Introduction: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive destruction of motor neurons. To date, there is no treatment to stop or slow the progression of the disease, and the diagnosis is mostly based on clinical symptoms. Identification of ALS biomarkers can be important for early diagnosis, especially in the early stages, as it can improve patients' quality of life and prolong survival. Therefore, this study aimed to discover the hub genes and important pathways associated with ALS.
Methods: A gene expression profile of Amyotrophic lateral sclerosis (GSE4595) was obtained from the gene expression omnibus (GEO) available at https://www.ncbi.nlm.nih.gov/geo. GSE4595 included 9 healthy controls and 11 ALS samples, which analyzed by R programming language to screen differentially expressed genes (DEGs) between ALS and normal samples. Genes with p-value < 0.05 and |logFC| ≥ 1.0 were considered as DEGs. Enrichment analysis of ALS-related genes was conducted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway using Enrichr available at https://maayanlab.cloud/Enrichr. The protein-protein interaction (PPI) network of identified DEGs was reconstructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://string-db.org/) and visualized by Cytoscape 3.9.0 software. CytoHubba plug-in and degree centrality were employed to identify 10 hub genes. Moreover, MCODE was used to identify top structural modules in the PPI network.
Results: A total of 676 DEGs were found after integrated analysis between ALS and normal samples. Among them, 501 were up-regulated and 175 were down-regulated. GO biological process demonstrated that DEGs are associated with chemical synaptic transmission, gluconeogenesis, signal release from synapse, neurotransmitter secretion, regulation of cation channel activity, cellular response to copper ion, and regulation of NMDA receptor activity. GO Molecular function indicated that DEGs are related to tubulin binding, calcium ion binding, metal ion binding, proton transmembrane transporter activity, phospholipase inhibitor activity, ATPase binding, oxidoreduction-driven active transmembrane transporter activity, and syntaxin-1 binding. GO cellular components showed a relationship between identified DEGs and neuron projection, axon, vesicle, dendrite, extracellular membrane-bounded organelle, proton-transporting V-type ATPase, V1 domain, and clathrin-coated vesicle membrane. Furthermore, KEGG pathway enrichment analysis showed an association between DEGs and Pathways of neurodegeneration, Alzheimer disease, Parkinson disease, Prion disease, Synaptic vesicle cycle, Huntington disease, Phagosome, and cGMP-PKG signaling pathway. In PPI network reconstruction, a total of 437 nodes and 1924 edges were existed. Based on degree, 10 genes including SNAP25, CYCS, SLC32A1, SNCA, GABRG2, SYT4, GABRA1, GAD2, GAP43, and ATP5A1 were selected as hub genes.
Conclusion: In this study, the crucial genes and pathways in ALS progression were identified. Based on top three modules related to ALS, SNAP25, CYCS, SLC32A1, SNCA, GABRG2, SYT4, GAD2, and ATP5A1 genes may have potential values for diagnosis and prognosis of ALS. Further experimental validation studies are needed to confirm these findings.
Keywords: Amyotrophic lateral sclerosis, ALS, Network-based analysis, Systems biology, Biomarker