Mov Disord. 2026 Mar 18. doi: 10.1002/mds.70227. Online ahead of print.
ABSTRACT
BACKGROUND: ATP1A3-related disorders are characterized by genetic heterogeneity and phenotypic pleiotropy, posing significant challenges for classification. Although canonical phenotypes have traditionally guided decision-making, increasing evidence highlights their limitations in capturing the clinical complexity.
OBJECTIVE: The aims of this study were to characterize movement disorders, paroxysmal features, and genotype-phenotype relationships; to build a curated video archive; and to assess alignment with canonical phenotypes.
METHODS: This is an observational study of 88 individuals with pathogenic or likely pathogenic variants in ATP1A3 who were evaluated in specialized movement disorders programs.
RESULTS: Age at last clinical follow-up ranged from 0.1 to 63 years; 80.7% were pediatric patients. Chronic movement disorders were present in 68 of 88 individuals (75%); most had two or more coexisting phenomenologies. Dystonia was most common (47/88, 53%), followed by spasticity (28/88, 32%) and ataxia (28/92, 32%). Paroxysmal events occurred in 78 of 88 (88%) patients, including dystonic spells (45/78, 58%), abnormal eye movements (39/78, 50%), and hemiplegic episodes (37/78, 47%). Common comorbidities included epilepsy (21/88, 24%), cognitive impairment (41/88, 47%), and neuropsychiatric disorders. Only 22 of 88 (25%) fulfilled criteria for a single canonical phenotype; 28 of 88 (32%) met canonical criteria plus additional features, 18 of 88 (20%) satisfied criteria for ≥2 canonical phenotypes, and 20 of 88 (23%) fit no canonical category. We identified 43 distinct ATP1A3 variants; recurrent variants (eg, p.Arg756His, p.Asp801Asn, p.Glu818Lys) showed variable expressivity across categories.
CONCLUSIONS: The extensive clinical heterogeneity in ATP1A3-related disorders challenges rigid phenotypic classifications. The predominance of patients with overlapping or atypical features supports a shift toward flexible, symptom-based clinical approaches rather than strict reliance on canonical phenotype recognition. © 2026 International Parkinson and Movement Disorder Society.
PMID:41850905 | DOI:10.1002/mds.70227