Transcriptome Classification Reveals Molecular Subgroups in Idiopathic Pulmonary Fibrosis

Area of Science:

• Pulmonary Medicine
• Molecular Biology
• Immunology

Background:

• Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with high mortality.
• Understanding IPF heterogeneity is crucial for targeted therapies.

Purpose of the Study:

• To identify molecular subgroups within IPF.
• To characterize the distinct molecular and immune features of these subgroups.

Main Methods:

• Analysis of IPF microarray datasets from GEO.
• Weighted Gene Co-expression Network Analysis (WGCNA) to identify gene modules.
• CIBERSORT algorithm to analyze immune cell infiltration.

Main Results:

• 173 IPF cases classified into two molecular subgroups (C1 and C2).
• Subgroup C2 exhibited higher SGRQ scores and age.
• Distinct WGCNA modules (MAPK signaling in C2; metabolic, chemokine, phagosome pathways in C1).
• Significant differences in M1 macrophages, CD8 T cells, Tregs, and plasma cells between subgroups.

Conclusions:

• Molecular subgrouping of IPF reveals unique patterns.
• Provides novel insights into IPF mechanisms.
• Potential for subgroup-specific therapeutic strategies.