Biomarkers Identification and Disease Modeling using Multimodal Neuroimaging Approaches in Polyglutamine Diseases

Abstract : Mutations in different gene loci that lead to the encoding of the unstable and expanded glutamine-encoding cytosine-adenine-guanine (CAG) repeats results in the group of diseases known as the polyglutamine diseases. This project focuses on the most common forms which are Huntington disease (HD) and spinocerebellar ataxia (SCA) types 1, 2, 3 and 7. These are autosomal dominant diseases responsible for severe movement disorders and are thought to share common pathophysiological pathways with a major emphasis on metabolic dysfunction. The availability of genetic testing and their predominantly adult onset opens a window for therapeutic intervention before symptoms onset. However, current clinical scales are not sensitive and cannot effectively be used to evaluate individuals at the presymptomatic stage of the diseases. This prompts the need for biomarkers that are sensitive to macroscopic and microscopic changes that may occur prior to disease onset. Magnetic resonance imaging (MRI) and spectroscopy (MRS) techniques present non-invasive approaches to extract pertinent information that otherwise would not be possible with clinical scales. In this work therefore, we present a combination of different MRI and MRS techniques to identify robust biomarkers in HD and SCA. We also present therapeutic approaches that hold promise in HD. Likewise, we show that imaging biomarkers have higher effect sizes than clinical scales. Finally, we combine multimodal data – volumetry, MRS, metabolomics and lipidomic – from SCA into a model that best explains the pathology.
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Isaac Mawusi Adanyeguh. Biomarkers Identification and Disease Modeling using Multimodal Neuroimaging Approaches in Polyglutamine Diseases. Neurons and Cognition [q-bio.NC]. Université Pierre et Marie Curie - Paris VI, 2017. English. ⟨NNT : 2017PA066279⟩. ⟨tel-02289619v2⟩

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