First trimester plasma microRNAs levels predict Matsuda Index-estimated insulin sensitivity between 24th and 29th week of pregnancy
Bibliographic record
Abstract
INTRODUCTION: Gestational diabetes mellitus (GDM) is a consequence of an imbalance between insulin sensitivity (IS) and secretion during pregnancy. MicroRNAs (miRNAs) are small and secreted RNA molecules stable in blood and known to regulate physiological processes including glucose homeostasis. The aim of this study was to identify plasmatic miRNAs detectable in early pregnancy predicting IS at 24th-29th week of pregnancy. RESEARCH DESIGN AND METHODS: We quantified circulating miRNAs in 421 women in plasma collected at 9.6±2.2 weeks of pregnancy using next-generation sequencing. RESULTS: we detected 2170 miRNAs: 39 (35 positively and 4 negatively) were associated with IS as estimated by the Matsuda Index at 26.4±1.0 weeks of pregnancy. Lasso regression identified 18 miRNAs independently predicting Matsuda Index-estimated IS. Together with gestational age, maternal age and body mass index at first trimester, they explain 36% of IS variance in late second trimester of pregnancy. These miRNAs regulate fatty acid biosynthesis and metabolism among other pathways. CONCLUSIONS: In summary, we have identified first trimester plasmatic miRNAs predictive of Matsuda Index-estimated IS in late second trimester of pregnancy. These miRNAs could also contribute to initiate and support IS adaptation to pregnancy potentially through lipid metabolism regulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".