Motor speech patterns in Huntington disease

Early Language Impairment as an Integral Part of the Cognitive Phenotype in Huntington's Disease

OBJECTIVE

Huntington's disease (HD) speech/language disorders have typically been attributed to motor and executive impairment due to striatal dysfunction. In-depth study of linguistic skills and the role of extrastriatal structures in HD is scarce. This study aimed to explore the profile of language compromise in HD and identify the structural neuroimaging correlates.

METHODS

Language and structural correlates were assessed using the Mini Linguistic State Examination (MLSE) in 81 participants (20 HD-ISS 0-1, 40 HD-ISS 2-3 and 21 controls). Clinical and global cognition measures were also obtained. Imaging data included computed gray matter volume (GMV) and cortical thickness (CTh) values extracted from a general linear model with the MLSE. Correlation analyses were performed with the language components of the MLSE. Multivariate regression analyses were used to explore the predictive ability of the language components on GMV and CTh loss.

RESULTS

HD individuals showed impaired MLSE performance (84.5 ± 12.8), particularly in syntax, motor speech, and to a lesser extent, semantics and phonology. Significant associations were found between linguistic performance and the structural integrity of nodes within the temporo-parietal, fronto-parietal, and fronto-striatal lexical-semantic and syntactic networks. Correlation analyses linked motor speech and syntax with predominantly left fronto-striatal GMV and CTh clusters, while semantics had a bilateral fronto-parietal topography. Multivariate regression analyses showed language domains as independent contributing factors of GMV and CTh loss in classical language-related regions.

INTERPRETATION

Language impairment is an integral part of the HD cognitive phenotype, with severity associated with structural disintegration in extensive cortico-subcortical territories involved in language production and processing.

Huntington's Disease and Dentistry: A Review of Its Etiology, Clinical Presentation, Symptomatic Pharmacotherapy, and Dental Management

AIMS

Patients with Huntington's Disease (HD) seeking dental care often present with poor oral health. Dentists often report that few protocols exist and there is a lack of understanding on how to manage these patients in the dental office. The aim of this review is to discuss the etiology and pathophysiology, clinical presentation, and management of this condition primarily from the dental perspective.

METHODS

A detailed literature review was conducted including articles searched on PubMed and Google Scholar using relevant keywords. Inclusion criteria prioritized studies based on relevance to oral care and HD with topics including caregiver-assisted oral hygiene, fluoride, dental preventative approaches, and case studies.

RESULTS

Research reveals the significant oral health issues patients with HD suffer from including dysphagia, xerostomia, and a high caries risk. Studies illustrate the need for tailored care emphasizing long term treatment planning, preventive, and clinically relevant approaches.

CONCLUSION

This review presents the importance of a proactive, multidisciplinary strategy to dental care in HD patients. Early preventive strategies can greatly postpone the decline of oral health in this population. Future studies should focus on a conclusive dental care guideline, caregiver education initiatives, and improving access to care in this patient population.

Characterization of visual cognition in pre-manifest, manifest and reduced penetrance Huntington's disease

Cognitive and visual impairment are common in Huntington's Disease (HD) and may precede motor diagnosis. We investigate the early presence of visual cognitive deficits in 181 participants, including HD carriers (40 pre-manifest, 30 early manifest, 27 manifest, and 6 reduced penetrance) and 78 healthy controls (HC). Significant differences in visual memory were observed between reduced penetrance and pre-manifest groups (p = .003), with pre-manifest showing worse performance. Age, education, CAG repeats, motor status, executive function, and verbal fluency, accounted for up to 72.8% of the variance in general and visual cognitive functions, with motor status having the strongest impact on visual domains in HD carriers. In pre-manifest HD, visual cognitive domains were primarily influenced by executive function, verbal fluency, age, and CAG repeats, while in early and manifest stages motor status and verbal fluency becomes more influential. ROC analyses showed that especially visuospatial abilities, visual memory, and visual attention (AUC = 0.927, 0.878, 0.874, respectively) effectively differentiated HC and pre-manifest from early and manifest HD. Early assessment of visual cognitive domains, particularly visual memory, could be an early marker of cognitive decline in HD. Our findings highlight the different profiles of impairment in visual cognition across HD carriers.

