Identification de biomarqueurs et modélisation de la maladie en utilisant des approches multimodales de neuroimagerie dans les maladies polyglutamine

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.Les maladies par expansion de polyglutamines sont des maladies neurodégénératives dues à l’expansion du trinucléotide cytosine-adénine-guanine (CAG) dans les gènes correspondants codant pour une expansion d’homopolymère de glutamine dans les protéines mutées. Ce projet concerne les formes les plus courantes qui sont la maladie de Huntington (MH) et les ataxies spinocérébelleuses (SCA) types 1, 2, 3 et 7. Ce sont des maladies autosomiques dominantes, responsables de troubles graves de la motricité partageant des voies physiopathologiques communes, avec un effet notable sur la dysfonction métabolique. La disponibilité des tests génétiques et le fait que la plupart du temps la maladie débute à l’âge adulte offre la possibilité d’une intervention thérapeutique avant l’apparition de symptômes. Toutefois, les échelles cliniques ne sont pas assez sensibles et ne peuvent effectivement être utilisés pour évaluer les personnes au stade présymptomatique de la maladie. Les techniques d’imagerie par résonance magnétique (IRM) et de spectroscopie (SRM) sont des approches non invasives qui permettent de recueillir des informations pertinentes et sensibles. Ainsi, dans ce travail, nous présentons une combinaison de différentes techniques d’IRM et SRM afin d’identifier de robustes biomarqueurs de la MH et des SCA. Nous présentons aussi des approches thérapeutiques prometteuses dans la MH. De la même manière, nous voulons démontrer que des biomarqueurs d’imagerie sont plus sensibles que des échelles cliniques. Pour conclure, nous combinons des données multimodales – volumétrie, SRM, métabolomique et lipidomique – à partir de SCA dans un modèle qui explique mieux la pathologie

Quantitative neuroimaging biomarkers in a series of 20 adult patients with POLG mutations

International audienceMutations in the gene encoding polymerase gamma (POLG) are a common cause of mitochondrial diseases in adults. We retrospectively analyzed volumetric and diffusion tensor imaging data from 20 adult POLG-mutated patients compared to healthy controls. We used an original clinical binary load score and electroneuromyography to evaluate disease severity. Patients showed atrophy in the basal ganglia, amygdala, and brainstem (p < 0.05) compared to controls, as well as decreased fractional anisotropy (FA) in the cingulate gyrus, the internal capsule and the corona radiata (p < 0.05). Clinical scores correlated with decreased FA and increased radial diffusivity in several brain regions (p < 0.05)

Expanded neurochemical profile in the early stage of Huntington disease using proton magnetic resonance spectroscopy

International audienceThe striatum is a well-known region affected in Huntington disease (HD). However, other regions, including the visual cortex, are implicated. We have identified previously an abnormal energy response in the visual cortex of patients at an early stage of HD using 31P magnetic resonance spectroscopy (31P MRS). We therefore sought to further characterize these metabolic alterations with 1H MRS using a well-validated semi-localized by adiabatic selective refocusing (semi-LASER) sequence that allows the measurement of an expanded number of neurometabolites. Ten early affected patients [Unified Huntington Disease Rating Scale (UHDRS), total motor score = 13.6 ± 10.8] and 10 healthy volunteers of similar age and body mass index (BMI) were recruited for the study. We performed 1H MRS in the striatum – the region that is primarily affected in HD – and the visual cortex. The protocol allowed a reliable quantification of 10 metabolites in the visual cortex and eight in the striatum, compared with three to five metabolites in previous 1H MRS studies performed in HD. We identified higher total creatine (p < 0.05) in the visual cortex and lower glutamate (p < 0.001) and total creatine (p < 0.05) in the striatum of patients with HD compared with controls. Less abundant neurometabolites [glutamine, γ-aminobutyric acid (GABA), glutathione, aspartate] showed similar concentrations in both groups. The protocol allowed the measurement of several additional metabolites compared with standard vendor protocols. Our study points to early changes in metabolites involved in energy metabolism in the visual cortex and striatum of patients with HD. Decreased striatal glutamate could reflect early neuronal dysfunction or impaired glutamatergic neurotransmission

A strategy for multimodal data integration: application to biomarkers identification in spinocerebellar ataxia

International audienceThe growing number of modalities (e.g. multi-omics, imaging and clinical data) characterizing a given disease provides physicians and statisticians with complementary facets reflecting the disease process but emphasizes the need for novel statistical methods of data analysis able to unify these views. Such data sets are indeed intrinsically structured in blocks, where each block represents a set of variables observed on a group of individuals. Therefore, classical statistical tools cannot be applied without altering their organization, with the risk of information loss. Regularized generalized canonical correlation analysis (RGCCA) and its sparse generalized canonical correlation analysis (SGCCA) counterpart are component-based methods for exploratory analyses of data sets structured in blocks of variables. Rather than operating sequentially on parts of the measurements, the RGCCA/SGCCA-based integrative analysis method aims at summarizing the relevant information between and within the blocks. It processes a priori information defining which blocks are supposed to be linked to one another, thus reflecting hypotheses about the biology underlying the data blocks. It also requires the setting of extra parameters that need to be carefully adjusted. Here, we provide practical guidelines for the use of RGCCA/SGCCA. We also illustrate the flexibility and usefulness of RGCCA/SGCCA on a unique cohort of patients with four genetic subtypes of spinocerebellar ataxia, in which we obtained multiple data sets from brain volumetry and magnetic resonance spectroscopy, and metabolomic and lipidomic analyses. As a first step toward the extraction of multimodal biomarkers, and through the reduction to a few meaningful components and the visualization of relevant variables, we identified possible markers of disease progression

Triheptanoin dramatically reduces paroxysmal motor disorder in patients with GLUT1 deficiency

International audienceObjective On the basis of our previous work with triheptanoin, which provides key substrates to the Krebs cycle in the brain, we wished to assess its therapeutic effect in patients with glucose transporter type 1 deficiency syndrome (GLUT1-DS) who objected to or did not tolerate ketogenic diets.Methods We performed an open-label pilot study with three phases of 2 months each (baseline, treatment and withdrawal) in eight patients with GLUT1-DS (7–47 years old) with non-epileptic paroxysmal manifestations. We used a comprehensive patient diary to record motor and non-motor paroxysmal events. Functional 31P-NMR spectroscopy was performed to quantify phosphocreatine (PCr) and inorganic phosphate (Pi) within the occipital cortex during (activation) and after (recovery) a visual stimulus.Results Patients with GLUT1-DS experienced a mean of 30.8 (±27.7) paroxysmal manifestations (52% motor events) at baseline that dropped to 2.8 (±2.9, 76% motor events) during the treatment phase (p=0.028). After withdrawal, paroxysmal manifestations recurred with a mean of 24.2 (±21.9, 52% motor events; p=0.043). Furthermore, brain energy metabolism normalised with triheptanoin, that is, increased Pi/PCr ratio during brain activation compared to the recovery phase (p=0.021), and deteriorated when triheptanoin was withdrawn.Conclusions Treatment with triheptanoin resulted in a 90% clinical improvement in non-epileptic paroxysmal manifestations and a normalised brain bioenergetics profile in patients with GLUT1-DS