ArticleInternational journal of molecular sciences2023
Integrated Bioinformatics Analysis of Shared Genes, miRNA, Biological Pathways and Their Potential Role as Therapeutic Targets in Huntington's Disease Stages.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Decoding Non-Neuronal Mechanisms and Therapeutic Targets in Huntington's Disease Through Integrative Transcriptomics and Machine Learning.Journal of molecular neuroscience : MN · 2026Article
- Network-based integrative analysis of multi-level regulatory mechanisms associated with glyphosate exposure.Frontiers in bioinformatics · 2026Article
- In Silico Analysis of miRNA-Regulated Pathways in Spinocerebellar Ataxia Type 7.Current issues in molecular biology · 2025Article
- Role of TFEB in Huntington's Disease.Biology · 2024Review
- Mechanism and Therapeutic Prospect of miRNAs in Neurodegenerative Diseases.Behavioural neurology · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Huntington's Disease (HD) is a progressive neurodegenerative disease caused by CAG repeat expansion in the huntingtin gene (HTT). The HTT gene was the first disease-associated gene mapped to a chromosome, but the pathophysiological mechanisms, genes, proteins or miRNAs involved in HD remain poorly understood. Systems bioinformatics approaches can divulge the synergistic relationships of multiple omics data and their integration, and thus provide a holistic approach to understanding diseases. The purpose of this study was to identify the differentially expressed genes (DEGs), HD-related gene targets, pathways and miRNAs in HD and, more specifically, between the pre-symptomatic and symptomatic HD stages. Three publicly available HD datasets were analysed to obtain DEGs for each HD stage from each dataset. In addition, three databases were used to obtain HD-related gene targets. The shared gene targets between the three public databases were compared, and clustering analysis was performed on the common shared genes. Enrichment analysis was performed on (i) DEGs identified for each HD stage in each dataset, (ii) gene targets from the public databases and (iii) the clustering analysis results. Furthermore, the hub genes shared between the public databases and the HD DEGs were identified, and topological network parameters were applied. Identification of HD-related miRNAs and their gene targets was obtained, and a miRNA-gene network was constructed. Enriched pathways identified for the 128 common genes revealed pathways linked to multiple neurodegeneration diseases (HD, Parkinson's disease, Spinocerebellar ataxia), MAPK and HIF-1 signalling pathways. Eighteen HD-related hub genes were identified based on network topological analysis of MCC, degree and closeness. The highest-ranked genes were
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