Abstract
BackgroundGene expression data provide invaluable insights into disease mechanisms. In Huntington’s disease (HD), a neurodegenerative disease caused by a tri-nucleotide repeat expansion in the huntingtin gene, extensive transcriptional dysregulation has been reported. Conventional dysregulation analysis has shown that e.g. in the caudate nucleus of the post mortem HD brain the gene expression level of about a third of all genes was altered. Owing to this large number of dysregulated genes, the underlying relevance of expression changes is often lost in huge gene lists that are difficult to comprehend.MethodsTo alleviate this problem, we employed weighted correlation network analysis to archival gene expression datasets of HD post mortem brain regions.ResultsWe were able to uncover previously unidentified transcription dysregulation in the HD cerebellum that contained a gene expression signature in common with the caudate nucleus and the BA4 region of the frontal cortex. Furthermore, we found that yet unassociated pathways, e.g. global mRNA processing, were dysregulated in HD. We provide evidence to show that, contrary to previous findings, mutant huntingtin is sufficient to induce a subset of stress response genes in the cerebellum and frontal cortex BA4 region. The comparison of HD with other neurodegenerative disorders showed that the immune system, in particular the complement system, is generally activated. We also demonstrate that HD mouse models mimic some aspects of the disease very well, while others, e.g. the activation of the immune system are inadequately reflected.ConclusionOur analysis provides novel insights into the molecular pathogenesis in HD and identifies genes and pathways as potential therapeutic targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-014-0060-2) contains supplementary material, which is available to authorized users.
Highlights
Gene expression data provide invaluable insights into disease mechanisms
Weighted correlation network construction using Weighted gene correlation network analysis (WGCNA) in the Huntington’s disease (HD) dataset For a more detailed explanation of the WGCNA package, the interested reader is referred to the original publication [29] or the WGCNA homepage: http://labs.genetics.ucla. edu/horvath/CoexpressionNetwork
We compared well studied HD mouse models to the human gene expression dataset, which implied that whilst the mouse models mimic some aspects of the disease very well, certain aspects, for example induction of the inflammatory response, were only poorly reflected
Summary
Gene expression data provide invaluable insights into disease mechanisms. In Huntington’s disease (HD), a neurodegenerative disease caused by a tri-nucleotide repeat expansion in the huntingtin gene, extensive transcriptional dysregulation has been reported. Huntington’s disease (HD) belongs to the group of polyglutamine (polyQ) repeat expansion diseases, which together comprise the most common form of inherited neurodegenerative disorders [1]. It can be categorized as a proteinopathy, a disorder in which abnormally folded proteins cause disease by loss- and/or gain-of-function mechanisms. Other diseases that are not associated with misfolded proteins can result in major neurodegeneration Amongst these are brain tumors, e.g. gangliogliomas (GG) [7], which arises from brain ganglion cells, and inflammatory diseases such as multiple sclerosis (MS) which can result in a massive loss of neurons [8]. There is evidence that even very heterogeneous mental illnesses, such as schizophrenia (SCHIZ) are at least partly associated with neurodegeneration [9]
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