ArticleNature communications2025
Genetic architecture and risk prediction of gestational diabetes mellitus in Chinese pregnancies.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycaemic traits during pregnancy reveals limited evidence of pregnancy-specific genetic effects.Nature communications · 2026Pooled it
- Cross-ancestry analysis of gestational diabetes mellitus identifies novel loci, drug targets and biological pathways.Frontiers in endocrinology · 2026Pooled it
- Omitting post-alignment processing and merging batch-based imputation: an efficient workflow for NIPT data imputation and its application in maternal folate metabolism genotyping.Journal of human genetics · 2026Article
- Genome-wide association analyses of gestational phenotypes identify context-specific genetic effects.Nature genetics · 2026Article
- Article
- Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.Acta obstetricia et gynecologica Scandinavica · 2026Review
- Prenatal Chromium Exposure and Gestational Diabetes Mellitus: Integrating Genetic and Epigenetic Regulation of LPCAT1 from a Phospholipid Remodeling Perspective.Biological trace element research · 2026Article
- GWAS-by-subtraction reveals new genetic architecture and health implications of type 2 diabetes-independent gestational diabetes mellitus.Genome medicine · 2026Article
- Independent and synergistic effects of OGTT-based hyperglycemia phenotypes and gestational weight gain on feto-maternal outcomes in GDM.BMC pregnancy and childbirth · 2026Article
- Prenatal Exposure to Artificial Light at Night and the Offspring's First 1000-Day Growth: A Prospective Metabolomic and Gene-Environment Interaction Study.Environmental science & technology · 2026Article
- Machine Learning-Based Early Prediction of Gestational Diabetes Using First-Trimester Laboratory Parameters.Cureus · 2026Article
- cfGWAS reveal genetic basis of cell-free DNA end motifs.Nature communications · 2026Article
- Predictive Value of Serum Pentraxin 3 and Galectin-3 in Early Pregnancy for Gestational Diabetes Mellitus in Chinese Women.International journal of women's health · 2026Article
- Flexible read-aware genotype imputation from sequence using biobank sized reference panels.Nature communications · 2025Article
- Placental growth plays a key role in the link between maternal glucose levels in pregnancy and risk of preeclampsia.medRxiv : the preprint server for health sciences · 2025Article
- From Molecular Insights to Clinical Management of Gestational Diabetes Mellitus-A Narrative Review.International journal of molecular sciences · 2025Review
- ZJU index as a predictive biomarker of gestational diabetes mellitus: a prospective cohort analysis.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Gestational diabetes mellitus, a heritable metabolic disorder and the most common pregnancy-related condition, remains understudied regarding its genetic architecture and its potential for early prediction using genetic data. Here we conducted genome-wide association studies on 116,144 Chinese pregnancies, leveraging their non-invasive prenatal test sequencing data and detailed prenatal records. We identified 13 novel loci for gestational diabetes mellitus and 111 for five glycemic traits, with minor allele frequencies of 0.01-0.5 and absolute effect sizes of 0.03-0.62. Approximately 50% of these loci were specific to gestational diabetes mellitus and gestational glycemic levels, distinct from type 2 diabetes and general glycemic levels in East Asians. A machine learning model integrating polygenic risk scores and prenatal records predicted gestational diabetes mellitus before 20 weeks of gestation, achieving an area under the receiver operating characteristic curve of 0.729 and an accuracy of 0.835. Shapley values highlighted polygenic risk scores as key contributors. This model offers a cost-effective strategy for early gestational diabetes mellitus prediction using clinical non-invasive prenatal test.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.