David J. Szmulewicz

Background: Friedreich ataxia (FRDA) is a rare neurodegenerative disorder with heterogenous clinical progression, complicating prognosis and trial design. Neuroimaging offers objective biomarkers of disease progression, yet variability in progression patterns remains poorly understood. Objective: The objective of this study is to identify distinct neurodegenerative progression patterns in FRDA using longitudinal multimodal magnetic resonance imaging (MRI) and to evaluate associations with clinical, demographic, and genetic factors. Methods: Longitudinal structural and diffusion MRI data from 54 patients with FRDA and 57 controls were analyzed. Annualized progression rates of macrostructural (volumetric) and microstructural (diffusion) features across cerebellum, brainstem, and spinal cord regions were clustered using Gaussian Mixture Models. Following model selection, clusters were evaluated for biological plausibility of longitudinal imaging trajectories, bootstrap and subsampling reproducibility, and consistency of case‐control composition. Associations with demographic, genetic, and clinical variables were examined, and Random Forest modeling assessed predictors of cluster membership. Results: Four statistical clusters were identified, three of which represented robust, biologically interpretable progression patterns characterized by predominant microstructural degeneration, predominant macrostructural atrophy, and minimal measurable progression. The microstructure‐ and macrostructure‐dominant patterns were enriched for FRDA participants, whereas the minimal‐progression pattern contained more controls. GAA1 repeat length was the only variable consistently associated with cluster membership, with larger expansions observed in the microstructure‐dominant pattern. Disease duration and clinical progression rates did not significantly differentiate progression patterns. Conclusions: Longitudinal multimodal MRI shows distinct neurodegenerative progression patterns in FRDA that are not fully captured by conventional clinical measures. This data‐driven framework provides a basis for investigating imaging‐derived disease heterogeneity and its potential relevance to participant stratification in clinical trials. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Cerebellar ataxia, neuropathy and vestibular areflexia syndrome (CANVAS) and the wider family of RFC1-related diseases are among the most common causes of adult-onset hereditary ataxia, yet diagnosis is frequently delayed by decades. This Patient Perspective combines the historical evolution of clinical understanding with a first-person patient account to illustrate why the disorder is so often missed, and to offer a structured, clinically usable approach to recognition, investigation and multidisciplinary management. We argue that no single symptom is diagnostic; rather, the diagnosis emerges from recognising phenotypic patterns, which in the case of CANVAS are sensory ganglionopathy, bilateral vestibular hypofunction and cerebellar impairment. This triad may accumulate over many years and is often attributed by patients and clinicians alike to unrelated, more common conditions. A chronic cough generally predates the onset of the other features. Practical diagnostic pearls, a stepwise investigation algorithm and a multidisciplinary management framework are presented alongside the patient’s own account of a three-decade diagnostic journey, to help shorten the path to diagnosis for future patients.

Background: Cerebellar ataxia, neuropathy and vestibular are flexia syndrome (CANVAS) and RFC1‐related disease are most commonly caused by biallelic AAGGG repeat expansions in RFC1. The high population frequency of this expansion compared to the frequency of CANVAS suggests incomplete penetrance. Objective: To determine whether polygenic risk factors influence incomplete penetrance in RFC1‐related disease. Methods: Biallelic RFC1 AAGGG status was profiled in Genomics England (GEL) and the UK Biobank (UKB) discovery cohorts and a replication Australian ataxia cohort (AAC). Polygenic score (PGS) analysis was performed with variants identified in a Huntington's Disease age at onset study. Results: We identified 56 (GEL) and 18 (UKB) biallelic individuals with ataxia and/or neuropathy, and 26 (GEL) and 207 (UKB) age‐matched biallelic carriers with no report of ataxia or neuropathy. Meta‐analysis of GEL and UKB identified elevated PGS in biallelic affected individuals (OR = 1.43, p = 2.2 × 10 ⁻³ ) compared to controls, but not in the biallelic carriers (OR = 1.01, P = 0.92). The variant rs245100, upstream MSH3, was the biggest contributor to this elevated risk (OR = 2.35, adjusted p = 0.02). Replication in the AAC showed elevated PGS in individuals with molecular confirmation of CANVAS or RFC1‐related disease ( n = 54) (OR = 1.93, P = 4.4 × 10 ⁻⁵ ), and enrichment of rs245100 (OR = 4.24, p = 1.0 × 10 ⁻⁴ ). Conclusion: These results indicate that modifier variant burden alters disease penetrance and presentation in RFC1‐related disease and determines an increased incidence of ataxia and neuropathy in biallelic individuals. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Background and objectives Cognitive deficits are observed in a subset of individuals with spinocerebellar ataxias (SCAs); however, there is limited research on the longitudinal trajectory of such deficits. We investigated longitudinal cognitive performance amongst individuals with SCAs relative to controls, and the relationship of change in cognitive performance with change in self-reported function. Methods Individuals with symptomatic SCA1, SCA2, SCA3, and SCA6 as well as unaffected controls were administered the Cerebellar Cognitive Affective Syndrome Scale (CCAS-S) at yearly intervals for up to two years. Participants with SCA self-reported day-to-day cognitive and motor function via annual completion of the Patient-Reported Outcome Measure of Ataxia. Results Significant two-year decline in CCAS-S performance was observed in individuals with SCA (n = 25). In a larger cohort of individuals who completed 1-year follow-up (n = 45 SCA), greater decline was observed among individuals with better baseline performance, and, at a trending level, those with milder motor ataxia severity. Greater one-year decline on the CCAS-S was significantly associated with greater decline in self-reported day-to-day cognitive function. In contrast, one-year CCAS-S change was not related to change in self-reported motor function. Conclusions The CCAS-S indexes functionally relevant cognitive change over time in SCAs, with this decline apparent in at least a subset of individuals with SCAs. Decline in cognitive performance may be particularly pronounced in early/mild disease stages. Our results motivate larger and longer-term studies of the CCAS-S in SCAs, including investigating cognitive change across the pre-symptomatic and symptomatic disease course, and identifying risk factors for cognitive decline, to inform appropriate clinical support.