Identifying time patterns in Huntington's disease trajectories using dynamic time warping-based clustering on multi-modal data

One of the principal goals of Precision Medicine is to stratify patients by accounting for individual variability. However, extracting meaningful information from Real-World Data, such as Electronic Health Records, still remains challenging due to methodological and computational issues. A Dynamic Time Warping-based unsupervised-clustering methodology is presented in this paper for the clustering of patient trajectories of multi-modal health data on the basis of shared temporal characteristics. Building on an earlier methodology, a new dimension of time-varying clinical and imaging features is incorporated, through an adapted cost-minimization algorithm for clustering on different, possibly overlapping, feature subsets. The model disease chosen is Huntington's disease (HD), characterized by progressive neurodegeneration. From a wide range of examined user-defined parameters, four case examples are highlighted to demonstrate the identified temporal patterns in multi-modal HD trajectories and to study how these differ due to the combined effects of feature weights and granularity threshold. For each identified cluster, polynomial fits that describe the time behavior of the assessed features are provided for an informative comparison, together with their averaged values. The proposed data-mining methodology permits the stratification of distinct time patterns of multi-modal health data in individuals that share a diagnosis, by employing user-customized criteria beyond the current clinical practice. Overall, this work bears implications for better analysis of individual variability in disease progression, opening doors to personalized preventative, diagnostic and therapeutic strategies.

An automatic measure for speech intelligibility in dysarthrias-validation across multiple languages and neurological disorders

Introduction

Dysarthria, a motor speech disorder caused by muscle weakness or paralysis, severely impacts speech intelligibility and quality of life. The condition is prevalent in motor speech disorders such as Parkinson's disease (PD), atypical parkinsonism such as progressive supranuclear palsy (PSP), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). Improving intelligibility is not only an outcome that matters to patients but can also play a critical role as an endpoint in clinical research and drug development. This study validates a digital measure for speech intelligibility, the ki: SB-M intelligibility score, across various motor speech disorders and languages following the Digital Medicine Society (DiMe) V3 framework.

Methods

The study used four datasets: healthy controls (HCs) and patients with PD, HD, PSP, and ALS from Czech, Colombian, and German populations. Participants' speech intelligibility was assessed using the ki: SB-M intelligibility score, which is derived from automatic speech recognition (ASR) systems. Verification with inter-ASR reliability and temporal consistency, analytical validation with correlations to gold standard clinical dysarthria scores in each disease, and clinical validation with group comparisons between HCs and patients were performed.

Results

Verification showed good to excellent inter-rater reliability between ASR systems and fair to good consistency. Analytical validation revealed significant correlations between the SB-M intelligibility score and established clinical measures for speech impairments across all patient groups and languages. Clinical validation demonstrated significant differences in intelligibility scores between pathological groups and healthy controls, indicating the measure's discriminative capability.

Discussion

The ki: SB-M intelligibility score is a reliable, valid, and clinically relevant tool for assessing speech intelligibility in motor speech disorders. It holds promise for improving clinical trials through automated, objective, and scalable assessments. Future studies should explore its utility in monitoring disease progression and therapeutic efficacy as well as add data from further dysarthrias to the validation.

Language-Independent Acoustic Biomarkers for Quantifying Speech Impairment in Huntington's Disease

PURPOSE

Changes in voice and speech are characteristic symptoms of Huntington's disease (HD). Objective methods for quantifying speech impairment that can be used across languages could facilitate assessment of disease progression and intervention strategies. The aim of this study was to analyze acoustic features to identify language-independent features that could be used to quantify speech dysfunction in English-, Spanish-, and Polish-speaking participants with HD.

METHOD

Ninety participants with HD and 83 control participants performed sustained vowel, syllable repetition, and reading passage tasks recorded with previously validated methods using mobile devices. Language-independent features that differed between HD and controls were identified. Principal component analysis (PCA) and unsupervised clustering were applied to the language-independent features of the HD data set to identify subgroups within the HD data.

RESULTS

Forty-six language-independent acoustic features that were significantly different between control participants and participants with HD were identified. Following dimensionality reduction using PCA, four speech clusters were identified in the HD data set. Unified Huntington's Disease Rating Scale (UHDRS) total motor score, total functional capacity, and composite UHDRS were significantly different for pairwise comparisons of subgroups. The percentage of HD participants with higher dysarthria score and disease stage also increased across clusters.

