Clinical phenotyping aids genotype prediction in hereditary ataxia: a case series
DOI:
https://doi.org/10.18203/2320-6012.ijrms20263551Keywords:
Hereditary ataxia, Spinocerebellar ataxia, SCA2, SCA3, Machado–Joseph disease, Friedreich's ataxia, ATXN2, ATXN3, Repeat expansion, Genotype-phenotype correlationAbstract
Hereditary cerebellar ataxias comprise a heterogeneous group of neurodegenerative disorders with overlapping clinical manifestations, often making accurate bedside diagnosis challenging. Careful clinical phenotyping remains essential to guide targeted genetic testing, particularly in resource limited settings. We retrospectively reviewed five patients with progressive hereditary ataxia at a tertiary care neurology centre. Detailed clinical evaluation, pedigree analysis, and comprehensive neurological examination were performed, followed by molecular genetic confirmation. The cohort included two patients with Spinocerebellar Ataxia Type 2 (SCA2), one with Spinocerebellar Ataxia Type 3 (SCA3/Machado–Joseph disease), and two with Friedreich's ataxia (FRDA). Distinctive clinical features were highly suggestive of the underlying genotype prior to molecular confirmation. Markedly slowed saccades and hyporeflexia characterized SCA2, whereas SCA3 demonstrated external ophthalmoparesis, pyramidal signs, and lower motor neuron involvement with preserved saccadic velocity. Both FRDA patients exhibited posterior column sensory loss with generalized areflexia and extensor plantar responses, consistent with corticospinal tract involvement. Pedigree analysis differentiated autosomal dominant from autosomal recessive inheritance, and repeat expansion size correlated with earlier disease onset and greater clinical severity. A systematic bedside assessment incorporating oculomotor findings, reflex pattern, sensory examination, pyramidal and lower motor neuron signs, and pedigree analysis enables reliable phenotypic differentiation among hereditary ataxias before genetic confirmation. Such an approach facilitates targeted molecular testing and optimizes diagnostic evaluation, particularly in resource-constrained settings.
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Copyright (c) 2026 Khyati S. Patel, Nehal M. Shah

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