Selected article for: "confidence interval and gene expression"

Author: Weigt, S. Samuel; Wang, Xiaoyan; Palchevskiy, Vyacheslav; Li, Xinmin; Patel, Naman; Ross, David J.; Reynolds, John; Shah, Pali D.; Danziger-Isakov, Lara A.; Sweet, Stuart C.; Singer, Lianne G.; Budev, Marie; Palmer, Scott; Belperio, John A.
Title: Usefulness of gene expression profiling of bronchoalveolar lavage cells in acute lung allograft rejection
  • Cord-id: 55yzkch7
  • Document date: 2019_5_7
  • ID: 55yzkch7
    Snippet: BACKGROUND: Chronic lung allograft dysfunction (CLAD) is the main limitation to long-term survival after lung transplantation. Because effective therapies are lacking, early identification and mitigation of risk factors is a pragmatic approach to improve outcomes. Acute cellular rejection (ACR) is the most pervasive risk factor for CLAD, but diagnosis requires transbronchial biopsy, which carries risks. We hypothesized that gene expression in the bronchoalveolar lavage (BAL) cell pellet (CP) cou
    Document: BACKGROUND: Chronic lung allograft dysfunction (CLAD) is the main limitation to long-term survival after lung transplantation. Because effective therapies are lacking, early identification and mitigation of risk factors is a pragmatic approach to improve outcomes. Acute cellular rejection (ACR) is the most pervasive risk factor for CLAD, but diagnosis requires transbronchial biopsy, which carries risks. We hypothesized that gene expression in the bronchoalveolar lavage (BAL) cell pellet (CP) could replace biopsy and inform on mechanisms of CLAD. METHODS: We performed RNA sequencing on BAL CPs from 219 lung transplant recipients with A-grade ACR (n = 61), lymphocytic bronchiolitis (n = 58), infection (n = 41), or no rejection/infection (n = 59). Differential gene expression was based on absolute fold difference >2.0 and Benjamini-adjusted p-value ≤0.05. We used the Database for Annotation, Visualization and Integrated Discovery Bioinformatics Resource for pathway analyses. For classifier modeling, samples were randomly split into training (n = 154) and testing sets (n = 65). A logistic regression model using recursive feature elimination and 5-fold cross-validation was trained to optimize area under the curve (AUC). RESULTS: Differential gene expression identified 72 genes. Enriched pathways included T-cell receptor signaling, natural killer cell–mediated cytotoxicity, and cytokine–cytokine receptor interaction. A 4-gene model (AUC = 0.72) and classification threshold defined in the training set exhibited fair performance in the testing set; accuracy was 76%, specificity 82%, and sensitivity 60%. In addition, classification as ACR was associated with worse CLAD-free survival (hazard ratio = 2.42; 95% confidence interval = 1.29–4.53). CONCLUSIONS: BAL CP gene expression during ACR is enriched for immune response pathways and shows promise as a diagnostic tool for ACR, especially ACR that is a precursor of CLAD.

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