Unbiased Proteomics Analysis Shows Distinct Graft Protein Expression in Donor-Specific Antibodies (DSA+) Kidney Transplant Recipients with Antibody-Mediated Rejection
Bibliographic record
Abstract
Background: Nearly 1,000,000 North Americans have end-stage renal disease (ESRD), where the kidneys no longer function. Transplantation is the best treatment for ESRD; however, 50% of grafts fail by 10 years, due mainly to antibody-mediated rejection (ABMR), where recipient donor-specific antibodies (DSA) are thought to drive tissue injury. Unfortunately, predicting ABMR onset is challenging, as 30-60% of DSA+ transplant patients do not develop ABMR. We aim to identify factors that regulate kidney protein expression in DSA+ kidney transplant recipients with and without ABMR. Methods: Glomeruli and tubulointerstitium isolated from DSA+ABMR (n=24) and DSA+ no ABMR (NA; n=21) kidney biopsies using laser capture microdissection were digested to peptides and analyzed by liquid chromatography mass spectrometry. MaxQuant and Perseus software were used to assess protein identification and differential expression. Significantly differentially expressed proteins (t-test, p<0.05) were then mapped to signaling pathways using the pathDIP database (FDR with Benjamini Hochberg adjustment, q<0.05). Results: 120 glomerular and 246 tubulointerstitial proteins were significantly differentially expressed between DSA+ABMR and DSA+NA patients, with 55% of these proteins upregulated in ABMR (Figure 1). pathDIP analysis showed that upregulated proteins mapped significantly to pathways involving the immune system (glomeruli, q=7.6e-8; tubulointerstitium, q=3.8e-11), antigen processing (glomeruli, q=5.6e-11) and integrin activity (tubulointerstitium, q=1.0e-8), while downregulated proteins mapped to tight junction regulation (glomeruli, q= 1.0e-3) and cellular metabolism (tubulointerstitium, q=1.8e-9).Fig1.: Differentially expressed (p<0.05) proteins in the glomeruli (left) and tubulointerstitium (right) of DSA+ kidney transplant recipients with vs without ABMR.Conclusions: Our preliminary results suggest that ABMR in DSA+ patients is strongly linked to dysregulated immune and cellular responses in multiple kidney tissues. These findings will ultimately help us identify novel targets for the development of therapeutics for kidney transplant recipients. Funding: Government Support - Non-U.S.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".