CONCLUSION

The results support the application of acoustic features to objectively quantify speech impairment and disease severity in HD in multilanguage studies.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25447171.

Identifying and verifying Huntington's disease subtypes: Clinical features, neuroimaging, and cytokine changes

AIMS

Huntington's disease (HD) is a progressive neurodegenerative disorder with heterogeneous clinical manifestations. Identifying distinct clinical clusters and their relevant biomarkers could elucidate the underlying disease pathophysiology.

METHODS

Following the Enroll-HD program initiated in 2018.09, we have recruited 104 HD patients (including 21 premanifest) and 31 health controls at Beijing Tiantan Hospital. Principal components analysis and k-means cluster analysis were performed to determine HD clusters. Chi-square test, one-way ANOVA, and covariance were used to identify features among these clusters. Furthermore, plasma cytokines levels and brain structural imaging were used as biomarkers to delineate the clinical features of each cluster.

RESULTS

Three clusters were identified. Cluster 1 demonstrated the most severe motor and nonmotor symptoms except for chorea, the lowest whole brain volume, the plasma levels of IL-2 were higher and significantly associated with cluster 1. Cluster 2 was characterized with the most severe chorea and the largest pallidum volume. Cluster 3 had the most benign motor symptoms but moderate psychiatric problems.

CONCLUSION

We have identified three HD clusters via clinical manifestations with distinct biomarkers. Our data shed light on better understanding about the pathophysiology of HD.

Exploring Huntington's Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review

Huntington's Disease (HD) is a devastating neurodegenerative disorder characterized by progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early and accurate diagnosis of HD is crucial for effective intervention and patient care. This comprehensive review provides a comprehensive overview of the utilization of Artificial Intelligence (AI) powered algorithms in the diagnosis of HD. This review systematically analyses the existing literature to identify key trends, methodologies, and challenges in this emerging field. It also highlights the potential of ML and DL approaches in automating HD diagnosis through the analysis of clinical, genetic, and neuroimaging data. This review also discusses the limitations and ethical considerations associated with these models and suggests future research directions aimed at improving the early detection and management of Huntington's disease. It also serves as a valuable resource for researchers, clinicians, and healthcare professionals interested in the intersection of machine learning and neurodegenerative disease diagnosis.

Voices from the past: The pioneering use of the phonograph in neurology

Since its discovery by the American inventor and industrialist Thomas Alva Edison (1847-1931) in 1877, the phonograph attracted much interest in the field of medicine. This article describes the earliest pioneering examples of the use of the phonograph in neurology. In France, the use of the phonograph for obtaining audio recordings of delusions and speech or language disturbances was first proposed by Victor Maurice Dupont (1857-1910) in 1889 and in Italy by the physician Gaetano Rummo (1853-1917), who had studied at La Salpêtrière under Jean-Martin Charcot (1825-1893). The applicability of the phonograph to the record of speech disturbances was illustrated in England by John Hughlings Jackson (1835-1911) and William Halse Rivers (1864-1922), and by William Hale White (1857-1949) and Cuthbert Hilton Golding-Bird (1848-1939) in 1891. Since then, audio recordings have been used rarely in neurology, a branch of medicine where the visual aspects dominate, to the extent that inspection can be enough to reach a definite clinical diagnosis. In the mid-20th century, the advent of audio and video recordings supplanted audio recordings alone, relegating them to a very marginal role.

Speech biomarkers in Huntington's disease: A cross-sectional study in pre-symptomatic, prodromal and early manifest stages

BACKGROUND AND PURPOSE

Motor speech alterations are a prominent feature of clinically manifest Huntington's disease (HD). Objective acoustic analysis of speech can quantify speech alterations. It is currently unknown, however, at what stage of HD speech alterations can be reliably detected. We aimed to explore the patterns and extent of speech alterations using objective acoustic analysis in HD and to assess correlations with both rater-assessed phenotypical features and biological determinants of HD.

METHODS

Speech samples were acquired from 44 premanifest (29 pre-symptomatic and 15 prodromal) and 25 manifest HD gene expansion carriers, and 25 matched healthy controls. A quantitative automated acoustic analysis of 10 speech dimensions was performed.

