinical Laboratory, Anqing Municipal Hospital
- 3Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University
- 4Department of Obstetrics and Gynecology, Anqing Municipal Hospital
- 5Key Laboratory for Health Technology Assessment, National Commission of Health and Family Planning, Fudan University
Abstract
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.
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BibTeX
@article{dong2026genomic,
title = {{Genomic and lipidomic analysis reveals lipid mediation of genetic risk in gestational diabetes}},
author = {Yao Dong and An-qun Hu and Bai-xue Han and Qing Li and Hai-yan Liu and Jin-jin Liu and Zong-guang Li and Zi-qiang Qian and Meng-ting Cao and Long-nan Pan and Yun-yun Xu and Yao Pei and Fang Wu and Yan Tan and Yong-fu Yu and Ying-jie Zheng},
journal = {BMC Medicine},
year = {2026},
month = jul,
doi = {10.1186/s12916-026-05083-5},
url = {https://doi.org/10.1186/s12916-026-05083-5},
note = {CC BY},
}
RIS
TY - JOUR
TI - Genomic and lipidomic analysis reveals lipid mediation of genetic risk in gestational diabetes
AU - Yao Dong
AU - An-qun Hu
AU - Bai-xue Han
AU - Qing Li
AU - Hai-yan Liu
AU - Jin-jin Liu
AU - Zong-guang Li
AU - Zi-qiang Qian
AU - Meng-ting Cao
AU - Long-nan Pan
AU - Yun-yun Xu
AU - Yao Pei
AU - Fang Wu
AU - Yan Tan
AU - Yong-fu Yu
AU - Ying-jie Zheng
PY - 2026
DA - 2026/07/01
JO - BMC Medicine
DO - 10.1186/s12916-026-05083-5
UR - https://doi.org/10.1186/s12916-026-05083-5
AB - 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.
SN - 1741-7015
ER -