Development and Validation of a Bronchoalveolar Lavage Genomic Classifier for Acute Cellular Rejection

Background: Acute cellular rejection (ACR) is the main risk factor for chronic lung allograft dysfunction (CLAD), but diagnosis requires invasive transbronchial biopsy (TBB). We previously demonstrated the feasibility of bronchoalveolar lavage cell pellet (BAL-cp) gene expression for ACR diagnosis. We sought to develop and validate a genomic classifier for ACR in a multicenter cohort.
Methods: We performed RNA-seq on 806 BAL-cp from 181 lung transplant recipients enrolled in CTOT-20. Differential expression was based on fold difference >2.0 and False Discovery adjusted p-value <0.05. Samples were randomly split 80:20 into training and testing sets. A Random Forest model was optimized for area under the curve (AUC), and the threshold for genomic ACR was selected for classification accuracy. We validated performance in an independent single-center cohort. Cox models evaluated risk for CLAD.
Findings: From 37 cases and 151 controls, we identified 62 ACR genes, indicating upregulation of T-cell receptor signaling, and downregulation of CTLA4 signaling in cytotoxic lymphocytes, among other enriched pathways. A 31-gene Random Forest model’s AUC was 0.99 (SE 0.0053) in the training set, and 0.72 (SE 0.0874) in the test set. At a probability threshold of 0.396, accuracy for distinguishing clinically significant ACR cases from stable controls was 93.1% (specificity 95.4%, sensitivity 83.8%). In the independent validation cohort, accuracy was 82.1% (specificity 87.5%, sensitivity 73.3%). The model classified 138 (17.1%) CTOT-20 samples as genomic ACR. Late genomic ACR (≥90 days posttransplant) associated with increased CLAD risk (HR 2.52, 95% CI 1.47 - 4.34, p<0.001).
Interpretation: A BAL-cp genomic classifier can identify ACR, predict CLAD risk, and may be a less invasive alternative to TBB after lung transplant.