Immune gene correlation networks differentiate both chronic lung allograft dysfunction and survival.

Chronic lung allograft dysfunction (CLAD) is the major barrier for long-term survival in lung transplant recipients (LTRs). CLAD remains a diagnosis of exclusion with poor responses to therapies. A molecular diagnostic for CLAD is needed to risk-stratify LTRs for prognosis and identify new targets to mitigate CLAD progression. We used weighted gene correlation network analysis on the airway brush-derived airway transcriptome to identify immune pathways and markers relevant to CLAD. Weighted gene correlation network analysis was performed on RNA sequencing from airway brushings of 37 LTRs with CLAD compared with 37 stable LTRs. We analyzed gene coexpression networks (modules) for their biological significance and association with CLAD. Three gene modules were positively correlated with CLAD, its severity, allograft dysfunction, and survival. These enriched components of the acute phase response, type 1 adaptive immunity, and innate immunity, respectively. A fourth module correlated with protection and was inversely correlated with the other modules. We validated our findings by identification of downstream protein and eicosanoid levels in the bronchoalveolar lavage, and an external validation cohort where module expression differentiated LTRs with CLAD and correlated with worse survival. The CLAD airway transcriptome enriches for coexpression networks associated with network modules that correlate with allograft dysfunction and survival.