Evolution of structural neuroimaging biomarkers in a series of adult patients with Niemann-Pick type C under treatment

International audienceBackground: Niemann-Pick type C (NPC) disease is a lysosomal storage disorder characterized by a wide clinical spectrum and non-specific conventional magnetic resonance imaging (MRI) signs. As substrate reduction therapy with miglustat is now used in almost all patients, its efficacy and the course of the disease are sometimes difficult to evaluate. Neuroimaging biomarkers could prove useful in this matter. We first performed a retrospective analysis of volumetric and diffusion tensor imaging (DTI) data on 13 adult NPC patients compared to 13 controls of similar age and sex. Eleven NPC patients were then studied using the same neuroimaging modalities over a mean of 5 years. The NPC composite score was used to evaluate disease severity.ResultsNPC patients showed atrophy in basal ganglia – pallidum (p = 0.029), caudate nucleus (p = 0.022), putamen (p = 0.002) and thalamus (p < 0.001) – cerebral peduncles (p = 0.003) and corpus callosum (p = 0.006), compared to controls. NPC patients also displayed decreased fractional anisotropy (FA) in several regions of interest – corona radiata (p = 0.015), internal capsule (p = 0.007), corpus callosum (p = 0.032) and cingulate gyrus (p = 0.002) – as well as a broad increase in radial diffusivity (p < 0.001), compared to controls. Over time, 3 patients worsened clinically, including 2 patients who interrupted treatment, while 8 patients remained stable. With miglustat, no significant volumetric change was observed but FA improved after 2 years in the corpus callosum and the corona radiata of NPC patients (n = 4; p = 0.029) – although that was no longer observed at further time points.ConclusionThis is the first study conducted on a series of adult NPC patients using two neuroimaging modalities and followed under treatment. It confirmed that NPC patients displayed cerebral atrophy in several regions of interest compared to controls. Furthermore, miglustat showed an early effect on diffusion metrics in treated patients. DTI can detect brain microstructure alterations caused by neurometabolic dysfunction. Its potential as a biomarker in NPC shall be further evaluated in upcoming therapeutic trials

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)

Plasma neurofilament light chain predicts cerebellar atrophy and clinical progression in spinocerebellar ataxia

International audienceNeurofilament light chain (NfL) is a marker of brain atrophy and predictor of disease progression in rare diseases such as Huntington Disease, but also in more common neurological disorders such as Alzheimer's disease. The aim of this study was to measure NfL longitudinally in autosomal dominant spinocerebellar ataxias (SCAs) and establish correlation with clinical and imaging parameters. We enrolled 62 pathological expansions carriers (17 SCA1, 13 SCA2, 19 SCA3, and 13 SCA7) and 19 age-matched controls in a prospective biomarker study between 2011 and 2015 and followed for 24 months at the Paris Brain Institute. We performed neurological examination, brain 3 T MRI and plasma NfL measurements using an ultrasensitive single-molecule array at baseline and at the two-year follow-up visit. We evaluated NfL correlations with ages, CAG repeat sizes, clinical scores and volumetric brain MRIs. NfL levels were significantly higher in SCAs than controls at both time points (p < 0.001). Age-adjusted NfL levels were significantly correlated at baseline with clinical scores (p < 0.01). We identified optimal NfL cutoff concentrations to differentiate controls from carriers for each genotype (SCA1 16.87 pg/mL, SCA2, 19.1 pg/mL, SCA3 16.04 pg/mL, SCA7 16.67 pg/mL). For all SCAs, NfL concentration was stable over two years (p = 0.95) despite a clinical progression (p < 0.0001). Clinical progression between baseline and follow-up was associated with higher NfL concentrations at baseline (p = 0.04). Of note, all premanifest carriers with NfL levels close to cut off concentrations had signs of the disease at follow-up. For all SCAs, the higher the observed NfL, the lower the pons volume at baseline (p < 0.01) and follow-up (p = 0.02). Higher NfL levels at baseline in all SCAs predicted a decrease in cerebellar volume (p = 0.03). This result remained significant for SCA2 only among all genotypes (p = 0.02). Overall, plasma NfL levels at baseline in SCA expansion carriers predict cerebellar volume change and clinical score progression. NfL levels might help refine inclusion criteria for clinical trials in carriers with very subtle signs

Multiparametric characterization of white matter alterations in early stage Huntington disease

