Endothelial Activation, Quantified By Electron Microscopy Scoring or Multiplexed Gene Expression, Predicts Accelerated Graft Loss in Patients With Transplant Glomerulopathy.
Bibliographic record
Abstract
Transplant glomerulopathy (TG) is a sign of chronic kidney transplant damage with poor survival and no effective therapies. However, some patients with TG stay free of dialysis for years. There are significant limitations in the understanding of disease progression in TG. We aimed to explore genome-wide transcription profiles of TG and their relationship with ultrastructural changes in kidney biopsies and graft survival. The study included kidney allograft biopsies for cause from 40 patients with TG and post-transplant time matched 54 control patients without TG. We developed an electron microscopical (EM) scoring system to semi-quantify morphological profiles of microvascular endothelial cells of glomerular and peritubular capillaries (cytoplasmic swelling, loss of fenestrations, subendothelial widening, microvilli) and podocytes (cytoplasmic swelling, foot process effacement) and recorded an EM sum-score for endothelial cells and podocytes. The interobserver reproducibility of endothelial and podocyte EM scores were %99.2 and 99.1% respectively. A class comparison of microarrays showed 34 probe sets as higher in TG vs. non-TG, including 7 endothelial transcripts (i.e. DARC, VWF, MCAM, ICAM1) and 6 Fc receptor transcripts (i.e. FCGR3A,B, FCGR2A, FCGR1B), suggesting that endothelial activation and activating Fc receptors are involved in pathogenesis of TG. Microvascular endothelial EM sum-scores were higher in TG vs. non-TG biopsies and positively correlated with molecular disturbances, particularly transcripts reflecting endothelial activation, NK cell burden, and interferon-gamma effects (p<0.001). Podocyte EM sum-scores were not different between TG and non-TG. We stratified TG into 2 prognostic groups using either molecularly or electron microscopically defined endothelial activation: progressive TG kidneys with accelerated graft loss and non-progressive TG kidneys with no significant graft loss. In multivariate survival models, endothelial EM sum-score (p=0.007) and endothelial gene set expression (p=0.029) were independent prognostic factors after adjusting for clinical and pathological confounders (C4d, glomerular double contour cg-score, donor specific antibody, proteinuria, eGFR at time of biopsy, and interstitial fibrosis ci-score). Thus, increased renal endothelial activation seems related to disease progression in TG. Endothelial EM scoring or endothelial gene signatures can serve as predictive biomarkers in patients with TG.
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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".