A Bioinformatics Approach to Identify Hub Genes Across Schizophrenia, Anxiety, Bipolar Disorder, and Depressive Disorder for Network-Based Drug Discovery

Abstract

Mental health disorders represent a significant challenge in society, requiring immediate attention and comprehensive knowledge to mitigate their widespread impacts. Although considerable research has focused on hub gene identification for one or two illnesses, there is a lack of literature examining multiple common disorders and their implications for drug discovery. This study utilizes a bioinformatics methodology to identify shared and critical genes linked to anxiety disorders, bipolar disorders, schizophrenia, and depressive disorders, along with potential therapeutic targets for these conditions. We methodically collected gene-related data from the National Center for Biotechnology Information (NCBI) for these disorders. Through protein-protein interaction analysis, we discovered hub genes, including GSK3B, MAPT, NR3C1, ESR1, TNF, SOD1, APP, CREB1, NOS1, APOE, GNB3, DISC1, SIRT1, CACNA1C, and BDNF. Additionally, we identified potential therapeutic agents targeting these hub genes, including Kaempferol, Simvastatin (CTD 00007319), Luteolin, Clozapine (CTD 00005693), Curcumin, Resveratrol, Melatonin (CTD 00006260), Felodipine, Apigenin, Docosahexaenoic Acid, Diazepam, and Alprazolam, using the DSigDB database. This study seeks to elucidate the genetic connections across mental health diseases and to find therapeutic compounds that may provide common treatment advantages.