Cardiac fibroblast BAG3 regulates TGFBR2 signaling and fibrosis in dilated cardiomyopathy
Bibliographic record
Abstract
Loss of Bcl2-associated athanogene 3 (BAG3) is associated with dilated cardiomyopathy (DCM). BAG3 regulates sarcomere protein turnover in cardiomyocytes; however, the function of BAG3 in other cardiac cell types is understudied. In this study, we used an isogenic pair of BAG3-knockout and wild-type human induced pluripotent stem cells (hiPSCs) to interrogate the role of BAG3 in hiPSC-derived cardiac fibroblasts (CFs). Analysis of cell type-specific conditional knockout engineered heart tissues revealed an essential contribution of CF BAG3 to contractility and cardiac fibrosis, recapitulating the phenotype of DCM. In BAG3-/- CFs, we observed an increased sensitivity to TGF-β signaling and activation of a fibrogenic response when cultured at physiological stiffness (8 kPa). Mechanistically, we showed that loss of BAG3 increased transforming growth factor-β receptor 2 (TGFBR2) levels by directly binding TGFBR2 and mediating its ubiquitination and proteasomal degradation. To further validate these results, we performed single-nucleus RNA sequencing of cardiac tissue from DCM patients carrying pathogenic BAG3 variants. BAG3 pathogenic variants increased fibrotic gene expression in CFs. Together, these results extend our understanding of the roles of BAG3 in heart disease beyond the cardiomyocyte-centric view and highlight the ability of tissue-engineered hiPSC models to elucidate cell type-specific aspects of cardiac disease.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".