Insights from cerebellar transcriptomic analysis into the pathogenesis of ataxia.
Insights from cerebellar transcriptomic analysis into the pathogenesis of ataxia.
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DOI：
10.1001/jamaneurol.2014.756
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发表时间：
2014-07-01
期刊：
影响因子：
29
通讯作者：
Houlden, Henry
中科院分区：
文献类型：
--
作者：
Bettencourt, Conceicao;Ryten, Mina;Forabosco, Paola;Schorge, Stephanie;Hersheson, Joshua;Hardy, John;Houlden, Henry
常染色体显性遗传性脊髓小脑共济失调（SCA）的核心临床和神经病理特征是小脑变性。已知基因的突变只能解释50%到60%的SCA病例。到目前为止，还没有有效的治疗方法，药物治疗的分子途径的知识是有限的。重叠机制的检查和共济失调基因如何相互作用的解释将是重要的发现潜在的疾病修饰剂。为了解决已知SCA基因之间的可能关系，预测它们的功能，确定重叠的途径，并提供一个框架，候选基因发现使用全转录组表达数据。我们使用了基于全转录组基因表达分析的系统生物学方法。作为英国脑表达联盟的一部分，我们分析了从101名神经病理学健康个体（每个个体10个不同的脑区域）获得的788个脑样本的表达谱。采用加权基因共表达网络分析方法，以无监督方式将24个SCA基因聚类为基因共表达模块。在小脑中确定的模块中SCA转录的过度表达进行了评估。进行富集分析以推断生物学相关模块中基因的功能和分子途径。涉及SCA基因的分子功能和机制，以及作为新SCA致病或修饰基因的潜在候选者的相关共表达基因的列表。两个小脑基因共表达模块在统计学上富集了SCA转录本（棕褐色模块P = 0.021，浅黄色模块P = 2.87 × 10−5），并分别含有已建立的颗粒和浦肯野细胞标记。一个模块包括参与遍在蛋白-蛋白酶体系统的基因，并包含通常与复杂表型相关的SCA基因，而另一个模块包含许多对钙稳态和信号传导重要的基因，并包含主要与纯共济失调相关的SCA基因。利用人脑中的正常基因表达，我们确定了SCA发病机制中的重要细胞类型和途径。参与钙稳态和信号传导的基因的过度表达可能预示着未来治疗的重要靶点。此外，基因网络为共济失调提供了新的候选基因，或可能对小脑功能至关重要的新基因。
The core clinical and neuropathological feature of the autosomal dominant spinocerebellar ataxias (SCAs) is cerebellar degeneration. Mutations in the known genes explain only 50% to 60% of SCA cases. To date, no effective treatments exist, and the knowledge of drug-treatable molecular pathways is limited. The examination of overlapping mechanisms and the interpretation of how ataxia genes interact will be important in the discovery of potential disease-modifying agents. To address the possible relationships among known SCA genes, predict their functions, identify overlapping pathways, and provide a framework for candidate gene discovery using whole-transcriptome expression data. We have used a systems biology approach based on whole-transcriptome gene expression analysis. As part of the United Kingdom Brain Expression Consortium, we analyzed the expression profile of 788 brain samples obtained from 101 neuropathologically healthy individuals (10 distinct brain regions each). Weighted gene coexpression network analysis was used to cluster 24 SCA genes into gene coexpression modules in an unsupervised manner. The overrepresentation of SCA transcripts in modules identified in the cerebellum was assessed. Enrichment analysis was performed to infer the functions and molecular pathways of genes in biologically relevant modules. Molecular functions and mechanisms implicating SCA genes, as well as lists of relevant coexpressed genes as potential candidates for novel SCA causative or modifier genes. Two cerebellar gene coexpression modules were statistically enriched in SCA transcripts (P = .021 for the tan module and P = 2.87 × 10−5 for the light yellow module) and contained established granule and Purkinje cell markers, respectively. One module includes genes involved in the ubiquitin-proteasome system and contains SCA genes usually associated with a complex phenotype, while the other module encloses many genes important for calcium homeostasis and signaling and contains SCA genes associated mostly with pure ataxia. Using normal gene expression in the human brain, we identified significant cell types and pathways in SCA pathogenesis. The overrepresentation of genes involved in calcium homeostasis and signaling may indicate an important target for therapy in the future. Furthermore, the gene networks provide new candidate genes for ataxias or novel genes that may be critical for cerebellar function.
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影响因子：
7
作者：
Lee, HK;Hsu, AK;Pavlidis, P
通讯作者：
Pavlidis, P
DOI：
10.1073/pnas.0810599106
发表时间：
2009-04-21
影响因子：
11.1
作者：
Becker, Esther B. E.;Olivera, Peter L.;Davies, Kay E.
通讯作者：
Davies, Kay E.
影响因子：
64.8
作者：
Moreno, Julie A.;Radford, Helois;Peretti, Diego;Steinert, Joern R.;Verity, Nicholas;Martin, Maria Guerra;Halliday, Mark;Morgan, Jason;Dinsdale, David;Ortori, Catherine A.;Barrett, David A.;Tsaytler, Pavel;Bertolotti, Anne;Willis, Anne E.;Bushell, Martin;Mallucci, Giovanna R.
通讯作者：
Mallucci, Giovanna R.
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
4.2
作者：
Forabosco P;Ramasamy A;Trabzuni D;Walker R;Smith C;Bras J;Levine AP;Hardy J;Pocock JM;Guerreiro R;Weale ME;Ryten M
通讯作者：
Ryten M