Multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycaemic traits during pregnancy reveals limited evidence of pregnancy-specific genetic effects
Bibliographic record
Abstract
Abstract Gestational diabetes mellitus (GDM) affects ∼14% of pregnancies and is linked to adverse pregnancy outcomes and increased maternal type 2 diabetes mellitus (T2DM) risk. The GenDiP Consortium conducted trans-generational, multi-ancestry genome-wide association study meta-analyses of GDM and pregnancy glycemic traits in up to 38,305 GDM cases and 776,145 controls. We identified 37 GDM-associated loci (19 novel) and five novel loci for glycemic traits, all operating through the maternal genome. Most GDM loci overlapped with T2DM and non-pregnant glycemic traits, with limited evidence for pregnancy-specific effects. MTNR1B showed pregnancy-enhanced effects on 2-hour glucose, potentially mediated by interaction with GPR61 , a novel GDM locus, suggesting a gestation-specific melatonin-glucose signalling axis. We also observed ancestry-specific effects at the fasting glucose locus ABCB11 , with opposite directions in European and East Asian populations. Our findings provide new insights into the genetic architecture of GDM and highlight the need for larger, ancestrally diverse studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".