Failure to up-regulate transcription of genes necessary for muscle adaptation underlies limb girdle muscular dystrophy 2A (calpainopathy)
Bibliographic record
Abstract
Limb girdle muscular dystrophy 2A is due to loss-of-function mutations in the Calpain 3 ( CAPN3 ) gene. Our previous data suggest that CAPN3 helps to maintain the integrity of the triad complex in skeletal muscle. In Capn3 knock-out mice (C3KO), Ca 2+ release and Ca 2+ /calmodulin kinase II (CaMKII) signaling are attenuated. We hypothesized that calpainopathy may result from a failure to transmit loading-induced Ca 2+ -mediated signals, necessary to up-regulate expression of muscle adaptation genes. To test this hypothesis, we compared transcriptomes of muscles from wild type (WT) and C3KO mice subjected to endurance exercise. In WT mice, exercise induces a gene signature that includes myofibrillar, mitochondrial and oxidative lipid metabolism genes, necessary for muscle adaptation. C3KO muscles fail to activate the same gene signature. Furthermore, in agreement with the aberrant transcriptional profile, we observe a commensurate functional defect in lipid metabolism whereby C3KO muscles fail to release fatty acids from stored triacylglycerol. In conjunction with the defects in oxidative metabolism, C3KO mice demonstrate reduced exercise endurance. Failure to up-regulate genes in C3KO muscles is due, in part, to decreased levels of PGC1α, a transcriptional co-regulator that orchestrates the muscle adaptation response. Destabilization of PGC1α is attributable to decreased p38 MAPK activation via diminished CaMKII signaling. Thus, we elucidate a pathway downstream of Ca 2+ -mediated CaMKII activation that is dysfunctional in C3KO mice, leading to reduced transcription of genes involved in muscle adaptation. These studies identify a novel mechanism of muscular dystrophy: a blunted transcriptional response to muscle loading resulting in chronic failure to adapt and remodel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".