International audienceHuntington's disease (HD) is a monogenic, fully penetrant neurodegenerative disorder. Widespread white matter damage affects the brain of patients with HD at very early stages of the disease. Fixel-based analysis (FBA) is a novel method to investigate the contribution of individual crossing fibers to the white matter damage and to detect possible alterations in both fiber density and fiber-bundle morphology. Diffusion-weighted magnetic resonance spectroscopy (DW-MRS), on the other hand, quantifies the motion of brain metabolites in vivo, thus enabling the investigation of microstructural alteration of specific cell populations. The aim of this study was to identify novel specific microstructural imaging markers of white matter degeneration in HD, by combining FBA and DW-MRS. Twenty patients at an early stage of HD and 20 healthy controls were recruited in a monocentric study. Using diffusion imaging we observed alterations to the brain microstructure and their morphology in patients with HD. Furthermore, FBA revealed specific fiber populations that were affected by the disease. Moreover, the mean diffusivity of the intra-axonal metabolite N-acetylaspartate, co-measured with N-acetylaspartylglutamate (tNAA), was significantly reduced in the corpus callosum of patients compared to controls. FBA and DW-MRS of tNAA provided more specific information about the biological mechanisms underlying HD and showed promise for early investigation of white matter degeneration in HD

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

Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes

Objective: As gene-based therapies may soon arise for patients with spinocerebellar ataxia (SCA), there is a critical need to identify biomarkers of disease progression with effect sizes greater than clinical scores, enabling trials with smaller sample sizes. Methods: We enrolled a unique cohort of patients with SCA1 (n = 15), SCA2 (n = 12), SCA3 (n = 20) and SCA7 (n = 10) and 24 healthy controls of similar age, sex and body mass index. We collected longitudinal clinical and imaging data at baseline and follow-up (mean interval of 24 months). We performed both manual and automated volumetric analyses. Diffusion tensor imaging (DTI) and a novel tractography method, called fixel-based analysis (FBA), were assessed at follow-up. Effect sizes were calculated for clinical scores and imaging parameters. Results: Clinical scores worsened as atrophy increased over time (p 1.2) compared to clinical scores (<0.8). FBA, applied for the first time to SCA, was sensitive to microstructural cross-sectional differences that were not captured by conventional DTI metrics, especially in the less studied SCA7 group. FBA also showed larger effect sizes than DTI metrics. Conclusion: This study showed that volumetry outperformed clinical scores to measure disease progression in SCA1, SCA2, SCA3 and SCA7. Therefore, we advocate the use of volumetric biomarkers in therapeutic trials of autosomal dominant ataxias. In addition, FBA showed larger effect size than DTI to detect cross-sectional microstructural alterations in patients relative to controls. Keywords: Spinocerebellar ataxia, Imaging biomarkers, Apparent fiber density, Fixel analysis, Diffusion imaging

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

Image_1_Assessment of Cerebral and Cerebellar White Matter Microstructure in Spinocerebellar Ataxias 1, 2, 3, and 6 Using Diffusion MRI.JPEG

Development of imaging biomarkers for rare neurodegenerative diseases such as spinocerebellar ataxia (SCA) is important to non-invasively track progression of disease pathology and monitor response to interventions. Diffusion MRI (dMRI) has been shown to identify cross-sectional degeneration of white matter (WM) microstructure and connectivity between healthy controls and patients with SCAs, using various analysis methods. In this paper, we present dMRI data in SCAs type 1, 2, 3, and 6 and matched controls, including longitudinal acquisitions at 12–24-month intervals in a subset of the cohort, with up to 5 visits. The SCA1 cohort also contained 3 premanifest patients at baseline, with 2 showing ataxia symptoms at the time of the follow-up scans. We focused on two aspects: first, multimodal evaluation of the dMRI data in a cross-sectional approach, and second, longitudinal trends in dMRI data in SCAs. Three different pipelines were used to perform cross-sectional analyses in WM: region of interest (ROI), tract-based spatial statistics (TBSS), and fixel-based analysis (FBA). We further analyzed longitudinal changes in dMRI metrics throughout the brain using ROI-based analysis. Both ROI and TBSS analyses identified higher mean (MD), axial (AD), and radial (RD) diffusivity and lower fractional anisotropy (FA) in the cerebellum for all SCAs compared to controls, as well as some cerebral alterations in SCA1, 2, and 3. FBA showed lower fiber density (FD) and fiber crossing (FC) regions similar to those identified by ROI and TBSS analyses. FBA also highlighted corticospinal tract (CST) abnormalities, which was not detected by the other two pipelines. Longitudinal ROI-based analysis showed significant increase in AD in the middle cerebellar peduncle (MCP) for patients with SCA1, suggesting that the MCP may be a good candidate region to monitor disease progression. The patient who remained symptom-free throughout the study displayed no microstructural abnormalities. On the other hand, the two patients who were at the premanifest stage at baseline, and showed ataxia symptoms in their follow-up visits, displayed AD values in the MCP that were already in the range of symptomatic patients with SCA1 at their baseline visit, demonstrating that microstructural abnormalities are detectable prior to the onset of ataxia.</p