Clinical Focus

  • Neurology
  • Neuromuscular Diseases
  • Myasthenia Gravis
  • Immune-mediated disorders

Academic Appointments

Professional Education

  • Fellowship: Stanford University Dept of Neurology (2023) CA
  • Board Certification: Royal College of Physicians and Surgeons of Canada, Neurology (2022)
  • Residency: Universite Laval (2022) Canada
  • Medical Education: Universite Laval (2017) Canada

All Publications

  • Cerebrospinal Fluid Proteomic Changes after Nusinersen in Patients with Spinal Muscular Atrophy. Journal of clinical medicine Beaudin, M., Kamali, T., Tang, W., Hagerman, K. A., Dunaway Young, S., Ghiglieri, L., Parker, D. M., Lehallier, B., Tesi-Rocha, C., Sampson, J. B., Duong, T., Day, J. W. 2023; 12 (20)


    Disease-modifying treatments have transformed the natural history of spinal muscular atrophy (SMA), but the cellular pathways altered by SMN restoration remain undefined and biomarkers cannot yet precisely predict treatment response. We performed an exploratory cerebrospinal fluid (CSF) proteomic study in a diverse sample of SMA patients treated with nusinersen to elucidate therapeutic pathways and identify predictors of motor improvement. Proteomic analyses were performed on CSF samples collected before treatment (T0) and at 6 months (T6) using an Olink panel to quantify 1113 peptides. A supervised machine learning approach was used to identify proteins that discriminated patients who improved functionally from those who did not after 2 years of treatment. A total of 49 SMA patients were included (10 type 1, 18 type 2, and 21 type 3), ranging in age from 3 months to 65 years. Most proteins showed a decrease in CSF concentration at T6. The machine learning algorithm identified ARSB, ENTPD2, NEFL, and IFI30 as the proteins most predictive of improvement. The machine learning model was able to predict motor improvement at 2 years with 79.6% accuracy. The results highlight the potential application of CSF biomarkers to predict motor improvement following SMA treatment. Validation in larger datasets is needed.

    View details for DOI 10.3390/jcm12206696

    View details for PubMedID 37892834

  • Characterization of the phenotype with cognitive impairment and protein mislocalization in SCA34 NEUROLOGY-GENETICS Beaudin, M., Sellami, L., Martel, C., Touzel-Deschenes, L., Houle, G., Martineau, L., Lacroix, K., Lavallee, A., Chrestian, N., Rouleau, G. A., Gros-Louis, F., Laforce, R., Dupre, N. 2020; 6 (2): e403


    To better characterize the neurologic and cognitive profile of patients with spinocerebellar ataxia 34 (SCA34) caused by ELOVL4 mutations and to demonstrate the presence of ELOVL4 cellular localization and distribution abnormalities in skin-derived fibroblasts.We investigated a 5-generation French-Canadian kindred presenting with a late-onset cerebellar ataxia and recruited age- and education-matched controls to evaluate the presence of neurocognitive impairment. Immunohistochemistry of dermal fibroblasts derived from a patient's skin biopsy was performed.Patients had a late-onset slowly progressive cerebellar syndrome (mean age at onset 47 years; range 32-60 years) characterized by truncal and limb ataxia, dysarthria, hypometric saccades, and saccadic pursuits. No patient had past or current signs of erythrokeratodermia variabilis, which had previously been reported. MRI revealed cerebellar atrophy, with pontine atrophy (4 of 6 patients), and cruciform hypersignal in the pons (2 of 6 patients). Fluorodeoxyglucose-PET showed diffuse cerebellar hypometabolism in all 5 tested patients with subtle parietal hypometabolism in 3. Significant cognitive deficits were found in executive functioning, along with apparent visuospatial, attention, and psychiatric involvement. Immunohistochemistry of dermal fibroblasts showed mislocalization of the ELOVL4 protein, which appeared punctate and aggregated, supporting a dominant negative effect of the mutation on protein localization.Our findings support the pathogenicity of ELOVL4 mutations in cerebellar dysfunction and provide a detailed characterization of the SCA34 phenotype, with neurocognitive changes typical of the cerebellar cognitive-affective syndrome.

