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Original Investigation |

Insights From Cerebellar Transcriptomic Analysis Into the Pathogenesis of Ataxia

Conceição Bettencourt, PhD1; Mina Ryten, MD1,2; Paola Forabosco, PhD3; Stephanie Schorge, PhD4; Joshua Hersheson, MD1; John Hardy, PhD1; Henry Houlden, MD1 ; for the United Kingdom Brain Expression Consortium
[+] Author Affiliations
1Department of Molecular Neuroscience, UCL Institute of Neurology, London, England
2Department of Medical and Molecular Genetics, King’s College London, London, England
3Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Cagliari, Italy
4Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, England
JAMA Neurol. 2014;71(7):831-839. doi:10.1001/jamaneurol.2014.756.
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Importance  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.

Objectives  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.

Design, Setting, and Participants  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.

Main Outcomes and Measures  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.

Results  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.

Conclusions and Relevance  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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Figure 1.
z Scores Indicating Whether Genes in the Coexpression Modules Identified in the Cerebellum Cluster in Other Brain Regions

z Scores of less than 2 (bottom red line) indicate no evidence of preservation (the case for the cerebellar light yellow module in most brain regions), while scores exceeding 5 (green line) and exceeding 10 (upper red line) indicate moderate and strong module preservation across brain regions, respectively.

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Figure 2.
Network Representation of the Light Yellow Module in the Cerebellum

Shown are all genes connected with a topological overlap measure exceeding 0.01. The spinocerebellar ataxia genes in this module are highlighted in pink, together with all genes that are directly connected to it based on the topological overlap measure cutoff used. Genes previously reported as interactors of spinocerebellar ataxia genes are highlighted in blue.

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Figure 3.
Proposed Molecular Mechanisms Contributing to Intracellular Calcium Homeostasis and Signaling in Neurons Depicting the Involvement of Genes Known to Cause Ataxia and Genes in the Cerebellar Light Yellow Coexpression Module

Genes are shown in italics: red indicates human ataxia genes (underlined if in the light yellow module) and purple indicates additional relevant genes in the light yellow module (underlined if involved in ataxia phenotypes in mice). The red star represents calcium ions (Ca2+). Red boxes highlight proteins encoded by SCA genes; yellow boxes represent proteins encoded by other genes in the light yellow module; pale yellow boxes show relevant proteins although not found in our data. KCN indicates Potassium channels; CACN, Voltage-gated calcium channels; EAATs, Excitatory amino-acid transporters; GluR, Glutamate receptors; GPCR, G protein-coupled receptors; SOC, Store-operated calcium channels; PLC, Phospholipase C; PKC, Protein kinase C; IP3, Inositol 1,4,5-triphosphate; IP4, Inositol 1,3,4,5-tetrakisphosphate; IP3R, Inositol 1,4,5-triphosphate receptors; DAG, diacylglycerol; STIM, Stromal interaction molecule; SERCA, Sarcoendoplasmic reticulum (SR) calcium transport ATPase; ER/SR, Endo/sarcoplasmic reticulum; mut, mutated; PolyQmut, proteins with expanded polyglutamine tracts, namely those encoded by mutated ATXN1, ATXN2, ATXN3, CACNA1A,ATXN7, TBP, and ATN1.

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