The assessment of speech in Cerebellar Ataxia (CA) is time-consuming and requires clinical interpretation. In this study, we introduce a fully automated objective algorithm that uses significant acoustic features from time, spectral, cepstral, and non-linear dynamics present in microphone data obtained from different repeated Consonant-Vowel (C-V) syllable paradigms. The algorithm builds machine-learning models to support a 3-tier diagnostic categorisation for distinguishing Ataxic Speech from healthy speech, rating the severity of Ataxic Speech, and nomogram-based supporting scoring charts for Ataxic Speech diagnosis and severity prediction. The selection of features was accomplished using a combination of mass univariate analysis and elastic net regularization for the binary outcome, while for the ordinal outcome, Spearman’s rank-order correlation criterion was employed. The algorithm was developed and evaluated using recordings from 126 participants: 65 individuals with CA and 61 controls (i.e., individuals without ataxia or neurotypical). For Ataxic Speech diagnosis, the reduced feature set yielded an area under the curve (AUC) of 0.97 (95% CI 0.90–1), the sensitivity of 97.43%, specificity of 85.29%, and balanced accuracy of 91.2% in the test dataset. The mean AUC for severity estimation was 0.74 for the test set. The high C-indexes of the prediction nomograms for identifying the presence of Ataxic Speech (0.96) and estimating its severity (0.81) in the test set indicates the efficacy of this algorithm. Decision curve analysis demonstrated the value of incorporating acoustic features from two repeated C-V syllable paradigms. The strong classification ability of the specified speech features supports the framework’s usefulness for identifying and monitoring Ataxic Speech.

Purpose of review: An increasing number of peripheral neuro(no)pathies are identified as involving other components of the neurological system, particularly those that further impair balance. Here we aim to outline an evidence-based approach to the diagnosis of patients who present with a somatosensory disorder which also involves at least one other area of neurological impairment such as the vestibular, auditory, or cerebellar systems. Recent findings: Detailed objective investigation of patients who present with sensory impairment, particularly where the degree of imbalance is greater than would be expected, aids the accurate diagnosis of genetic, autoimmune, metabolic, and toxic neurological disease. Summary: Diagnosis and management of complex somatosensory disorders benefit from investigation which extends beyond the presenting sensory impairment.

Cerebellar ataxia is the poorly coordinated movement that results from injury or disease affecting the cerebellum. The diagnosis and assessment of ataxia are significantly challenging due to dependency on clinicians’ experience and the attendant subjectivity of such a process. In recent years, neuroimaging and sensor-based approaches, supported by effective machine learning techniques have made advances in the pursuit of addressing these clinical challenges. In this work, we present an outline of approaches to applying machine learning to this clinical challenge. We first provide a fundamental clinical overview with practical problems and then from a machine learning perspective, outline possible approaches with which to address these clinical challenges. Also discussed are the limitations in existing methods, the provision of cross disciplinary approaches and the current state-of-the-art as a potential basis for future research.

Increasingly, cerebellar syndromes are recognized as affecting multiple systems. Extracerebellar features include peripheral neuropathies affecting proprioception; cranial neuropathies such as auditory and vestibular; and neuronopathies, for example, dorsal root and vestibular. The presence of such features, which in and of themselves may cause ataxia, likely contribute to key disabilities such as gait instability and falls. Based on the evolving available literature and experience, we outline a clinical approach to the diagnosis of adult-onset ataxia where a combination of cerebellar and peripheral or cranial nerve pathology exists. Objective diagnostic modalities including electrophysiology, oculomotor, and vestibular function testing are invaluable in accurately defining an individual9s phenotype. Advances in MRI techniques have led to an increased recognition of disease-specific patterns of cerebellar pathology, including those conditions where neuronopathies may be involved. Depending on availability, a stepwise approach to genetic testing is suggested. This is guided by factors such as pattern of inheritance and age at disease onset, and genetic testing may range from specific genetic panels through to whole-exome and whole-genome sequencing. Management is best performed with the involvement of a multidisciplinary team, aiming at minimization of complications such as falls and aspiration pneumonia and maximizing functional status.

In 2019, a biallelic pentanucleotide repeat expansion in the gene encoding replication factor C subunit 1 (RFC1) was reported as a cause of cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS). In addition, biallelic expansions were shown to account for up to 22% of cases with late-onset ataxia. Since this discovery, the phenotypic spectrum reported to be associated with RFC1 expansions has extended beyond the initial conditions to include pure cerebellar ataxia, isolated somatosensory impairment, combinations of the 2, and parkinsonism, leading to a potentially broad differential diagnosis. Genetic studies suggest RFC1 expansions may be the most common genetic cause of ataxia and are likely underdiagnosed. This review summarizes the current molecular and clinical knowledge of RFC1-related disease, with a focus on the evaluation of recent phenotype associations and highlighting the current challenges in clinical pathways to diagnosis and molecular testing.