    View details for DOI 10.1212/NXG.0000000000000403

    View details for Web of Science ID 000532368400007

    View details for PubMedID 32211516

    View details for PubMedCentralID PMC7073455

  • The Classification of Autosomal Recessive Cerebellar Ataxias: a Consensus Statement from the Society for Research on the Cerebellum and Ataxias Task Force CEREBELLUM Beaudin, M., Matilla-Duenas, A., Soong, B., Pedroso, J., Barsottini, O. G., Mitoma, H., Tsuji, S., Schmahmann, J. D., Manto, M., Rouleau, G. A., Klein, C., Dupre, N. 2019; 18 (6): 1098-1125


    There is currently no accepted classification of autosomal recessive cerebellar ataxias, a group of disorders characterized by important genetic heterogeneity and complex phenotypes. The objective of this task force was to build a consensus on the classification of autosomal recessive ataxias in order to develop a general approach to a patient presenting with ataxia, organize disorders according to clinical presentation, and define this field of research by identifying common pathogenic molecular mechanisms in these disorders. The work of this task force was based on a previously published systematic scoping review of the literature that identified autosomal recessive disorders characterized primarily by cerebellar motor dysfunction and cerebellar degeneration. The task force regrouped 12 international ataxia experts who decided on general orientation and specific issues. We identified 59 disorders that are classified as primary autosomal recessive cerebellar ataxias. For each of these disorders, we present geographical and ethnical specificities along with distinctive clinical and imagery features. These primary recessive ataxias were organized in a clinical and a pathophysiological classification, and we present a general clinical approach to the patient presenting with ataxia. We also identified a list of 48 complex multisystem disorders that are associated with ataxia and should be included in the differential diagnosis of autosomal recessive ataxias. This classification is the result of a consensus among a panel of international experts, and it promotes a unified understanding of autosomal recessive cerebellar disorders for clinicians and researchers.

    View details for DOI 10.1007/s12311-019-01052-2

    View details for Web of Science ID 000502725000008

    View details for PubMedID 31267374

    View details for PubMedCentralID PMC6867988

  • Systematic review of autosomal recessive ataxias and proposal for a classification. Cerebellum & ataxias Beaudin, M., Klein, C. J., Rouleau, G. A., Dupre, N. 2017; 4: 3


    BACKGROUND: The classification of autosomal recessive ataxias represents a significant challenge because of high genetic heterogeneity and complex phenotypes. We conducted a comprehensive systematic review of the literature to examine all recessive ataxias in order to propose a new classification and properly circumscribe this field as new technologies are emerging for comprehensive targeted gene testing.METHODS: We searched Pubmed and Embase to identify original articles on recessive forms of ataxia in humans for which a causative gene had been identified. Reference lists and public databases, including OMIM and GeneReviews, were also reviewed. We evaluated the clinical descriptions to determine if ataxia was a core feature of the phenotype and assessed the available evidence on the genotype-phenotype association. Included disorders were classified as primary recessive ataxias, as other complex movement or multisystem disorders with prominent ataxia, or as disorders that may occasionally present with ataxia.RESULTS: After removal of duplicates, 2354 references were reviewed and assessed for inclusion. A total of 130 articles were completely reviewed and included in this qualitative analysis. The proposed new list of autosomal recessive ataxias includes 45 gene-defined disorders for which ataxia is a core presenting feature. We propose a clinical algorithm based on the associated symptoms.CONCLUSION: We present a new classification for autosomal recessive ataxias that brings awareness to their complex phenotypes while providing a unified categorization of this group of disorders. This review should assist in the development of a consensus nomenclature useful in both clinical and research applications.

    View details for DOI 10.1186/s40673-017-0061-y

    View details for PubMedID 28250961