RESULTS

Automated speech analysis allowed us to differentiate between participants with HD and controls, with areas under the curve of 0.74 for pre-symptomatic, 0.92 for prodromal, and 0.97 for manifest stages. In addition to irregular alternating motion rates and prolonged pauses seen only in manifest HD, both prodromal and manifest HD displayed slowed articulation rate, slowed alternating motion rates, increased loudness variability, and unstable steady-state position of articulators. In participants with premanifest HD, speech alteration severity was associated with cognitive slowing (r = -0.52, p < 0.001) and the extent of bradykinesia (r = 0.43, p = 0.004). Speech alterations correlated with a measure of exposure to mutant gene products (CAG-age-product score; r = 0.60, p < 0.001).

CONCLUSION

Speech abnormalities in HD are associated with other motor and cognitive deficits and are measurable already in premanifest stages of HD. Therefore, automated speech analysis might represent a quantitative HD biomarker with potential for assessing disease progression.

Listener Detection of Objectively Validated Acoustic Features of Speech in Huntington's Disease

BACKGROUND

Subtle progressive changes in speech motor function and cognition begin prior to diagnosis of Huntington's disease (HD).

OBJECTIVE

To determine the nature of listener-rated speech differences in premanifest and early-stage HD (i.e., PreHD and EarlyHD), compared to neurologically healthy controls.

METHODS

We administered a speech battery to 60 adults (16 people with PreHD, 14 with EarlyHD, and 30 neurologically healthy controls), and conducted a cognitive test of processing speed/visual attention, the Symbol Digit Modalities Test (SDMT) on participants with HD. Voice recordings were rated by expert listeners and analyzed for acoustic and perceptual speech features.

RESULTS

Listeners perceived subtle differences in the speech of PreHD compared to controls, including abnormal pitch level and speech rate, reduced loudness and loudness inflection, altered voice quality, hypernasality, imprecise articulation, and reduced naturalness of speech. Listeners detected abnormal speech rate in PreHD compared to healthy speakers on a reading task, which correlated with slower speech rate from acoustic analysis and a lower cognitive performance score. In early-stage HD, continuous speech was characterized by longer pauses, a higher proportion of silence, and slower rate.

CONCLUSION

Differences in speech and voice acoustic features are detectable in PreHD by expert listeners and align with some acoustically-derived objective speech measures. Slower speech rate in PreHD suggests altered oral motor control and/or subtle cognitive deficits that begin prior to diagnosis. Speakers with EarlyHD exhibited more silences compared to the PreHD and control groups, raising the likelihood of a link between speech and cognition that is not yet well characterized in HD.

Dysarthria Subgroups in Talkers with Huntington's Disease: Comparison of Two Data-Driven Classification Approaches

Although researchers have recognized the need to better account for the heterogeneous perceptual speech characteristics among talkers with the same disease, guidance on how to best establish such dysarthria subgroups is currently lacking. Therefore, we compared subgroup decisions of two data-driven approaches based on a cohort of talkers with Huntington's disease (HD): (1) a statistical clustering approach (STATCLUSTER) based on perceptual speech characteristic profiles and (2) an auditory free classification approach (FREECLASS) based on listeners' similarity judgments. We determined the amount of overlap across the two subgrouping decisions and the perceptual speech characteristics driving the subgrouping decisions of each approach. The same speech samples produced by 48 talkers with HD were used for both grouping approaches. The STATCLUSTER approach had been conducted previously. The FREECLASS approach was conducted in the present study. Both approaches yielded four dysarthria subgroups, which overlapped between 50% to 78%. In both grouping approaches, overall bizarreness and speech rate characteristics accounted for the grouping decisions. In addition, voice abnormalities contributed to the grouping decisions in the FREECLASS approach. These findings suggest that apart from overall bizarreness ratings, indexing dysarthria severity, speech rate and voice characteristics may be important features to establish dysarthria subgroups in HD.

The oral manifestations of Huntington's disease: A systematic review of prevalence

OBJECTIVES

The objective of this systematic literature review was to provide a complete panorama of the oral manifestations of Huntington's disease (HD).

MATERIALS AND METHODS

Databases were searched, and original research studies or case report manuscripts up to May 2021 were included using keywords that describe HD combined with words related to oral health; MeSH terms were used exclusively. No time or language restrictions were applied.

