Methylation and Expression of Immune and Inflammatory Genes in the Offspring of Bariatric Bypass Surgery Patients
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Maternal obesity, excess weight gain and overnutrition during pregnancy increase risks of obesity, type 2 diabetes mellitus, and cardiovascular disease in the offspring. Maternal biliopancreatic diversion is an effective treatment for severe obesity and is beneficial for offspring born after maternal surgery (AMS). These offspring exhibit lower severe obesity prevalence and improved cardiometabolic risk factors including inflammatory marker compared to siblings born before maternal surgery (BMS). OBJECTIVE: To assess relationships between maternal bariatric surgery and the methylation/expression of genes involved in the immune and inflammatory pathways. METHODS: A differential gene methylation analysis was conducted in a sibling cohort of 25 BMS and 25 AMS offspring from 20 mothers. Following differential gene expression analysis (23 BMS and 23 AMS), pathway analysis was conducted. Correlations between gene methylation/expression and circulating inflammatory markers were computed. RESULTS: Five immune and inflammatory pathways with significant overrepresentation of both differential gene methylation and expression were identified. In the IL-8 pathway, gene methylation correlated with both gene expression and plasma C-reactive protein levels. CONCLUSION: These results suggest that improvements in cardiometabolic risk markers in AMS compared to BMS offspring may be mediated through differential methylation of genes involved in immune and inflammatory pathways.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it