Clinical omics-based biomarker identification for precision medicine targeting idiopathic pulmonary fibrosis

Abstract

Biomarkers hold great promise for advancing precision medicine, particularly in the areas of diagnosis, prognosis, and therapy. In the context of precision medicine, the identification of appropriate biomarkers is essential for achieving disease-specific therapeutic interventions. Since the biomarkers enable early disease diagnosis and offer predictive insights into therapeutic outcomes, ideal biomarkers should reflect the underlying disease states. Additionally, clinical data-based approaches are necessary to address the limitations of translation from preclinical research into clinical practice. Herein, we aim to demonstrate clinical omics-based biomarker identification and validation of its role in idiopathic pulmonary fibrosis (IPF), a chronic and irreversible lung disease. We used both bulk and single-cell RNA sequencing data from 13 and 5 cohorts, respectively. Differentially expressed gene (DEG) analysis was performed on bulk RNA sequencing data to identify genes co-upregulated across all cohorts. Subsequently, we identified cell-type-specific gene expression and predicted its role using single-cell RNA sequencing data. Mechanistically, its role was further validated in a human cell line using siRNA-mediated gene knockdown. Consequently, our findings revealed a novel biomarker involved in the regulation of IPF pathogenesis. This approach may serve as the identification of clinically relevant biomarkers.