Idiopathic cerebellar ataxia (IDCA): Diagnostic criteria and clinical analyses of 63 Japanese patients

[Recent clinical advances in hereditary spinocerebellar degeneration]

Spinocerebellar degeneration (SCD) is a neurodegenerative disorder characterized by cerebellar ataxia and other multisystem manifestations, such as Parkinsonism and pyramidal tract symptoms. No effective treatment is available for SCD. Approximately one-third of the cases of SCD are inherited, and the remaining two-third are sporadic, including multiple system atrophy. This article provides an overview of hereditary SCD, its clinical features, recent treatment advances, biomarkers, role of genomic medicine, and future treatment prospects.

A retrospective study of autoimmune cerebellar ataxia over a 20-year period in a single institution

BACKGROUND

It is important to differentiate autoimmune cerebellar ataxia (ACA) from neurodegenerative CA, but this is sometimes difficult. We performed a retrospective study in a single institution in Japan over a 20-year period to reveal the clinical features of ACA.

METHODS

Patients with CA as the primary neurological symptom were enrolled from those admitted to the Department of Neurology, Hokkaido University Hospital between April 2002 and March 2022. ACA was diagnosed retrospectively according to the following criteria: (1) CA being the predominant symptom; (2) identification of cancer within 2 years of onset; (3) improvement in cerebellar symptoms following immunotherapy; and (4) ruling out alternative causes of CA. Patients fulfilling criteria (1), (2), and (4) were classified as paraneoplastic cerebellar degeneration (PCD), while those fulfilling (1), (3), and (4) were classified as non-PCD and enrolled as patients with ACA. Neurodegenerative diseases, e.g., multiple system atrophy (MSA), were confirmed retrospectively based on generally used diagnostic criteria and enrolled. Furthermore, the ACA diagnostic criteria proposed by Dalmau and Graus were applied retrospectively to the ACA patients to examine the validity of the diagnoses.

RESULTS

Among the 243 patients with CA, 13 were enrolled as ACA; five were PCD and eight were non-PCD. Eight of these cases met the proposed diagnostic criteria by Dalmau and Graus. MSA was the most prevalent disease among CA patients, with 93 cases. The incidence of cerebellar atrophy was significantly lower in ACA (3/13) than in MSA (92/92). Cerebrospinal fluid (CSF) pleocytosis was significantly more frequent in ACA than in MSA (4/13 vs. 2/55, respectively). However, there was no significant difference in the presence of oligoclonal bands, increased protein in CSF, and laterality differences in ataxia.

CONCLUSION

ACA was present in ~ 5% of Japanese CA patients. The absence of cerebellar atrophy, despite the presence of CA, strongly supports ACA over MSA. While CSF pleocytosis was observed more often in ACA, the positivity rate was only ~ 30%. Since ACA is treatable, further studies are needed to identify additional clinical features and accurate diagnostic biomarkers.

A novel clinicopathologic entity causing rapidly progressive cerebellar ataxia?

Sporadic, adult-onset cerebellar ataxia is a disease with multiple etiologies. In addition to cortical cerebellar atrophy (CCA), which is often used for the pathological diagnosis, other terms such as idiopathic late-onset cerebellar ataxia (ILOCA) and sporadic adult-onset ataxia of unknown etiology (SAOA) have been used to refer to this disorder. These names describe key features of the disease, including degeneration limited to the cerebellar cortex (with or without secondary involvement of inferior olivary nuclei), a slowly progressive ataxia, and absence of a clear etiology, such as multiple system atrophy, as well as paraneoplastic, autoimmune, infectious and inherited ataxias. In this Point of View article, we describe two patients with sporadic, adult-onset ataxia with rapidly progressive disease course in addition to extracerebellar symptoms resembling prion disease, including the reevaluation of one patient who was previously reported. Pathological findings are mostly consistent with CCA, but also have degenerative changes in the thalamus. Whole genome sequencing in two patients with rapidly progressive CCA did not reveal any pathogenic variants associated with cerebellar ataxia. Although the underlying etiology behind rapidly progressive CCA is unknown, we suggest that the unique combination of clinical and pathological features of CAA with a short disease course defines a new disease entity, rapidly progressive cerebellar cortical and thalamic degeneration. This viewpoint article draws attention to this rare sporadic cerebellar ataxia with the hope that highlighting clinical and pathologic findings in a typical case will lead to improved recognition and research.

Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks

Dysarthria may present during the natural course of many degenerative neurological conditions. Hypokinetic and ataxic dysarthria are common in movement disorders and represent the underlying neuropathology. We developed an artificial intelligence (AI) model to distinguish ataxic dysarthria and hypokinetic dysarthria from normal speech and differentiate ataxic and hypokinetic speech in parkinsonian diseases and cerebellar ataxia. We screened 804 perceptual speech analyses performed in the Samsung Medical Center Neurology Department between January 2017 and December 2020. The data of patients diagnosed with parkinsonian disorders or cerebellar ataxia were included. Two speech tasks (numbering from 1 to 50 and reading nine sentences) were analyzed. We adopted convolutional neural networks and developed a patch-wise wave splitting and integrating AI system for audio classification (PWSI-AI-AC) to differentiate between ataxic and hypokinetic speech. Of the 395 speech recordings for the reading task, 76, 112, and 207 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. Of the 409 recordings of the numbering task, 82, 111, and 216 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. The reading and numbering task recordings were classified with 5-fold cross-validation using PWSI-AI-AC as follows: hypokinetic dysarthria vs. others (area under the curve: 0.92 ± 0.01 and 0.92 ± 0.02), ataxia vs. others (0.93 ± 0.04 and 0.89 ± 0.02), hypokinetic dysarthria vs. ataxia (0.96 ± 0.02 and 0.95 ± 0.01), hypokinetic dysarthria vs. none (0.86 ± 0.03 and 0.87 ± 0.05), and ataxia vs. none (0.87 ± 0.07 and 0.87 ± 0.09), respectively. PWSI-AI-AC showed reliable performance in differentiating ataxic and hypokinetic dysarthria and effectively augmented data to classify the types even with limited training samples. The proposed fully automatic AI system outperforms neurology residents. Our model can provide effective guidelines for screening related diseases and differential diagnosis of neurodegenerative diseases.

