ArticleJournal of translational medicine2020
Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage.
Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 14 citations in OpenAlex.
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- A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease.Bioinformatics and biology insights · 2023Article
- In silico gene expression and pathway analysis of DEK in the human brain across the lifespan.The European journal of neuroscience · 2022Article
- Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis.ACS omega · 2022Article
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Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuntington's disease (HD) is a neurodegenerative disorder characterized by psychiatric symptoms, serious motor and cognitive deficits. Certain pathological changes can already be observed in pre-symptomatic HD (pre-HD) patients; however, the underlying molecular pathogenesis is still uncertain and no effective treatments are available until now. Here, we reanalyzed HD-related differentially expressed genes from the GEO database between symptomatic HD patients, pre-HD individuals, and healthy controls using bioinformatics analysis, hoping to get more insight in the pathogenesis of both pre-HD and HD, and shed a light in the potential therapeutic targets of the disease.
methodsPre-HD and symptomatic HD differentially expressed genes (DEGs) were screened by bioinformatics analysis Gene Expression Omnibus (GEO) dataset GSE1751. A protein-protein interaction (PPI) network was used to select hub genes. Subsequently, Gene Ontology (GO) enrichment analysis of DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of hub genes were applied. Dataset GSE24250 was downloaded to verify our hub genes by the Kaplan-Meier method using Graphpad Prism 5.0. Finally, target miRNAs of intersected hub genes involved in pre-HD and symptomatic HD were predicted.
resultsA total of 37 and 985 DEGs were identified in pre-HD and symptomatic HD, respectively. The hub genes, SIRT1, SUZ12, and PSMC6, may be implicated in pre-HD, and the hub genes, FIS1, SIRT1, CCNH, SUZ12, and 10 others, may be implicated in symptomatic HD. The intersected hub genes, SIRT1 and SUZ12, and their predicted target miRNAs, in particular miR-22-3p and miR-19b, may be significantly associated with pre-HD.
conclusionThe PSMC6, SIRT1, and SUZ12 genes and their related ubiquitin-mediated proteolysis, transcriptional dysregulation, and histone metabolism are significantly associated with pre-HD. FIS1, CCNH, and their related mitochondrial disruption and transcriptional dysregulation processes are related to symptomatic HD, which might shed a light on the elucidation of potential therapeutic targets in HD.
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