Unique association of extreme elevation of cell free DNA and histologic patterns of intra-alveolar injury among lung transplant recipients - Zehra Dhanani; Omar Al Omari; Alonso Marquez; Kartik Shenoy; Fatima Anjum (JHLT Open)
Background: Donor-derived cell-free DNA (dd-cfDNA) is a valuable biomarker for allograft injury, but its association with various histopathologic injury patterns as specified in the Lung Allograft Standardized Histological Analysis (LASHA) protocol remains unclear. This study evaluates the relationship between various histopathologic findings as per the LASHA protocol, dd-cfDNA levels including extreme molecular injury (EMI), and allograft outcomes. Methods: We conducted a retrospective analysis of lung transplant recipients at a single center (2022-2024). A total of 84 patients with 589 dd-cfDNA samples were analyzed, with 124 samples having corresponding transbronchial biopsy (TBBX) and bronchoalveolar lavage (BAL) data. EMI was defined as dd-cfDNA > 5%. Multivariate regression analyses examined associations between histopathologic findings—including hemosiderin-laden macrophages (HLM) and organizing pneumonia (OP)—clinical comorbidities, EMI, and allograft outcomes. Results: EMI was observed in 29% of the cohort and was significantly associated with CLAD (p = 0.04), diabetes (p = 0.009), and elevated DSAs (p = 0.03). EMI was also more frequently detected in Black patients. On histopathology, OP was present in 11.2% of TBBX samples, while 8.9% had HLM. Patients with OP had significantly higher median dd-cfDNA levels compared to those without OP (p < 0.05) and exhibited lymphocytic-predominant BAL (p < 0.001). HLM was more prevalent in Black patients and in those with clinical or radiographic suspicion of OP, even in the absence of OP on histopathology. Conclusion: Our study highlights novel associations between dd-cfDNA, histopathologic findings, comorbidities, race, and allograft injury, emphasizing the need for personalized monitoring and risk stratification in lung transplantation and to explore mechanisms underlying the observed disparities.