Investigation on epigenomic signature for chronic obstructive pulmonary disease - an in silico approach

Chronic obstructive pulmonary disease is an advanced and debilitating respiratory condition characterized by chronic inflammation and airflow constraint. Despite its global prevalence, precise diagnostic and prognostic biomarkers remain unidentified. This research aims to identify potential epigenomic biomarkers for pulmonary disease by integrating DNA methylation and differential gene expression analyses. Publicly available datasets were utilized, ‘R’ programming was used for the differential methylation analysis to identify significantly differentially methylated regions, and gene expression analysis was performed in ‘R’, revealing differentially expressed genes associated with this disease. Functional enrichment and pathway analyses were carried out using the DAVID bioinformatics tool, and Reactome revealed the key biological processes and pathways involved in pulmonary disease pathogenesis. Additionally, protein-protein interaction networks were constructed utilizing a string database to recognize hub genes with potential therapeutic relevance. Our research work provides an understanding of the epigenetic landscape of pulmonary disease, identifying 8 candidate epigenomic biomarkers that could aid as diagnostic tools or therapeutic targets. Gene ontology and protein-protein interaction show the disease mechanism and pathways, showing the efficiency of the biomarker in pulmonary disease. This integrative approach not only advances the understanding of pulmonary disease molecular underpinnings but also paves the way for personalized treatment strategies.