Maternal obesity alters fatty acid oxidation, AMPK activity, and associated DNA methylation in mesenchymal stem cells from human infants
Bibliographic record
Abstract
OBJECTIVE: Infants born to mothers with obesity have greater adiposity, ectopic fat storage, and are at increased risk for childhood obesity and metabolic disease compared with infants of normal weight mothers, though the cellular mechanisms mediating these effects are unclear. METHODS: We tested the hypothesis that human, umbilical cord-derived mesenchymal stem cells (MSCs) from infants born to obese (Ob-MSC) versus normal weight (NW-MSC) mothers demonstrate altered fatty acid metabolism consistent with adult obesity. In infant MSCs undergoing myogenesis in vitro, we measured cellular lipid metabolism and AMPK activity, AMPK activation in response to cellular nutrient stress, and MSC DNA methylation and mRNA content of genes related to oxidative metabolism. RESULTS: We found that Ob-MSCs exhibit greater lipid accumulation, lower fatty acid oxidation (FAO), and dysregulation of AMPK activity when undergoing myogenesis in vitro. Further experiments revealed a clear phenotype distinction within the Ob-MSC group where more severe MSC metabolic perturbation corresponded to greater neonatal adiposity and umbilical cord blood insulin levels. Targeted analysis of DNA methylation array revealed Ob-MSC hypermethylation in genes regulating FAO (PRKAG2, ACC2, CPT1A, SDHC) and corresponding lower mRNA content of these genes. Moreover, MSC methylation was positively correlated with infant adiposity. CONCLUSIONS: These data suggest that greater infant adiposity is associated with suppressed AMPK activity and reduced lipid oxidation in MSCs from infants born to mothers with obesity and may be an important, early marker of underlying obesity risk.
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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) | 0.001 | 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".