Abstract P348: High Glucose Induces Smad Activation via the Transcriptional Coregulator P300 and Contributes to Cardiac Fibrosis and Hypertrophy
Bibliographic record
Abstract
Background: Despite advances in the treatment of heart failure (HF), the mortality remains high, particularly in those individuals with diabetes mellitus. Activated transforming growth factor beta (TGF-ß) contributes to the pathogenesis of diabetic cardiomyopathy. We hypothesized that the transcriptional co-activator p300 regulates glucose induced activation of TGF-ß via acetylation of a specific Lysine residue (Lys19) in the Mad homology 1 domain of Smad 2, and that by inhibiting p300, TGF-ß activity will be reduced and heart failure ameliorated/prevented. Methods: p300 activity and Smad acetylation in normal glucose (5.6 mmol/L - NG) and high glucose (25 mmol/L - HG) media were assessed in H9c2 rat cardiomyoblasts. [H]3 proline incorporation was assessed in cardiac fibroblasts as a marker of collagen synthesis. The role of increased p300 activity was assessed in vitro by using a known p300 inhibitor, curcumin or siRNA directed at p300 and in vivo in a hemodynamically validated model of diabetic cardiomyopathy, the (mRen)2-27 transgenic rat. Results: H9c2 cells exposed to HG demonstrated increased p300 activity c/w NG media, that was reduced by p300 inhibition using curcumin or p300 siRNA (all p<0.01). Increased p300 activity in HG media increased [H]3 proline incorporation (p<0.05). This effect was attenuated by treatment with curcumin/p300 siRNA (p<0.01). Finally, H9c2 cells were stimulated, extracted protein was immunoprecipitated with Smad2, and lys19 acetylation assessed. Acetylation of the Lys19 was reduced in cells pre-incubated with the p300 inhibitor (p<0.05). To determine the functional significance of p300 inhibition, diabetic Ren-2 rats were randomised to receive either curcumin/vehicle for 6 weeks. Curcumin treated diabetic rats had reduced cardiac hypertrophy and improved chamber compliance when c/w untreated diabetic counterparts (all p<0.01). Conclusions: These findings demonstrate that high glucose increases activity of the transcriptional coregulator p300, acetylating Smad2 and promoting cardiac fibrosis and hypertrophy. Inhibition of p300 reduces cardiac hypertrophy and results in improved diastolic function. Modulation of the p300 may be a novel strategy to treat diabetes induced heart failure.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".