Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33054835", "kind": "science-record", "revision": 7, "content_hash": "sha256:5add1945e456c3d5b0dfab56c8e1e9ec94096c1cea64669618ecab6976f1d72a", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:02:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage.", "doi": "10.1186/s12967-020-02549-9", "pmid": "33054835", "authors": ["Chunchen Xiang", "Shengri Cong", "Bin Liang", "Shuyan Cong"], "journal": "Journal of translational medicine", "year": 2020, "abstract": "BACKGROUND: Huntington'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.\nMETHODS: Pre-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.\nRESULTS: A 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.\nCONCLUSION: The 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.", "claims": [{"id": "claim-method", "statement": "The Kaplan–Meier method was used to determine the probability of survival in Graphpad Prism 5.0 for Windows.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33054835", "locator": "sections[7] \"Prediction of the miRNAs of the intersected hub genes and their validation\" paragraph 2", "quote": "The Kaplan–Meier method was used to determine the probability of survival in Graphpad Prism 5.0 for Windows."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Availability of data and materialsGSE1751 and GSE24250 datasets were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/)) [16, 55] and expression profiling arrays were generated using GPL96 (Affymetrix Human Genome U133 Plus 2.0 Array). R packages of “limma” (https://cran.r-project.org/), provided by a bioconductor project ( https://www.bioconductor.org/) [17], were applied to assess GSE1751 and GSE24250 RAW datasets. We applied online prediction tools utilizing Targetscan [21] (https://www.targetscan.org/vert_71/) and miRDB [22] (https://www.mirdb.org/), to predict potential microRNA targeting.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33054835", "locator": "sections[24] \"notes\" paragraph 1", "quote": "Availability of data and materialsGSE1751 and GSE24250 datasets were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/)) [16, 55] and expression profiling arrays were generated using GPL96 (Affymetrix Human Genome U133 Plus 2.0 Array). R packages of “limma” (https://cran.r-project.org/), provided by a bioconductor project ( https://www.bioconductor.org/) [17], were applied to assess GSE1751 and GSE24250 RAW datasets. We applied online prediction tools utilizing Targetscan [21] (https://www.targetscan.org/vert_71/) and miRDB [22] (https://www.mirdb.org/), to predict potential microRNA targeting."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33054835"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE1751"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE1751"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33054835", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12967-020-02549-9", "sha256": "sha256:e01835469af494ceded4316a9d7f066072f4154eea58bd059ff717ec3f1651f7", "bytes": 25724, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12967-020-02549-9", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7559361", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE1751", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1751", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE1751", "version": null, "note": "Availability of data and materialsGSE1751 and GSE24250 datasets were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/)) [16, 55] and expression profiling arrays were generated using GPL96 (Affymetrix Human Genome U133 Plus 2.0 Array). R packages of “limma” (https://cran.r-project.org/), provided by a bioconductor project ( https://www.bioconductor.org/) [17], were applied to assess GSE1751 and GSE24250 RAW datasets. We applied online prediction tools utilizing Targetscan [21] (https://www.targetscan.org/vert_71/) and miRDB [22] (https://www.mirdb.org/), to predict potential microRNA targeting.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Availability of data and materialsGSE1751 and GSE24250 datasets were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/)) [16, 55] and expression profiling arrays were generated using GPL96 (Affymetrix Human Genome U133 Plus 2.0 Array). R packages of “limma” (https://cran.r-project.org/), provided by a bioconductor project ( https://www.bioconductor.org/) [17], were applied to assess GSE1751 and GSE24250 RAW datasets. 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