354-OR: Physiologic Pathways in Pregnancy Glycemic Regulation Implicated through Genetic Clustering Analysis
Bibliographic record
Abstract
Background: Genetic determinants of glycemic regulation in pregnancy are poorly understood. Methods: We studied 35 glycemia-related traits measured during pregnancy and 191 genetic variants identified in prior genome-wide association studies of type 2 diabetes (T2D) or gestational glycemia. Using linear regression, we quantified associations between glucose-raising alleles and traits measured in 582 women at 24-28 weeks gestation. We clustered traits and variants using Bayesian nonnegative matrix factorization (bNMF) to identify physiologic pathways involved in pregnancy glucose metabolism. Results: In a plurality of bNMF iterations (22/50), 5 clusters emerged, with highly weighted traits and loci suggesting distinct physiologic pathways. Cluster 1: reduced insulin secretory response (lower insulin/c-peptide, greater insulin sensitivity); loci included several known or suspected to affect beta-cell function (ABO, CDKN2B, SLC30A8, CDKN1B). Cluster 2: obesity-related hyperglycemia (higher percent body fat, BMI, fasting/post-load glucose); loci included known obesity/T2D loci (MCR4, FTO) and loci previously tied to beta-cell function that associated with higher glucose and greater adiposity pregnant women (MTNR1B, GLP2R). Cluster 3: insulin resistance (reduced insulin sensitivity, higher fasting insulin/c-peptide, greater insulin secretory response); loci included LYPLAL1 and ANKRD55 (known to harbor insulin resistance variants). Cluster 4 traits suggested reduced adiposity with post-load glucose intolerance. Cluster 5 traits suggested a favorable metabolic profile (lower cholesterol and glucose, higher disposition index and insulin sensitivity). Conclusion: Genetic variants can be grouped to identify physiologic mechanisms at play in gestational glycemic regulation. Associations between physiologically-informed variant clusters, gestational diabetes, and related perinatal outcomes await testing in well-powered cohorts. Disclosure C.E. Powe: None. M. Udler: None. C. Allard: None. J. Kim: None. P. Perron: None. L. Bouchard: None. J.C. Florez: None. M. Hivert: None. Funding American Diabetes Association/Pathway to Stop Diabetes (1-15-ACE-26 to M-F.H.); National Institute of Diabetes and Digestive and Kidney Diseases (K23DK113218, K24DK110550); Robert Wood Johnson Foundation; Fonds de la recherche du Québec en santé
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".