Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis.

ABSTRACT:

Background

Considerable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow for a biomarker-driven personalised medicine approach. We aimed to identify clinically distinct groups of patients with IPF that could represent distinct disease endotypes.

Methods

We co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier w

SUBMITTER: Kraven LM 

PROVIDER: S-EPMC9643664 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature