Estrogen-Related Receptor-α Coordinates Transcriptional Programs Essential for Exercise Tolerance and Muscle Fitness
Bibliographic record
Abstract
Muscle fitness is an important determinant of health and disease. However, the molecular mechanisms involved in the coordinate regulation of the metabolic and structural determinants of muscle endurance are still poorly characterized. Herein, we demonstrate that estrogen-related receptor α (ERRα, NR3B1) is essential for skeletal muscle fitness. Notably, we show that ERRα-null animals are hypoactive and that genetic or therapeutic disruption of ERRα in mice results in reduced exercise tolerance. Mice lacking ERRα also exhibited lactatemia at exhaustion. Gene expression profiling demonstrates that ERRα plays a key role in various metabolic processes important for muscle function including energy substrate transport and use (Ldhd, Slc16a1, Hk2, and Glul), the tricarboxylic acid cycle (Cycs, and Idh3g), and oxidative metabolism (Pdha1, and Uqcrq). Metabolomics studies revealed impairment in replenishment of several amino acids (eg, glutamine) during recovery to exercise. Moreover, loss of ERRα was found to alter the expression of genes involved in oxidative stress response (Hmox1), maintenance of muscle fiber integrity (Trim63, and Hspa1b), and muscle plasticity and neovascularization (Vegfa). Taken together, our study shows that ERRα plays a key role in directing transcriptional programs required for optimal mitochondrial oxidative potential and muscle fitness, suggesting that modulation of ERRα activity could be used to manage metabolic myopathies and/or promote the adaptive response to physical exercise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".