Epigenetic transmission of cardiometabolic risk in offspring discordant for maternal gestational metabolic fitness
Bibliographic record
Abstract
Abstract OBJECTIVE Diabesity during gestation predisposes offspring to lifetime cardiometabolic risk. We demonstrated that maternal biliopancreatic diversion surgery (BPD) improved metabolic fitness and pregnancies reducing cardiometabolic risk in siblings born after (AMS) compared to before maternal surgery (BMS). We found differential methylation of inflammatory and glucoregulatory genes in peripheral blood cell DNA in offspring and in mothers after BPD compared to preoperative “control” women. Here we study offspring trajectories of cardiometabolic risk markers and determine persistence of the methylome related to body weight (BMI) and gestational weight gain (GWG). RESEARCH DESIGN AND METHODS Prospective, cross-sectional study of 133 mothers with 89 BMS and 183 AMS offspring born mean 4 years after BPD and 83 unoperated control women was conducted, and differential methylation patterns in mothers were compared with those of offspring during 2-26 years. RESULTS Independent of maternal or offspring BMI and GWG, postoperative maternal metabolic fitness was associated with improved cardiometabolic phenotype in AMS vs. BMS offspring sustained beyond puberty. BMS offspring exhibited increasing linear trajectories of weight, cardiometabolic and inflammation risk factors versus normative horizontal trajectories of AMS offspring. Methylation differences between AMS and BMS offspring identified 45 625 differentially methylated sites, 73% overlapping with those of mothers vs. controls; 4 446 demonstrated similar sustained directionality of differences in methylation levels; 154 sites exhibited significant correlation coefficients (r≥0.4) overrepresented within genes associated with cardiometabolic risk, growth and inflammation. CONCLUSION Maternal BPD appears to epigenetically prevent transmission of cardiometabolic risk independent of BMI.
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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 | 0.000 | 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) | 0.002 | 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".