In Silico Analysis of Pulmonary Arterial Hypertension to İdentify Key Biomarkers at Protein and RNA Levels

Abstract Background Pulmonary arterial hypertension (PAH) is a chronic cardiopulmonary disorder marked by a raised hypertension in the pulmonary arteries. There is no remedy for PAH, existing medications can help to reduce the disease’s progression. The goal of this research was to investigate potential protein and RNA biomarkers of PAH by bioinformatic analysis. Methods Two PAH datasets accessed from the publicly available Gene Expression Omnibus (GEO) database were utilized to discover differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for common DEGs were conducted by the DAVID tool. Cytoscape was used to create the protein-protein interaction (PPI) and pick the top 10 hub genes. The transcription factors (TFs) and microRNAs (miRNAs) that target DEGs and hub genes were investigated using the JASPAR database. Potential therapeutics that target the top hub genes have been discovered. Results Ten hub genes were discovered to be linked to the pathogenesis of PAH (CCL5, TLR4, TLR1, SPP1, CYBB, HGF, IGF1, SELL, CD163 and POSTN). “Positive regulation of tumor necrosis factor biosynthetic process” and a “toll-like receptor signaling pathway” are the most enriched GO term and KEGG pathway, respectively. “hsa-mir-26b-5p, hsa-mir-146a-5p, hsa-mir-335-5p” and FOXC1, YY1, GATA2 are the top TFs targeting hub genes. 21 drugs targeting ten hub genes have been discovered. Conclusions Our results would help to discover the pathogenesis of PAH and hub genes, miRNAs and 10 TFs that might serve as potential therapeutic targets at protein and RNA levels for PAH patients.