Methylenetetrahydrofolate reductase deficiency and high-dose FA supplementation disrupt embryonic development of energy balance and metabolic homeostasis in zebrafish
Bibliographic record
Abstract
Folic acid (synthetic folate, FA) is consumed in excess in North America and may interact with common pathogenic variants in methylenetetrahydrofolate reductase (MTHFR); the most prevalent inborn error of folate metabolism with wide-ranging obesity-related comorbidities. While preclinical murine models have been valuable to inform on diet-gene interactions, a recent Folate Expert panel has encouraged validation of new animal models. In this study, we characterized a novel zebrafish model of mthfr deficiency and evaluated the effects of genetic loss of mthfr function and FA supplementation during embryonic development on energy homeostasis and metabolism. mthfr-deficient zebrafish were generated using CRISPR mutagenesis and supplemented with no FA (control, 0FA) or 100 μm FA (100FA) throughout embryonic development (0-5 days postfertilization). We show that the genetic loss of mthfr function in zebrafish recapitulates key biochemical hallmarks reported in MTHFR deficiency in humans and leads to greater lipid accumulation and aberrant cholesterol metabolism as reported in the Mthfr murine model. In mthfr-deficient zebrafish, energy homeostasis was also impaired as indicated by altered food intake, reduced metabolic rate and lower expression of central energy-regulatory genes. Microglia abundance, involved in healthy neuronal development, was also reduced. FA supplementation to control zebrafish mimicked many of the adverse effects of mthfr deficiency, some of which were also exacerbated in mthfr-deficient zebrafish. Together, these findings support the translatability of the mthfr-deficient zebrafish as a preclinical model in folate research.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".