Coordination and timing deficits in speech and swallowing in autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS)

Perceptual and Acoustic Analysis of Speech in Spinocerebellar ataxia Type 1

This study characterizes the speech phenotype of spinocerebellar ataxia type 1 (SCA1) using both perceptual and objective acoustic analysis of speech in a cohort of SCA1 patients. Twenty-seven symptomatic SCA1 patients in various disease stages (SARA score range: 3-32 points) and 18 sex and age matched healthy controls underwent a clinical assessment addressing ataxia severity, non-ataxia signs, cognitive functioning, and speech. Speech samples were perceptually rated by trained speech therapists, and acoustic metrics representing speech timing, vocal control, and voice quality were extracted. Perceptual analysis revealed reduced intelligibility and naturalness in speech samples of SCA1 patients. Acoustically, SCA1 patients presented with slower speech rate and diadochokinetic rate as well as longer syllable duration compared to healthy controls. No distinct abnormalities in voice quality in the acoustic analysis were detected at group level. Both the affected perceptual and acoustic variables correlated with ataxia severity. Longitudinal assessment of speech is needed to place changes in speech in the context of disease progression and potential response to treatment.

Disease Delineation for Multiple Sclerosis, Friedreich Ataxia, and Healthy Controls Using Supervised Machine Learning on Speech Acoustics

Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.

SARAspeech-Feasibility of automated assessment of ataxic speech disturbance

Ataxias are a group of movement disorders that are characterized by progressive loss of balance, impaired coordination and speech disturbance, which together lead to markedly reduced quality of life. Speech disturbance is clinically diagnosed, but methods for objective assessment of severity are lacking. Using 71 sets of speech recordings from ataxia patients, we developed an automated classification system. With a tolerance of ±1 point, this classification system correctly predicted experts' ratings of speech disturbance according to item 4 of the Scale for Assessment and rating of ataxia (SARA) in 80% of cases. We thereby demonstrate feasibility of computer-assisted voice analysis for automated assessment of severity of speech disturbance.

The efficacy of acoustic-based articulatory phenotyping for characterizing and classifying four divergent neurodegenerative diseases using sequential motion rates

Despite the impacts of neurodegeneration on speech function, little is known about how to comprehensively characterize the resulting speech abnormalities using a set of objective measures. Quantitative phenotyping of speech motor impairments may have important implications for identifying clinical syndromes and their underlying etiologies, monitoring disease progression over time, and improving treatment efficacy. The goal of this research was to investigate the validity and classification accuracy of comprehensive acoustic-based articulatory phenotypes in speakers with distinct neurodegenerative diseases. Articulatory phenotypes were characterized based on acoustic features that were selected to represent five components of motor performance: Coordination, Consistency, Speed, Precision, and Rate. The phenotypes were first used to characterize the articulatory abnormalities across four progressive neurologic diseases known to have divergent speech motor deficits: amyotrophic lateral sclerosis (ALS), progressive ataxia (PA), Parkinson's disease (PD), and the nonfluent variant of primary progressive aphasia and progressive apraxia of speech (nfPPA + PAOS). We then examined the efficacy of articulatory phenotyping for disease classification. Acoustic analyses were conducted on audio recordings of 217 participants (i.e., 46 ALS, 52 PA, 60 PD, 20 nfPPA + PAOS, and 39 controls) during a sequential speech task. Results revealed evidence of distinct articulatory phenotypes for the four clinical groups and that the phenotypes demonstrated strong classification accuracy for all groups except ALS. Our results highlight the phenotypic variability present across neurodegenerative diseases, which, in turn, may inform (1) the differential diagnosis of neurological diseases and (2) the development of sensitive outcome measures for monitoring disease progression or assessing treatment efficacy.

Documenting manifestations and impacts of autosomal recessive spastic ataxia of Charlevoix-Saguenay to develop patient-reported outcome

BACKGROUND

Autosomal recessive cerebellar ataxias (ARCA) are a group of rare inherited disorders characterized by degeneration or abnormal development of the cerebellum. Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is one of the most prevalent in Europe.

OBJECTIVES

The aim of this study is to provide a better understanding of the manifestations and impacts of ARSACS.

METHODS

A systematic review of the literature was conducted, followed by a qualitative study using semistructured interviews and discussion groups to obtain the experience of people affected.

RESULTS

According to the PROMIS framework, the results show manifestations and impacts in three components of health: physical, mental, and social. Fatigue and struggles with balance and dexterity are the physical manifestations of the disease most often cited by participants. Negative affects such as frustration and depression are among the mental health impacts with some loss in cognitive abilities. Social health is the least documented component; nonetheless, people with the disease report significant impacts in terms of social relationships, activities and work.

CONCLUSIONS

These findings shed new light on the experience of people with recessive ataxia and identify key aspects to assess to improve their overall health.

