Plasma proteomics reveals the molecular features in rapidly progressive pneumoconiosis.

BACKGROUND

Rapidly progressive pneumoconiosis (RPP) is an aggressive subtype of pneumoconiosis characterized by persistent pulmonary inflammation, rapidly progressive fibrosis, and early-onset progressive massive fibrosis. However, the systemic molecular alterations of RPP remain unclear. Here, we profiled the plasma proteome to identify candidate proteins associated with RPP, aiming to discover potential peripheral biomarkers for this aggressive phenotype.

METHODS

Plasma samples from 15 RPP patients and 13 non-RPP controls were analyzed by data-independent acquisition (DIA)-based proteomics. Differential expression analysis, protein-protein interaction network analysis, and random forest machine learning were performed for identifying RPP-associated proteins. Subsequently, the least absolute shrinkage and selection operator (LASSO) regression was applied to prioritize candidate biomarkers, whose associations with lung function were then evaluated using correlation analysis. Finally, the expression levels of these key proteins were validated in an independent cohort and a cell model using western blot and enzyme-linked immunosorbent assay.

RESULTS

A total of 74 differentially expressed proteins (DEPs) were identified in RPP compared to non-RPP. These DEPs were predominantly enriched in pathways involving macrophage activation, glycolysis/gluconeogenesis, complement and coagulation cascades, cytoskeletal reorganization, and neutrophil extracellular traps. Through DEPs-based screening, six proteins were identified as key molecules of RPP. Five of them showed significant correlations with lung function. The protein expressions of F11, CSTB, PSMB9, PRB4, and DLAT were validated in an independent cohort and crystalline silica-induced cell model.

CONCLUSIONS

This study provided a systematic plasma proteomic profiling of RPP, revealed coordinated alterations in immune, metabolic, and coagulation pathways, and identified a prioritized panel of candidate biomarkers for future validation. These findings constituted a foundational resource for elucidating the molecular architecture of RPP.