Abstract
Idiopathic pulmonary fibrosis (IPF) is characterized by persistent fibroblast activation and progressive extracellular matrix remodeling, leading to irreversible lung architectural distortion. Although high-throughput omics approaches have advanced understanding of IPF pathogenesis, most studies have relied on single-omics analyses, limiting cross-layer functional interpretation. Here, we applied an integrated multi-omics strategy to characterize coordinated molecular alterations in IPF fibroblasts. Primary lung fibroblasts derived from patients with IPF and control subjects were analyzed using integrated transcriptomic, proteomic, and metabolomic profiling. Publicly available RNA-sequencing data deposited in the Gene Expression Omnibus (GEO; GSE301181) were used for transcriptomic analysis, while proteomic and metabolomic analyses were newly performed in a donor-matched subset of 10 IPF patients and 10 control subjects. Differentially expressed genes (DEGs), proteins (DEPs), and metabolites were identified using standardized statistical criteria, and cross-layer integration was conducted to identify molecules showing concordant regulation. Transcriptomic analysis identified 1,689 DEGs in IPF fibroblasts, whereas proteomic profiling initially quantified 6,236 proteins; after restricting analyses to peptide-supported proteins (≥2 unique peptides), 56 high-confidence DEPs were retained. Integration of transcriptomic and proteomic datasets identified 10 peptide-supported molecules exhibiting concordant regulation at both the mRNA and protein levels. Metabolomic profiling demonstrated significant reductions in metabolites involved in redox balance, lipid metabolism, glycolysis, nitrogen metabolism, and amine metabolism, indicating broad metabolic reprogramming associated with persistent fibroblast activation. Together, these findings suggest that IPF fibroblast activation is accompanied by coordinated transcriptional, translational, and metabolic reprogramming and highlight the value of integrated multi-omics analysis for interpreting regulatory features of fibrotic fibroblasts.
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