Discovery of Therapeutics Targeting Oxidative Stress in Autosomal Recessive Cerebellar Ataxia: A Systematic Review

Autosomal recessive cerebellar ataxias (ARCAs) are a heterogeneous group of rare neurodegenerative inherited disorders. The resulting motor incoordination and progressive functional disabilities lead to reduced lifespan. There is currently no cure for ARCAs, likely attributed to the lack of understanding of the multifaceted roles of antioxidant defense and the underlying mechanisms. This systematic review aims to evaluate the extant literature on the current developments of therapeutic strategies that target oxidative stress for the management of ARCAs. We searched PubMed, Web of Science, and Science Direct Scopus for relevant peer-reviewed articles published from 1 January 2016 onwards. A total of 28 preclinical studies fulfilled the eligibility criteria for inclusion in this systematic review. We first evaluated the altered cellular processes, abnormal signaling cascades, and disrupted protein quality control underlying the pathogenesis of ARCA. We then examined the current potential therapeutic strategies for ARCAs, including aromatic, organic and pharmacological compounds, gene therapy, natural products, and nanotechnology, as well as their associated antioxidant pathways and modes of action. We then discussed their potential as antioxidant therapeutics for ARCAs, with the long-term view toward their possible translation to clinical practice. In conclusion, our current understanding is that these antioxidant therapies show promise in improving or halting the progression of ARCAs. Tailoring the therapies to specific disease stages could greatly facilitate the management of ARCAs.

Acoustic Speech Analytics Are Predictive of Cerebellar Dysfunction in Multiple Sclerosis

Speech production relies on motor control and cognitive processing and is linked to cerebellar function. In diseases where the cerebellum is impaired, such as multiple sclerosis (MS), speech abnormalities are common and can be detected by instrumental assessments. However, the potential of speech assessments to be used to monitor cerebellar impairment in MS remains unexplored. The aim of this study is to build an objectively measured speech score that reflects cerebellar function, pathology and quality of life in MS. Eighty-five people with MS and 21 controls participated in the study. Speech was independently assessed through objective acoustic analysis and blind expert listener ratings. Cerebellar function and overall disease disability were measured through validated clinical scores; cerebellar pathology was assessed via magnetic resonance imaging, and validated questionnaires informed quality of life. Selected speech variables were entered in a regression model to predict cerebellar function. The resulting model was condensed into one composite speech score and tested for prediction of abnormal 9-hole peg test (9HPT), and for correlations with the remaining cerebellar scores, imaging measurements and self-assessed quality of life. Slow rate of syllable repetition and increased free speech pause percentage were the strongest predictors of cerebellar impairment, complemented by phonatory instability. Those variables formed the acoustic composite score that accounted for 54% of variation in cerebellar function, correlated with cerebellar white matter volume (r = 0.3, p = 0.017), quality of life (r = 0.5, p < 0.001) and predicted an abnormal 9HPT with 85% accuracy. An objective multi-feature speech metric was highly representative of motor cerebellar impairment in MS.

Using Voice Change as an Indicator of Dysphagia: A Systematic Review

Voice change post-swallow, observed during a clinical swallow examination, is often used as a clinical indicator of dysphagia risk. However, there has been limited research that evaluated the level of agreement between voice change and swallow dysfunction reported to date. This systematic review aims to investigate existing evidence relating to the relationship between vocal change post-swallow and swallow deficits identified on a Videofluoroscopic Swallow Study (VFSS). The studies were selected by two independent evaluators for inclusion, without restriction on language or date of publication and the methodological quality and the risk of bias were assessed using QUADAS-2. Following the PRISMA recommendation, 271 articles were analyzed, of which 17 were included in the study. Of these, the methodology described in five studies employed voice analyses using only acoustic methods, seven others conducted only auditory-perceptual analyses, and five other studies used both. Across the studies there was no homogeneity in the voice quality parameters assessed, analytic methods used, and results obtained. Forty seven per cent of the studies presented a high risk of bias in the analysis of vocal quality due to lack of clarity and blinding of VFSS. There was no homogeneity in the choice of consistencies evaluated during swallowing, as well as standardization of the outcome investigated in VFSS without a vocal parameter attributable to accurate detection in each outcome. It is not possible to obtain a consensus regarding the recommendation of the use of vocal evaluation as an accurate method for identifying swallowing alterations due to heterogeneity of the vocal evaluation methods, the outcomes evaluated in the VFSS examination, heterogeneity in food and liquid consistencies, and the methodological quality of the studies.

Assessment of muscular strength and functional capacity in the juvenile and adult myotonic dystrophy type 1 population: a 3-year follow-up study

INTRODUCTION

Myotonic dystrophy type 1 (DM1) is a progressive, multisystemic, and autosomal dominant disease. Muscle wasting and weakness have been associated with impaired functional capacity and restricted social participation in affected individuals. The disease's presentation is very heterogenous and its progression is still under-documented.

OBJECTIVE

The aim of the study was to document the progression of muscular strength and functional capacity in the DM1 population over a 3-year period.

