Plasma proteomics and machine learning deliver non-invasive distinction between fibrotic hypersensitivity pneumonitis and idiopathic pulmonary fibrosis.

WGCNA revealed significant enrichment of the glycolysis/gluconeogenesis and pyruvate metabolism pathways, implicating metabolic reprogramming in FHP pathogenesis.

Differential analysis identified nine differentially expressed proteins, from which a six-protein signature (H2BC12, SHBG, APCS, PTPRG, IGHV1-58, and GAPDH) was derived through LASSO regression and recursive feature elimination.

This model represents a promising non-invasive molecular tool for the differential diagnosis of atypical interstitial lung diseases.