PGC-1α4 Interacts with REST to Upregulate Neuronal Genes and Augment Energy Consumption in Developing Cardiomyocytes
Bibliographic record
Abstract
Transcriptional coactivator PGC-1α is a main regulator of cardiac energy metabolism. In addition to canonical PGC-1α1, other PGC-1α isoforms have been found to exert specific biological functions in a variety of tissues. We investigated the expression patterns and the biological effects of the non-canonical isoforms in the heart. We used RNA sequencing data to identify the expression patterns of PGC-1α isoforms in the heart. To evaluate the biological effects of the alternative isoform expression, we generated a transgenic mouse with cardiac-specific overexpression of PGC-1α4 and analysed the cardiac phenotype with a wide spectrum of physiological and biophysical tools. Our results show that non-canonical isoforms are expressed in the heart, and that the main variant PGC-1α4 is induced by β-adrenergic signalling in adult cardiomyocytes. Cardiomyocyte specific PGC-1α4 overexpression in mice relieves the RE1-Silencing Transcription factor (REST)-mediated suppression of neuronal genes during foetal heart development. The resulting de-repression of REST target genes induces a cardiac phenotype with increased cellular energy consumption, resulting in postnatal dilated cardiomyopathy. These results propose a new concept for actions of the PGC-1α protein family where activation of the Pgc-1α gene, through its isoforms, induces a phenotype with concurrent supply and demand for cellular energy. These data highlight the biological roles of the different PGC-1α isoforms, which should be considered when future therapies are developed.
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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".