95-OR: Plasma miRNAs Levels at First Trimester of Pregnancy Predict Insulin Sensitivity Estimated at the Second Trimester of Pregnancy
Bibliographic record
Abstract
Background: Gestational diabetes mellitus (GDM) is the most common pregnancy complication with a prevalence of 14% worldwide and has important consequences on both the mother and her child. GDM results from imbalance between insulin secretion capacity response and decreasing insulin sensitivity in pregnancy. MicroRNAs (miRNAs) are small (19-24nt) single-stranded RNA molecules involved in post-transcriptional regulation through binding to targeted mRNAs. MiRNAs are thought to regulate many physiological processes including glucose homeostasis. Objective: Identify plasmatic miRNAs at the first trimester of pregnancy that predict insulin sensitivity (IS; as estimated with the Matsuda index) assessed between the 24th and the 28thweek of pregnancy. Methods: miRNAs were quantified by next generation sequencing in 443 plasma samples from the Gen3G birth-cohort. DESeq2 package was applied to identify miRNAs associated with IS. Glmnet package was used to compute lasso regression and find the minimum number of miRNAs predicting IS. Results: On average, participants were 28.43 ± 4.3 (18-47) years old and had a BMI of 26.1 ± 6.1 (16.6-54.1) kg/m2 at first trimester and had a Matsuda index of 8.41 ± 4.9 (0.77-37.53) at second trimester. A total of 106 miRNAs were associated with IS (p-adjusted for false discovery rate <0.1) when analyses were corrected for gestational age at blood collection, with 37 of them remaining significant after further correction for maternal age and BMI measured at first trimester. A lasso regression selected 27 of these miRNAs along with maternal age and BMI and overall explained 32% of the variability of IS at second trimester. Conclusion: miRNAs quantified at first trimester of pregnancy are associated with and predictive of maternal IS estimated at second trimester. These miRNAs are likely involved in the pathophysiology of GDM and provide novel promising biomarkers for predicting glucose metabolism dysregulation in pregnancy. Disclosure C. Légaré: None. V. Desgagné: None. F. White: None. M.S. Scott: None. P. Perron: None. M. Hivert: None. R. Guérin: None. L. Bouchard: None. Funding IRSC (IGH-155183)
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".