Gestational Diabetes Alters Offspring DNA Methylation Profiles in Human and Rat: Identification of Key Pathways Involved in Endocrine System Disorders, Insulin Signaling, Diabetes Signaling, and ILK Signaling
Bibliographic record
Abstract
Gestational diabetes is associated with risk for metabolic disease later in life. Using a cross-species approach in rat and humans, we examined the hypothesis that gestational diabetes during pregnancy triggers changes in the methylome of the offspring that might be mediating these risks. We show in a gestation diabetes rat model, the Cohen diabetic rat, that gestational diabetes triggers wide alterations in DNA methylation in the placenta in both candidate diabetes genes and genome-wide promoters, thus providing evidence for a causal relationship between diabetes during pregnancy and DNA methylation alterations. There is a significant overlap between differentially methylated genes in the placenta and the liver of the rat offspring. Several genes differentially methylated in rat placenta exposed to maternal diabetes are also differentially methylated in the human placenta of offspring exposed to gestational diabetes in utero. DNA methylation changes inversely correlate with changes in expression. The changes in DNA methylation affect known functional gene pathways involved in endocrine function, metabolism, and insulin responses. These data provide support to the hypothesis that early-life exposures and their effects on metabolic disease are mediated by DNA methylation changes. This has important diagnostic and therapeutic implications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".