The Molecular Phenotype of Heart Transplant Biopsies: Relationship to Histopathological and Clinical Variables
Bibliographic record
Abstract
Histopathology of endomyocardial biopsies (EMB) is the standard rejection surveillance for heart transplants. However, ISHLT consensus criteria for interpreting biopsies are arbitrarily defined. Gene expression offers an independent re-evaluation of existing diagnostic systems. We performed histologic and microarray analysis on 105 EMB from 45 heart allograft recipients. Histologic lesions, diagnosis and transcripts were compared to one another, time posttransplantation, indication for biopsy and left ventricular ejection fraction (LVEF). Histologic lesions presented in two groups: myocyte-interstitial and microcirculation lesions. Expression of transcript sets reflecting T cell and macrophage infiltration, and γ-interferon effects correlated strongly with each other and with transcripts indicating tissue/myocardium injury. This molecular phenotype correlated with Quilty (p < 0.005), microcirculation lesions (p < 0.05) and decreased LVEF (p < 0.007), but not with the histologic diagnosis of rejection. In multivariate analysis, LVEF was associated (p < 0.03) with γ-interferon inducible transcripts, time posttransplantation, ischemic injury and clinically indicated biopsies, but not the diagnosis of rejection. The results indicate that (a) the current ISHLT system for diagnosing rejection does not reflect the molecular phenotype in EMB and lacks clinical relevance; (b) the interpretation of Quilty lesions has to be revisited; (c) the assessment of molecules in heart biopsy can guide improvements of current diagnostics.
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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 | 0.001 | 0.002 |
| 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".