Bioinformatic Gene Analysis for Potential Therapeutic Targets of Huntington's Disease in Pre-symptomatic and Symptomatic Stage

Overview

Journal J Transl Med

Publisher Biomed Central

Specialties Biomedical Engineering
General Medicine

Date 2020 Oct 15

PMID 33054835

Citations 8

Authors

Chunchen Xiang

Shengri Cong

Bin Liang

Shuyan Cong

Affiliations

Soon will be listed here.

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.

Methods: 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.

Results: 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.

Conclusion: 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.

Citing Articles

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References

Kim Y, Liu T, Koul D, Tiao N, Feroze A, Wang J . Identification of novel synergistic targets for rational drug combinations with PI3 kinase inhibitors using siRNA synthetic lethality screening against GBM. Neuro Oncol. 2011; 13(4):367-75. PMC: 3064700. DOI: 10.1093/neuonc/nor012. View

Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A . STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 2012; 41(Database issue):D808-15. PMC: 3531103. DOI: 10.1093/nar/gks1094. View

De Preter K, Vermeulen J, Brors B, Delattre O, Eggert A, Fischer M . Accurate outcome prediction in neuroblastoma across independent data sets using a multigene signature. Clin Cancer Res. 2010; 16(5):1532-41. DOI: 10.1158/1078-0432.CCR-09-2607. View

Barrett T, Wilhite S, Ledoux P, Evangelista C, Kim I, Tomashevsky M . NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 2012; 41(Database issue):D991-5. PMC: 3531084. DOI: 10.1093/nar/gks1193. View

Wiatr K, Szlachcic W, Trzeciak M, Figlerowicz M, Figiel M . Huntington Disease as a Neurodevelopmental Disorder and Early Signs of the Disease in Stem Cells. Mol Neurobiol. 2017; 55(4):3351-3371. PMC: 5842500. DOI: 10.1007/s12035-017-0477-7. View

Sinha M, Ghose J, Das E, Bhattarcharyya N . Altered microRNAs in STHdh(Q111)/Hdh(Q111) cells: miR-146a targets TBP. Biochem Biophys Res Commun. 2010; 396(3):742-7. DOI: 10.1016/j.bbrc.2010.05.007. View

Reed E, Latourelle J, Bockholt J, Bregu J, Smock J, Paulsen J . MicroRNAs in CSF as prodromal biomarkers for Huntington disease in the PREDICT-HD study. Neurology. 2017; 90(4):e264-e272. PMC: 5798654. DOI: 10.1212/WNL.0000000000004844. View

Tang Q, Len Q, Liu Z, Wang W . Overexpression of miR-22 attenuates oxidative stress injury in diabetic cardiomyopathy via Sirt 1. Cardiovasc Ther. 2017; 36(2). DOI: 10.1111/1755-5922.12318. View

Rai A, Vargas M, Wang L, Andersen E, Miller E, Simon J . Elements of the polycomb repressor SU(Z)12 needed for histone H3-K27 methylation, the interface with E(Z), and in vivo function. Mol Cell Biol. 2013; 33(24):4844-56. PMC: 3889545. DOI: 10.1128/MCB.00307-13. View

10.

Fusilli C, Migliore S, Mazza T, Consoli F, De Luca A, Barbagallo G . Biological and clinical manifestations of juvenile Huntington's disease: a retrospective analysis. Lancet Neurol. 2018; 17(11):986-993. DOI: 10.1016/S1474-4422(18)30294-1. View

11.

Moslehi R, Mills J, Signore C, Kumar A, Ambroggio X, Dzutsev A . Integrative transcriptome analysis reveals dysregulation of canonical cancer molecular pathways in placenta leading to preeclampsia. Sci Rep. 2013; 3:2407. PMC: 3757356. DOI: 10.1038/srep02407. View

12.

Liu M, Xu Z, Du Z, Wu B, Jin T, Xu K . The Identification of Key Genes and Pathways in Glioma by Bioinformatics Analysis. J Immunol Res. 2018; 2017:1278081. PMC: 5736927. DOI: 10.1155/2017/1278081. View

13.

Liu H, Liu N, Zhao Y, Zhu X, Wang C, Liu Q . Oncogenic USP22 supports gastric cancer growth and metastasis by activating c-Myc/NAMPT/SIRT1-dependent FOXO1 and YAP signaling. Aging (Albany NY). 2019; 11(21):9643-9660. PMC: 6874452. DOI: 10.18632/aging.102410. View

14.

van Roon-Mom W, Reid S, Jones A, MacDonald M, Faull R, Snell R . Insoluble TATA-binding protein accumulation in Huntington's disease cortex. Brain Res Mol Brain Res. 2003; 109(1-2):1-10. DOI: 10.1016/s0169-328x(02)00450-3. View

15.

Labbadia J, Morimoto R . Huntington's disease: underlying molecular mechanisms and emerging concepts. Trends Biochem Sci. 2013; 38(8):378-85. PMC: 3955166. DOI: 10.1016/j.tibs.2013.05.003. View

16.

Dong X, Tsuji J, Labadorf A, Roussos P, Chen J, Myers R . The Role of H3K4me3 in Transcriptional Regulation Is Altered in Huntington's Disease. PLoS One. 2015; 10(12):e0144398. PMC: 4670094. DOI: 10.1371/journal.pone.0144398. View

17.

Zou Q, Tang Q, Pan Y, Wang X, Dong X, Liang Z . MicroRNA-22 inhibits cell growth and metastasis in breast cancer via targeting of SIRT1. Exp Ther Med. 2017; 14(2):1009-1016. PMC: 5526179. DOI: 10.3892/etm.2017.4590. View

18.

Schmitges F, Prusty A, Faty M, Stutzer A, Lingaraju G, Aiwazian J . Histone methylation by PRC2 is inhibited by active chromatin marks. Mol Cell. 2011; 42(3):330-41. DOI: 10.1016/j.molcel.2011.03.025. View

19.

Ho D, Calingasan N, Wille E, Dumont M, Beal M . Resveratrol protects against peripheral deficits in a mouse model of Huntington's disease. Exp Neurol. 2010; 225(1):74-84. DOI: 10.1016/j.expneurol.2010.05.006. View

20.

Liang J, Fang Z, Huang Y, Liuyang Z, Zhang X, Wang J . Application of Weighted Gene Co-Expression Network Analysis to Explore the Key Genes in Alzheimer's Disease. J Alzheimers Dis. 2018; 65(4):1353-1364. PMC: 6218130. DOI: 10.3233/JAD-180400. View