Folic Acid Reduces Insulin Resistance in Mice With Diet‐Induced Obesity by Altering One‐Carbon Metabolism and DNA Methylation Patterns of Hypothalamic and Hepatic Insulin Receptor Gene
Bibliographic record
Abstract
Diet-induced obesity and insulin resistance (IR) are associated with alterations in one-carbon (1C) metabolism, gene methylation, and expression. Folate, a methyl donor in 1C metabolism, is essential in gene methylation and expression and has been shown to reduce IR but the precise mechanism(s) remains unclear. Therefore, we investigated whether reduced IR can be explained by 1C metabolism modifications and differences in hypothalamic and hepatic IR-related genes expression and methylation patterns. Four-week-old male C57BL/6J mice (n = 12/group) received high-fat diets (HFDs) with 1- (control), 5- (5FA-HFD), or 10-fold (10FA-HFD) AIN-93G amounts folic acid (FA) for 15 weeks. Body weight, hepatic 1C metabolites, plasma insulin and glucose, and hepatic and hypothalamic expression and methylation of IR-related genes were measured. 5FA-HFD and 10FA-HFD mice had ∼50% lower HOMA-IR compared to control. 10FA-HFD mice also had lower body weight (9%) and adiposity (13%) and higher s-adenosylmethionine levels (19%). 5FA-HFD mice had higher hepatic s-adenosylhomocysteine levels (26%) and DNA methyltransferase 3b expression (45%). Methylation of the InsR gene was correlated with gene expression and the improved metabolic phenotype. FA supplementation reduced IR by modifying 1C metabolism in DIO male mice by differentially altering hypothalamic and hepatic methylation patterns of InsR gene.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".