P.068 Abnormal fatty acid metabolism is a feature of spinal muscular atrophy
Bibliographic record
Abstract
Background: Spinal muscular atrophy (SMA) is a children’s neuromuscular disorder. Although motor neuron loss is a major feature of the disease, we have identified fatty acid abnormalities in SMA patients and in preclinical animal models, suggesting metabolic perturbation is also an important component of SMA. Methods: Biochemical, histological, proteomic, and high resolution respirometry were used. Results: SMA patients are more susceptible to dyslipidemia than the average population as determined by a standard lipid profile in a cohort of 72 pediatric patients. As well, we observed a non-alcoholic liver disease phenotype in apreclinical mouse model. Denervation alone was not sufficient to induce liver steatosis, as a mouse model of ALS, did not develop fatty liver. Hyperglucagonemia in Smn2B/-mice could explain the hepatic steatosis by increasing plasma substrate availability via glycogen depletion and peripheral lipolysis. Proteomic analysis identified mitochondrion and lipid metabolism as major clusters. Alterations in mitochondrial function were revealed by high-resolution respirometry. Finally, low-fat diets led to increased survival in Smn2B/-mice. Conclusions: These results provide strong evidence for lipid metabolism defects in SMA. Further investigation will be required to establish the primary mechanism of these alterations and understand how they lead to additional co-morbidities in SMA patients.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.012 |
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".