Transcriptome Classification Reveals Molecular Subgroups in Idiopathic Pulmonary Fibrosis

Abstract

Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. This study aimed to uncover the underlying molecular features for different types of IPF. IPF microarray datasets were retrieved from GEO databases. Weighted gene co-expression analysis (WGCNA) was used and identified subgroup-specific WGCNA modules. Infiltration-level immune cells in different subgroups of microenvironments were analyzed with CIBERSORT algorithms. The result is we classified 173 IPF cases into two subgroups based on gene expression profiles, which were retrieved from the GEO databases. The SGRQ score and age were significantly higher in C2 than in C1. Using WGCNA, five subgroup-specific modules were identified. M4 was mainly enriched by MAPK signaling, which was mainly expressed in C2; M1, M2, and M3 were mainly enriched by metabolic pathways and Chemokine signaling, and the pathway of M5 was phagosome inflammation; M1, M2, M3, and M5 were mainly expressed in C1. Utilizing the CIBERSORT, we showed that the number of M1 macrophage cells, CD8 T cells, regulatory T cells (Tregs), and Plasma cells was significantly different between C1 and C2. We found the molecular subgroups of IPF revealed that cases from different subgroups may have their unique patterns and provide novel information to understand the mechanisms of IPF itself.