Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease - Linh T. Ngo; Michaella J. Rekowski; Devin C. Koestler; Takafumi Yorozuya; Atsushi Saito; Imaan Azeem; Alexis Harrison; M. Kristen Demoruelle; Jonathan Boomer; Bryant R. England; Paul Wolters; Philip L. Molyneaux; et al. (ERJ Open Research)
Background Idiopathic interstitial pneumonias (IIPs), such as idiopathic pulmonary fibrosis and interstitial pneumonia with autoimmune features, present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF). Methods Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared with controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles that were then analysed to predict survival outcomes and investigate associated pathways. Results Proteomic profiling successfully differentiated IIP from controls. k-means clustering based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology index (concordance index 0.794 versus 0.709). The cluster with the worst prognosis featured decreased inflammatory signalling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B-cell-mediated immunity. Conclusions The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalised treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.