Identification and analysis of biomarkers involved in Multiple Sclerosis (MS) by bioinformatics tools
Identification and analysis of biomarkers involved in Multiple Sclerosis (MS) by bioinformatics tools
AmirReza Homaei ,1,*
1. Cancer Research center, Shahid Beheshti University of Medical Science, Tehran, Iran
Introduction: Multiple sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system, leading to progressive disability. The global prevalence of MS has been rising, with over 2.8 million people affected worldwide. The disease presents significant challenges due to its complex etiology and varied clinical presentations. Bioinformatic analysis is crucial for identifying potential biomarkers that could aid in early diagnosis and personalized treatment approaches, addressing the unmet needs in MS management.
Methods: The dataset GSE21942 was downloaded from the GEO database. Subsequently, analyses were performed on the samples within the dataset using both the GEO2R tool and R programming. Up-regulated and down-regulated genes were identified based on GEO2R and R analysis (adjpval < 0.05). A Venn diagram was then created to determine common genes between GEO2R and R results for both up-regulated and down-regulated genes.
Then these common genes analyzed using the Enrichr database to determine associated biological processes, KEGG pathways and related diseases.
Next, the identified up-regulated and down-regulated genes were imported into Cytoscape for centrality analysis, leading to the identification of hub genes
Results: The results obtained from the Enrichr database, based on the highest p-value significance, are as follows:
Up-regulated genes:
Biological Process: B Cell Receptor Signaling Pathway, Antigen Receptor-Mediated Signaling Pathway, Hydrogen Peroxide Catabolic Process, Amyloid Fibril Formation, Oxygen Transport, Carbon Dioxide Transport, Antibacterial Humoral Response, Gas Transport, Regulation Of B Cell Activation.
Related Disease: Hemoglobinopathies, Chronic Lymphocytic Leukemia, Burkitt Lymphoma, Leukemia, Precursor B-cell Lymphoblastic Leukemia, B-Cell Lymphomas, Immunologic Deficiency Syndromes.
KEGG Pathway: B Cell Receptor Signaling Pathway, Hematopoietic Cell Lineage, Transcriptional Misregulation in Cancer, Epstein-Barr Virus Infection, Primary Immunodeficiency, NOD-like Receptor Signaling Pathway, RNA Transport.
Down-regulated genes:
Biological Process: Regulation Of Apoptotic Process, Regulation Of Protein Autophosphorylation, Regulation Of ERK1 And ERK2 Cascade, Regulation Of Cell Communication By Electrical Coupling, Regulation Of Innate Immune Response, Positive Regulation Of Peptidyl-Threonine Phosphorylation.
Related Disease: Tuberculosis, Neoplasm Metastasis, Lymphoma, Sjogren's Syndrome, Multiple Sclerosis, Lung Carcinoma, IGA Glomerulonephritis, Post-Traumatic Stress Disorder, Inflammatory Bowel Diseases.
KEGG Pathway: Neurotrophin Signaling Pathway, Necroptosis, Tuberculosis, Lipid and Atherosclerosis, Hepatitis B, Natural Killer Cell-Mediated Cytotoxicity, Pertussis, Antigen Processing and Presentation, MAPK Signaling Pathway, D-Glutamine and D-Glutamate Metabolism.
The hub genes identified in Cytoscape were as follows:
Up-regulated genes: CD19, JUN, BRD4, CXCL8, ATRX.
Down-regulated genes: TP53, ACTB, IFNG, CALM3, SRSF1, HNRNPH1, CANX, LAMP1.
Conclusion: The analysis reveals enhanced immune activation and disrupted signaling pathways in MS, with up-regulation of key immune-related genes and down-regulation of genes involved in cellular stress and neuronal survival. These findings suggest critical targets for potential therapeutic interventions.