Granzyme B contributes to subretinal fibrosis in neovascular age-related macular degeneration by modulating inflammation and epithelial-mesenchymal transition
Bibliographic record
Abstract
BACKGROUND: More than half of patients with neovascular age-related macular degeneration (nAMD) develop subretinal fibrosis, regardless of anti-vascular endothelial growth factor (VEGF) therapy. No treatment exists for subretinal fibrosis, as its pathophysiology remains elusive. Granzyme B (GzmB) is a serine protease elevated in human eyes with nAMD and contributes to choroidal neovascularization (CNV). Although GzmB is involved in dermal and cardiac fibrosis, its role in subretinal fibrosis has yet to be elucidated. METHODS: Using the two-stage laser-induced mouse model of subretinal fibrosis, fibrotic lesions were induced in younger (3–6 months old) and older (7–14 months old) C57BL/6J and GzmB deficient mice. Seven days after the second laser, in vivo imaging of fibrotic lesions was performed using custom-built polarization diversity-optical coherence tomography (PD-OCT) system. Eyes were collected and used for either retina wholemounts or cross-sections. Wholemounts were immunostained to assess pathological features of fibrosis and determine the size of fibrotic lesions and mast cell counts within fibrotic lesions. Cross-sections were processed to quantify the levels of GzmB substrates within fibrotic lesions, namely pro-fibrotic thrombospondin-1 (TSP-1) and anti-fibrotic decorin (DCN), the extent of macrophage-to-myofibroblast transition (MMT), activation of astrocytes/Müller cells and finally photoreceptor cell death. ARPE-19 wound healing assay was performed to study the direct role of GzmB in RPE wound healing in vitro. GzmB-mediated transcriptional changes in ARPE-19 were determined by performing bulk RNA sequencing. Immunocytochemistry was performed to assess epithelial-mesenchymal transition (EMT). RESULTS: GzmB deficiency resulted in smaller fibrotic lesions in older mice and was associated with decreased levels of TSP-1 and increased levels of DCN within fibrotic lesions. It also led to increased MMT but reduced mast cell counts within fibrotic lesions, which was correlated with reduced photoreceptor cell death. In ARPE-19, exogenous application of GzmB impaired wound closure and promoted partial EMT by selectively modulating genes involved in transforming growth factor-β signaling, EMT, inflammation, angiogenesis and cell-cell interaction. CONCLUSIONS: Our study reveals that extracellular GzmB is a key contributor to subretinal fibrosis in nAMD, modulating inflammation, EMT and photoreceptor degeneration. These findings suggest GzmB as a promising therapeutic target for mitigating the development of subretinal fibrosis in nAMD.
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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".