Identification of marker genes and signaling pathways associated with amyotrophic lateral sclerosis using bioinformatics analysis of RNA sequencing data

Abstract

Abstract Amyotrophic lateral sclerosis (ALS), is a global disease that is a leading cause of neurodegenerative condition that affects motor neurons. However, the etiology of ALS remains poorly understood. The genes responsible for the pathogenesis of ALS have not been fully identified. The present study aimed to explore new genes of ALS by mining the ALS RNA sequencing data. RNA sequencing data (GSE277709) in the Gene Expression Omnibus (GEO) database were analysed to identify the differentially expressed genes (DEGs) (ALS vs. normal control) using bioinformatics methods. The DEGs were subjected to Gene Ontology (GO) functional enrichment and REACTOME pathway enrichment, and the protein-protein interaction (PPI) networks and functional modules were constructed to screen the hub genes. Then, the microRNAs (miRNAs) and transcription factors (TF) in ALS were screened out from the the miRNet and NetworkAnalyst database. Potential drug targets for ALS were obtained from the DrugBank database. MiRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network were constructed by Cytoscape software. Finally, receiver operating characteristic (ROC) curve assess the diagnostic value of hub genes. There exist strong correlations among samples of ALS and normal control group. There was a total of 958 DEGs, including 479 up-regulated genes and 479 down-regulated genes. GO were significantly enriched in multicellular organismal process, primary metabolic process, cell periphery, intracellular membraneless organelle, signaling receptor and transmembrane transporter activity. Enrichment Analysis of REACTOME indicated that the top pathways were extracellular matrix organization and sensory perception. Hub genes EGFR, FN1, CAV1, BCAR1, YAP1, POU5F1, TTYH1, ACTA1, GPR17 and TF were identified form PPI network and modules. The MiRNA-hub gene regulatory network and TF-hub gene regulatory network showed that hsa-miR-6874-5p, hsa-miR-561-5p, GATA2 and SRF might play an important role in the ALS. By analyzing drug-hub gene interaction network, we pridicted drug molecules such as Lormetazepam and Medazepam for ALS treatment. These hub demonstrated strong diagnostic values. The study highlights the potential impact of EGFR, FN1, CAV1, BCAR1, YAP1, POU5F1, TTYH1, ACTA1, GPR17 and TF on the development and progression of ALS, supporting their role as potential biomarkers.