Diagnostic algorithm for autosomal recessive ataxia

Nuzhnyi E.P.; Abramycheva N.Yu.; Klyushnikov S.A.; Seliverstov Iu.A.; Vetchinova A.S.; Pogoda T.V.; Ershova M.V.; Fedotova E.Yu.; Illarioshkin S.N.

doi:https://doi.org/10.17116/jnevro201911909174

Nuzhnyi E.P.

Pavlov First St. Petersburg State Medical University, St. Petersburg, Russia

Abramycheva N.Yu.

Research Center of Neurology, Russian Academy of Sciences, Moscow

Klyushnikov S.A.

Research Center of Neurology, Moscow, Russia

Seliverstov Iu.A.

FGBU "Nauchnyĭ tsentr nevrologii RAMN", Moskva

Vetchinova A.S.

Research Center of Neurology, Moscow, Russia

Pogoda T.V.

Research Center of Neurology, Moscow, Russia

Ershova M.V.

Research Center of Neurology, Moscow, Russia

Fedotova E.Yu.

Research Center of Neurology, Moscow, Russia

Illarioshkin S.N.

Nauchnyĭ tsentr nevrologii RAMN

Diagnostic algorithm for autosomal recessive ataxia

Authors:

Nuzhnyi E.P., Abramycheva N.Yu., Klyushnikov S.A., Seliverstov Iu.A., Vetchinova A.S., Pogoda T.V., Ershova M.V., Fedotova E.Yu., Illarioshkin S.N.

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Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2019;119(9): 74‑82

DOI: 10.17116/jnevro201911909174

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To cite this article:

Nuzhnyi EP, Abramycheva NYu, Klyushnikov SA, et al. Diagnostic algorithm for autosomal recessive ataxia. S.S. Korsakov Journal of Neurology and Psychiatry. 2019;119(9):74‑82. (In Russ.)
https://doi.org/10.17116/jnevro201911909174

Подписка 2026 Журнал неврологии и психиатрии им. С.С. Корсакова (S.S. Korsakov Journal of Neurology and Psychiatry)

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Abstract:

Objective. To develop a complex algorithm for autosomal recessive ataxia (ARA) diagnosis applicable for Russian patients with degenerative ataxias. Material and methods. 48 patients with of presumably degenerative ataxias were examined. Clinical evaluation was performed with the use of the SARA and ICARS scales (for ataxia) and MoCA (cognitive functions), and a set of laboratory tests was carried out, including electromyography, brain MRI, and DNA analysis of mutations responsible for Friedreich’s disease and spinocerebellar ataxias (SCAs) types 1, 2, 3, 6 and 17. 28 patients underwent mutation screening using a multigenic MPS panel. Results. 8 patients (16.7%) with non-hereditary causes of ataxia were identified: cerebellar alcoholic degeneration (n = 6) and multiple system atrophy of cerebellar type (n = 2); 3 patients (6.3%) with genetic ataxias were identified using routine DNA tests, such as with SCA type 1, 2 and 17, and 9 (18.8%) patients with Friedreich’s disease. The MPS panel enabled molecular diagnosis of ARA in 8 patients (28.6%): ataxia-telangiectasia (n = 2), SANDO syndrome (n = 2), ataxia with oculomotor apraxia type 2 (n = 1), SCAR10 (n = 1), SCAR16 (n = 1), and atypical form of neuroaxonal dystrophy (n = 1). The diagnosis was not established in 20 patients. Conclusion We have proposed an appropriate algorithm for degenerative ataxia diagnosis which is recommended to be used when examining patients with sporadic and autosomal recessive cases of the disorders with dyscoordination of movements.

Keywords:

autosomal recessive ataxia

clinical presentation

genetic diagnosis

massive parallel sequencing

diagnostic algorithm

Authors:

Nuzhnyi E.P.

Pavlov First St. Petersburg State Medical University, St. Petersburg, Russia

Abramycheva N.Yu.

Research Center of Neurology, Russian Academy of Sciences, Moscow

Klyushnikov S.A.

Research Center of Neurology, Moscow, Russia

Seliverstov Iu.A.

FGBU "Nauchnyĭ tsentr nevrologii RAMN", Moskva

Vetchinova A.S.

Research Center of Neurology, Moscow, Russia

Pogoda T.V.

Research Center of Neurology, Moscow, Russia

Ershova M.V.

Research Center of Neurology, Moscow, Russia

Fedotova E.Yu.

Research Center of Neurology, Moscow, Russia

Illarioshkin S.N.

Nauchnyĭ tsentr nevrologii RAMN

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