Abnormal fatty acid metabolism is a core component of spinal muscular atrophy
Bibliographic record
Abstract
Abstract Objective Spinal muscular atrophy (SMA) is an inherited neuromuscular disorder leading to paralysis and subsequent death in young children. Initially considered a motor neuron disease, extra‐neuronal involvement is increasingly recognized. The primary goal of this study was to investigate alterations in lipid metabolism in SMA patients and mouse models of the disease. Methods We analyzed clinical data collected from a large cohort of pediatric SMA type I–III patients as well as SMA type I liver necropsy data. In parallel, we performed histology, lipid analysis, and transcript profiling in mouse models of SMA. Results We identify an increased susceptibility to developing dyslipidemia in a cohort of 72 SMA patients and liver steatosis in pathological samples. Similarly, fatty acid metabolic abnormalities were present in all SMA mouse models studied. Specifically, Smn 2B/‐ mice displayed elevated hepatic triglycerides and dyslipidemia, resembling non‐alcoholic fatty liver disease (NAFLD). Interestingly, this phenotype appeared prior to denervation. Interpretation This work highlights metabolic abnormalities as an important feature of SMA, suggesting implementation of nutritional and screening guidelines in patients, as such defects are likely to increase metabolic distress and cardiovascular risk. This study emphasizes the need for a systemic therapeutic approach to ensure maximal benefits for all SMA patients throughout their life.
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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 | 0.001 |
| 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".