METHODS

Twenty-three individuals with juvenile or adult phenotypes of DM1 were recruited to complete clinical assessments in 2016 and 2019. Maximal isometric muscle strength (MIMS) was evaluated with quantified muscle testing and functional capacity was evaluated with the Mini-BESTest, the 10-m walk test at comfortable and maximal speeds, the Timed Up and Go and the 6-min walk test. Participants also completed three questionnaires: DM1-Activ, Upper Extremity Functional Index and Lower Extremity Functional Scale (LEFS). Subgroup analyses were evaluated for sex, phenotype, and type of physical activity practiced during the 3-year period.

RESULTS

For the whole group, there was a significant decline in the scores of the Mini-BESTest and the LEFS. Also, MIMS significantly declined for prehension, lateral pinch as well as for hip abductors, knee extensors and ankle dorsiflexors muscle groups. Subgroups analyses revealed that men lost more MIMS than women, and that adult phenotype lost more MIMS than juvenile phenotype.

CONCLUSION

Quantified muscle testing is a better indicator of disease progression over a 3-year period than functional tests. Phenotype and sex are important factors that influence the progression of DM1.

Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning

Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and response to therapies. Assessments are limited as they require an in-person evaluation by a neurology subspecialist or specialized and expensive equipment. We tested the hypothesis that important eye movement abnormalities in cerebellar disorders (i.e., ataxias) could be captured from iPhone video. Videos of the face were collected from individuals with ataxia (n = 102) and from a comparative population (Parkinson's disease or healthy participants, n = 61). Computer vision algorithms were used to track the position of the eye which was transformed into high temporal resolution spectral features. Machine learning models trained on eye movement features were able to identify abnormalities in smooth pursuit (a key eye behavior) and accurately distinguish individuals with abnormal pursuit from controls (sensitivity = 0.84, specificity = 0.77). A novel machine learning approach generated severity estimates that correlated well with the clinician scores. We demonstrate the feasibility of capturing eye movement information using an inexpensive and widely accessible technology. This may be a useful approach for disease screening and for measuring severity in clinical trials.

Features of speech and swallowing dysfunction in pre-ataxic spinocerebellar ataxia type 2

OBJECTIVE

To determine whether objective and quantitative assessment of dysarthria and dysphagia in spinocerebellar ataxia type 2 (SCA2), specifically at pre-ataxic and early disease phases, can act as sensitive disease markers.

METHODS

Forty-six individuals (16 with pre-ataxic SCA2, 14 with early-stage ataxic SCA2, and 16 healthy controls) were recruited in Holguin, Cuba. All participants underwent a comprehensive battery of assessments including objective acoustic analysis, clinician-derived ratings of speech function and swallowing, and quality of life assessments of swallowing.

RESULTS

Reduced speech agility manifest at the pre-ataxic stage was observed during diadochokinetic tasks, with the magnitude of speech deficit augmented in the early ataxic stage. Speech rate was slower in early-stage ataxic SCA2 compared with pre-ataxic SCA2 and healthy controls. Reduced speech agility and speech rate correlated with disease severity and time to ataxia onset, verifying that speech deficits occur prior to ataxia onset and increase in severity as the disease progresses. Whereas dysphagia was observed in both pre-ataxic and ataxic SCA2, it was not associated with swallowing-related quality of life, disease severity, or time to ataxia onset.

CONCLUSIONS

Speech and swallowing deficits appear sensitive to disease progression in early-stage SCA2, with syllabic rate a viable marker. Findings provide insight into mechanisms of disease progression in early-stage SCA2, signaling an opportunity for stratifying early-stage SCA2 and identifying salient markers of disease onset as well as outcome measures in future early-stage therapeutic studies.

Quantitative Assessment of Speech in Cerebellar Ataxia Using Magnitude and Phase Based Cepstrum

The clinical assessment of speech abnormalities in Cerebellar Ataxia (CA) is time-consuming and inconsistent. We have developed an automated objective system to quantify CA severity and thereby facilitate remote monitoring and optimisation of therapeutic interventions. A quantitative acoustic assessment could prove to be a viable biomarker for this purpose. Our study explores the use of phase-based cepstral features extracted from the modified group delay function as a complement to the features obtained from the magnitude cepstrum. We selected a combination of 15 acoustic measurements using RELIEF feature selection algorithm during the feature optimisation process. These features were used to segregate ataxic speakers from normal speakers (controls) and objectively assess them based on their severity. The effectiveness of our study has been experimentally evaluated through a clinical study involving 42 patients diagnosed with CA and 23 age-matched controls. A radial basis function kernel based support vector machine (SVM) classifier achieved a classification accuracy of 84.6% in CA-Control discrimination [area under the ROC curve (AUC) of 0.97] and 74% in the modified 3-level CA severity estimation (AUC of 0.90) deduced from the clinical ratings. The strong classification ability of selected features and the SVM model supports this scheme's suitability for monitoring CA related speech motor abnormalities.