Pulmonary fibrosis (PF), particularly idiopathic pulmonary fibrosis (IPF), is a progressive and often fatal interstitial lung disease characterised by complex genetic and molecular heterogeneity. Traditional diagnostic approaches, which rely on clinical, radiological and histopathological assessment, are frequently insufficient to capture the underlying biological diversity of the disease. The advent of next-generation sequencing (NGS) has substantially advanced the understanding of PF by enabling comprehensive genomic and transcriptomic profiling. NGS technologies, including whole-exome sequencing (WES), whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and targeted gene panels, have uncovered key genetic determinants. These include mutations in telomere-related genes (TERT, TERC, RTEL1) and surfactant-related genes (SFTPC, SFTPA2), as well as common variants like the MUC5B promoter polymorphism. These discoveries have clarified disease pathogenesis, revealed polygenic risk models, and may improve diagnostic accuracy, particularly in distinguishing overlapping interstitial lung disease (ILD) phenotypes. Beyond genetics, transcriptomic analyses have identified dysregulated pathways, including TGF-β, Wnt/β-catenin, and PI3K/Akt signalling, and have enabled the discovery of novel biomarkers for prognosis and therapeutic response. In selected clinical settings, NGS is beginning to support patient stratification and inform management decisions. Emerging applications, including liquid biopsy and integration with artificial intelligence, further expand the potential clinical utility of NGS. Despite challenges related to cost, data interpretation and standardisation, NGS represents a powerful research tool in PF.
Pagliaro et al. (Wed,) studied this question.
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