Differential diagnosis between Parkinson's disease and atypical parkinsonism based on gait and postural instability: Artificial intelligence using an enhanced weight voting ensemble model

BACKGROUND

Parkinsonian diseases and cerebellar ataxia among movement disorders, are representative diseases which present with distinct pathological gaits. We proposed a machine learning system that can differentiate Parkinson's disease (PD), cerebellar ataxia and progressive supranuclear palsy Richardson syndrome (PSP-RS) based on postural instability and gait analysis.

METHODS

We screened 1467 gait (GAITRite) and postural instability (Pedoscan) analyses performed in Samsung Medical Center from January 2019 to December 2020. PD, probable PSP-RS, and cerebellar ataxia (i.e., probable MSA-C, hereditary ataxia, and sporadic adult-onset ataxia) were included in the study. The gated recurrent units for GaitRite and the deep neural network for Pedoscan were applied. The enhanced weight voting ensemble (EWVE) method was applied to incorporate the two modalities.

RESULTS

We included 551 PD, 38 PSP-RS, 113 cerebellar ataxia and among them, 71 were MSA-C. Pedoscan-based and Gait-based model showed high sensitivity but low specificity in differentiating atypical parkinsonism from PD. The EWVE showed significantly improved specificity and reliable performance in differentiation between PD vs. ataxia patients (AUC 0.974 ± 0.036, sensitivity 0.829 ± 0.217, specificity 0.969 ± 0.038), PD vs. MSA-C (AUC 0.975 ± 0.020, sensitivity 0.823 ± 0.162, specificity 0.932 ± 0.030) and PD vs. PSP-RS (AUC 0.963 ± 0.028, sensitivity 0.555 ± 0.157, specificity 0.936 ± 0.031).

CONCLUSION

We proposed reliable Pedoscan-based, Gait-based and EWVE model in differentiating gait disorders by integrating information from gait and postural instability. This model can provide diagnosis guidelines to primary caregivers and assist in differential diagnosis of PD from atypical parkinsonism for neurologists.

Effect of rovatirelin in patients with cerebellar ataxia: two randomised double-blind placebo-controlled phase 3 trials

OBJECTIVE

To investigate the efficacy of rovatirelin, a thyrotropin-releasing hormone analogue, for ataxias in patients with spinocerebellar degeneration (SCD).

METHODS

Two multicentre, randomised, double-blind, placebo-controlled phase 3 studies (KPS1301, KPS1305) enrolled patients with predominant cerebellar ataxia, including SCA6, SCA31 or cortical cerebellar atrophy. KPS1301 enrolled patients with truncal ataxia and KPS1305 enrolled patients with truncal and limb ataxia. Each study included 4 weeks of pretreatment, a 28-week or 24-week treatment period and 4 weeks of follow-up. Patients were randomised (1:1:1) to rovatirelin (1.6 or 2.4 mg) or placebo in KPS1301, and randomised (1:1) to rovatirelin 2.4 mg or placebo in KPS1305. The primary endpoint was change in Scale for the Assessment and Rating of Ataxia (SARA) total scores. Pooled analysis was performed in patients who met the SARA recruitment criteria of KPS1305.

RESULTS

From October 2013 to May 2014, KPS1301 enrolled 411 patients; 374 were randomised to rovatirelin 1.6 mg (n=125), rovatirelin 2.4 mg (n=126) or placebo (n=123). From November 2016 to August 2017, KPS1305 enrolled 241 patients; 203 were randomised to rovatirelin 2.4 mg (n=101) or placebo (n=102). The primary endpoint showed no significant difference between rovatirelin and placebo in these two studies. In the pooled analysis (n=278), the difference between rovatirelin 2.4 mg (n=140) and placebo (n=138) was -0.61 (-1.64 vs -1.03; 95% CI -1.16 to -0.06; p=0.029) in the adjusted mean change in the SARA total score.

CONCLUSIONS

Rovatirelin is a potentially effective treatment option for SCD.

TRIAL REGISTRATION NUMBER

NCT01970098; NCT02889302.

Progressive Supranuclear Palsy with Predominant Cerebellar Ataxia

Progressive supranuclear palsy (PSP) is characterized by supranuclear gaze palsy, dystonic rigidity of the neck and upper trunk, frequent falls and mild cognitive impairment. Cerebellar ataxia is one of the exclusion criteria given by the National Institute of Neurological Disorders and Stroke and the Society for Progressive Supranuclear Palsy. As a result, pathologically proven PSP patients exhibiting cerebellar ataxia have often been misdiagnosed with spinocerebellar degeneration, specifically multiple system atrophy with predominant cerebellar ataxia (MSA-C). However, more recently, it has been recognized that patients with PSP can present with truncal and limb ataxia as their initial symptom and/or main manifestation. These patients can be classified as having PSP with predominant cerebellar ataxia (PSP-C), a new subtype of PSP. Since the development of this classification, patients with PSP-C have been identified primarily in Asian countries, and it has been noted that this condition is very rare in Western communities. Furthermore, the clinical features of PSP-C have been identified, enabling it to be distinguished from other subtypes of PSP and MSA-C. In this review, we describe the clinical and neuropathological features of PSP-C. The hypothesized pathophysiology of cerebellar ataxia in PSP-C is also discussed.