Introduction: Huntington's disease (HD) is a rare neurodegenerative disease characterized by progressive degeneration of neurons in the cerebral cortex and basal ganglia. HD is an autosomal dominant disorder caused by the expansion of CAG trinucleotide repeat in the Huntingtin gene (HTT) and defined by cognitive, psychiatric and motor disturbance. Although HD has been shown to have a genetic origin, its underlying cellular and molecular mechanisms are still not well understood and remain unclear to date. Therefore, early detection of HD by specific biomarkers can lead to earlier initiation of treatment programs, lifestyle modification and increase the patient's quality of life. Hence, this study was designed to identify the key genes and related pathways in HD.
Methods: The gene expression omnibus (GEO) available at https://www.ncbi.nlm.nih.gov/geo was used to obtain the gene expression profile of Huntington's disease (GSE1751) including 12 HD samples and 14 control samples. Screening and analysis of differentially expressed genes (DEGs) between HD and healthy controls were performed using R programming language. Genes with p-value < 0.05 and |logFC| ≥ 1.0 were considered as DEGs. The enrichment analysis of HD-related genes was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway using Enrichr (https://maayanlab.cloud/Enrichr). Additionally, the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://string-db.org/) was used to predict protein–protein interactions (PPI) network of identified DEGs. The PPI network visualization and analysis were employed using Cytoscape 3.9.0. The plug-in CytoHubba and degree centrality were applied to select 10 hub genes. MCODE was also used to distinguish top structural modules in the PPI network.
Results: In general, 404 genes were up-regulated and 1492 genes were down-regulated. GO biological process showed that DEGs are associated with proteasome-mediated ubiquitin-dependent protein catabolic process, cotranslational protein targeting to membrane, cytoplasmic translation, regulation of apoptotic process, and protein targeting to ER. GO Molecular function indicated a relationship between DEGs and RNA binding, nuclear receptor binding, cadherin binding, alpha-amylase activity, and nuclear import signal receptor activity. GO cellular components revealed that DEGs are related to intracellular membrane-bounded organelle, COPII-coated ER to Golgi transport vesicle, bounding membrane of organelle, cytoplasmic vesicle membrane, and nuclear inner membrane. KEGG pathway enrichment analysis demonstrated a relationship of DEGs with Coronavirus disease, Autophagy, Th17 cell differentiation, Ubiquitin mediated proteolysis, Pathways in cancer, Lipid and atherosclerosis, and Ribosome. A total of 1554 nodes and 14888 edges were involved in the PPI network. Based on degree, 10 genes including HSP90AA1, PTEN, JUN, HIST1H4F, SIRT1, FN1, SMARCA4, SUMO1, CASP3, and SRSF1 were referred as hub genes.
Conclusion: Based on key modules related to HD, PTEN, HIST1H4F, SIRT1, FN1, and SMARCA4 genes may have potential value in detecting and predicting HD progression. More experimental validations are needed for better understanding the role of these genes in HD.
Keywords: Huntington's disease, HD, Network-based analysis, Systems biology, Biomarker