Proteomics Reveals Extracellular Matrix Injury in the Glomeruli and Tubulointerstitium of Kidney Allografts with Early Antibody-Mediated Rejection
Bibliographic record
Abstract
Background: Antibody-mediated rejection (AMR) accounts for >50% of kidney allograft losses. AMR is caused by donor-specific antibodies (DSA) against HLA antigens in the glomeruli and the tubulointerstitium, which together with interferon-γ and tumor necrosis factor-α (TNFα), trigger graft injury. The reasons behind cell-specific injury in AMR remain unclear. Identifying compartment-specific proteome alterations may help uncover mechanisms of early antibody-mediated injury. Methods: We studied 30 for-cause kidney biopsies with early AMR, acute cellular rejection (ACR) or acute tubular necrosis (ATN). We laser-captured microdissected glomeruli and tubulointerstitium and subjected them to unbiased proteome analysis. Results: We found 107 glomerular and 112 tubulointerstitial proteins significantly differentially expressed in AMR vs ACR (p<0.05). Similarly, 112 (glomeruli) and 124 (tubulointerstitium) proteins were altered in AMR vs ATN. Basement membrane and extracellular matrix (ECM) proteins were decreased in both compartments in AMR, compared to ACR and ATN. We verified decreased glomerular and tubulointerstitial LAMC1 expression, and decreased glomerular NPHS1 and PTPRO expression in AMR. Cathepsin-V (CTSV) was predicted to cleave ECM-proteins in the AMR glomeruli. We identified galectin-1, an immunomodulatory protein increased in AMR glomeruli and linked to the ECM. An external dataset (GSE36059) also demonstrated increased galectin-1 expression in AMR. Anti-HLA class-I antibodies induced inflammation and significantly increased CTSV expression, and galectin-1 expression and secretion, in human glomerular endothelial cells. We also studied GSTO1, an ECM-modifying enzyme, increased in the AMR tubulointerstitium. GSTO1 expression was significantly increased in TNFα-treated proximal tubular epithelial cells. Conclusions: Basement membranes are often remodeled in chronic AMR, and we demonstrated that this remodeling begins early in glomeruli and tubulointerstitium. ECM-remodeling in AMR may represent a new therapeutic target.
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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 | 0.001 | 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) | 0.001 | 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".