Defining a natural killer cell-enriched molecular rejection-like state in lung transplant transbronchial biopsies
Bibliographic record
Abstract
In lung transplantation, antibody-mediated rejection (AMR) diagnosed using the International Society for Heart and Lung Transplantation criteria is uncommon compared with other organs, and previous studies failed to find molecular AMR (ABMR) in lung biopsies. However, understanding of ABMR has changed with the recognition that ABMR in kidney transplants is often donor-specific antibody (DSA)-negative and associated with natural killer (NK) cell transcripts. We therefore searched for a similar molecular ABMR-like state in transbronchial biopsies using gene expression microarray results from the INTERLUNG study (#NCT02812290). After optimizing rejection-selective transcript sets in a training set (N = 488), the resulting algorithms separated an NK cell-enriched molecular rejection-like state (NKRL) from T cell-mediated rejection (TCMR)/Mixed in a test set (N = 488). Applying this approach to all 896 transbronchial biopsies distinguished 3 groups: no rejection, TCMR/Mixed, and NKRL. Like TCMR/Mixed, NKRL had increased expression of all-rejection transcripts, but NKRL had increased expression of NK cell transcripts, whereas TCMR/Mixed had increased effector T cell and activated macrophage transcripts. NKRL was usually DSA-negative and not recognized as AMR clinically. TCMR/Mixed was associated with chronic lung allograft dysfunction, reduced one-second forced expiratory volume at the time of biopsy, and short-term graft failure, but NKRL was not. Thus, some lung transplants manifest a molecular state similar to DSA-negative ABMR in kidney and heart transplants, but its clinical significance must be established.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".