Background Idiopathic interstitial pneumonias (IIPs) such as idiopathic pulmonary fibrosis (IPF) and interstitial pneumonia with autoimmune features (IPAF), 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 to controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles which were then analyzed 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 (GAP) index (C-index 0.794 vs. 0.709). The cluster with the worst prognosis featured decreased inflammatory signaling 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 personalized 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.

The authors have declared no competing interest.

SMM, LTN, DCK and this work were supported by P20GM130423. The proteomics data were collected in the Mass Spectrometry and Proteomics Core facility utilizing the Orbitrap Ascend Tribrid System that was purchased with funds provided by the University of Kansas Cancer Center, which is supported by the National Cancer Institute Cancer Center Support Grant P30 CA168524.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Institutional Review Board of Sapporo Medical University Hospital approved this study (No. 342 201, approved on 02/09/2023).

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Funding: SMM, LTN, DCK and this work were supported by P20GM130423.

The proteomics data were collected in the Mass Spectrometry and Proteomics Core facility utilizing the Orbitrap Ascend Tribrid System that was purchased with funds provided by the University of Kansas Cancer Center, which is supported by the National Cancer Institute Cancer Center Support Grant P30 CA168524.

All data available upon reasonable request to authors