The translational regulator FMRP controls lipid and glucose metabolism in mice and humans
Bibliographic record
Abstract
OBJECTIVES: The Fragile X Mental Retardation Protein (FMRP) is a widely expressed RNA-binding protein involved in translation regulation. Since the absence of FMRP leads to Fragile X Syndrome (FXS) and autism, FMRP has been extensively studied in brain. The functions of FMRP in peripheral organs and on metabolic homeostasis remain elusive; therefore, we sought to investigate the systemic consequences of its absence. METHODS: Using metabolomics, in vivo metabolic phenotyping of the Fmr1-KO FXS mouse model and in vitro approaches, we show that the absence of FMRP induced a metabolic shift towards enhanced glucose tolerance and insulin sensitivity, reduced adiposity, and increased β-adrenergic-driven lipolysis and lipid utilization. RESULTS: Combining proteomics and cellular assays, we highlight that FMRP loss increased hepatic protein synthesis and impacted pathways notably linked to lipid metabolism. Mapping metabolomic and proteomic phenotypes onto a signaling and metabolic network, we predicted that the coordinated metabolic response to FMRP loss was mediated by dysregulation in the abundances of specific hepatic proteins. We experimentally validated these predictions, demonstrating that the translational regulator FMRP associates with a subset of mRNAs involved in lipid metabolism. Finally, we highlight that FXS patients mirror metabolic variations observed in Fmr1-KO mice with reduced circulating glucose and insulin and increased free fatty acids. CONCLUSIONS: Loss of FMRP results in a widespread coordinated systemic response that notably involves upregulation of protein translation in the liver, increased utilization of lipids, and significant changes in metabolic homeostasis. Our study unravels metabolic phenotypes in FXS and further supports the importance of translational regulation in the homeostatic control of systemic metabolism.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".