Extreme Elevations of Donor-Derived Cell-Free DNA Increases the Risk of Chronic Lung Allograft Dysfunction and Death, Even Without Clinical Manifestations of Disease

BACKGROUND: Lung transplant recipients are traditionally monitored with pulmonary function testing (PFT) and lung biopsy to detect post-transplant complications and guide treatment. Plasma donor-derived cell free DNA (dd-cfDNA) is a novel molecular approach of assessing allograft injury, including subclinical allograft dysfunction. The aim of this study was to determine if episodes of extreme molecular injury (EMI) in lung transplant recipients increases the risk of chronic lung allograft dysfunction (CLAD) or death. METHODS: This multicenter prospective cohort study included 238 lung transplant recipients. Serial plasma samples were collected for dd-cfDNA measurement by shotgun sequencing. EMI was defined as a dd-cfDNA above the third quartile of levels observed for acute rejection (dd-cfDNA level of >= 5% occurring after 45 days post-transplant). EMI was categorized as Secondary if associated with co-existing acute rejection, infection or PFT decline; or Primary if not associated with these conditions. RESULTS: EMI developed in 16% of patients at a median 343.5 (IQR: 177.3-535.5) days post-transplant. Over 50% of EMI episodes were classified as Primary. EMI was associated with an increased risk of severe CLAD or death (HR: 2.78, 95% CI: 1.26-6.22, p = 0.012). The risk remained consistent for the Primary EMI subgroup (HR: 2.34, 95% CI 1.18-4.85, p = 0.015). Time to first EMI episode was a significant predictor of the likelihood of developing CLAD or death (AUC = 0.856, 95% CI = 0.805-0.908, p < 0.001). CONCLUSIONS: Episodes of EMI in lung transplant recipients are often isolated and may not be detectable with traditional clinical monitoring approaches. EMI is associated with an increased risk of severe CLAD or death, independent of concomitant transplant complications. (c) 2024 International Society for Heart and Lung Transplantation. All rights are reserved, including those for text and data mining, AI training, and similar technologies.