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.

Objective 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. Methods 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 patient9s skin biopsy was performed. Results 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. Conclusions 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.

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.

IntroductionThe last decade has witnessed major breakthroughs in identifying novel genetic causes of hereditary ataxias, deepening our understanding of disease mechanisms, and developing therapies for these debilitating disorders.Areas coveredThis article reviews the currently approved and most promising candidate pharmacotherapies in relation to the known disease mechanisms of the most prevalent autosomal recessive ataxias. Omaveloxolone is an Nrf2 activator that increases antioxidant defense and was recently approved for treatment of Friedreich ataxia. Its therapeutic effect is modest, and further research is needed to find synergistic treatments that would halt or reverse disease progression. Promising approaches include upregulation of frataxin expression by epigenetic mechanisms, direct protein replacement, and gene replacement therapy. For ataxia-telangiectasia, promising approaches include splice-switching antisense oligonucleotides and small molecules targeting oxidative stress, inflammation, and mitochondrial function. Rare recessive ataxias for which disease-modifying therapies exist are also reviewed, emphasizing recently approved therapies. Evidence supporting the use of riluzole and acetyl-leucine in recessive ataxias is discussed.Expert opinionAdvances in genetic therapies for other neurogenetic conditions have paved the way to implement feasible approaches with potential dramatic benefits. Particularly, as we develop effective treatments for these conditions, we may need to combine therapies, consider newborn testing for pre-symptomatic treatment, and optimize non-pharmacological approaches.