RESULTS

Twenty-two investigations (12 original articles and 10 case reports) regarding oral manifestations of HD were included. The subjects examined in the selected research articles were dental health, coordination of oral structures, speech, dysphagia, and swallowing alterations. The case reports described dental treatment procedures, oromandibular dyskinesia, dysphagia, and speech alterations.

CONCLUSIONS

The oral manifestations of HD were found to be associated with the advance of the disease in that the more severe the HD, the worse the alterations affecting the oral cavity. Dysphagia, dysarthria, masticatory problems, oral health impairment, and choreiform movements involving the tongue and other orofacial muscles were the main manifestations of HD in the oral cavity. The PROSPERO systematic review registration number of this study is CRD42021238934.

GEORGE®: A Pilot Study of a Smartphone Application for Huntington's Disease

BACKGROUND

Current Huntington's disease (HD) measures are limited to subjective, episodic assessments conducted in clinic. Smartphones can enable the collection of objective, real-world data but their use has not been extensively evaluated in HD.

OBJECTIVE

Develop and evaluate a smartphone application to assess feasibility of use and key features of HD in clinic and at home.

METHODS

We developed GEORGE®, an Android smartphone application for HD which assesses voice, chorea, balance, gait, and finger tapping speed. We then conducted an observational pilot study of individuals with manifest HD, prodromal HD, and without a movement disorder. In clinic, participants performed standard clinical assessments and a battery of active tasks in GEORGE. At home, participants were instructed to complete the activities thrice daily for one month. Sensor data were used to measure chorea, tap rate, and step count. Audio data was not analyzed.

RESULTS

Twenty-three participants (8 manifest HD, 5 prodromal HD, 10 controls) enrolled, and all but one completed the study. On average, participants used the application 2.1 times daily. We observed a significant difference in chorea score (HD: 19.5; prodromal HD: 4.5, p = 0.007; controls: 4.3, p = 0.001) and tap rate (HD: 2.5 taps/s; prodromal HD: 8.9 taps/s, p = 0.001; controls: 8.1 taps/s, p = 0.001) between individuals with and without manifest HD. Tap rate correlated strongly with the traditional UHDRS finger tapping score (left hand: r = -0.82, p = 0.022; right hand: r = -0.79, p = 0.03).

CONCLUSION

GEORGE is an acceptable and effective tool to differentiate individuals with and without manifest HD and measure key disease features. Refinement of the application's interface and activities will improve its usability and sensitivity and, ideally, make it useful for clinical care and research.

State-of-the-art pharmacological approaches to reduce chorea in Huntington's disease

Introduction Chorea is a common motor manifestation of Huntington's disease (HD). Two vesicular monoamine transporter type 2 (VMAT-2) inhibitors have been approved by the FDA for treatment of HD chorea, and a third is currently being assessed in a phase 3 trial. Antipsychotic therapies are used off-label for treatment of chorea and can treat comorbid psychiatric symptoms. There is considerable clinical equipoise regarding the safe and effective treatment of chorea and comorbid symptoms in HD.Areas covered: The authors review existing medications used to treat HD chorea in the United States of America (USA). Implications for common comorbid symptoms (e.g. psychiatric, metabolic) are also discussed. Available therapies vary widely in cost, dosing frequency, and off -target effects, both beneficial or negative.Expert opinion: Treatment considerations for chorea should account for patient comorbidities. The authors recommend prospective, observational clinical effectiveness studies which can evaluate the long-term comparative effectiveness and safety of VMAT-2 inhibitors and antipsychotics in HD. Data regarding safety of dual therapy is another critical need. This is especially timely given the changing landscape of HD therapies which may increase cost burden and possibly extend both asymptomatic and symptomatic years for HD patients.

Striatum and language processing: Where do we stand?

More than a century ago, Broca (1861), Wernicke (1874) and Lichteim (1885) laid the foundations for the first anatomo-functional model of language, secondarily enriched by Geschwind (1967), leading to the Broca-Wernicke-Lichteim-Geschwind model. This model included the frontal, parietal, and temporal cortices as well as a subcortical structure, which could be the striatum, whose nature and role have remained unclear. Although the emergence of language deficits in patients with striatal injury has challenged the cortical language models developed over the past 30 years, the integration of the striatum into language processing models remains rare. The main argument for not including the striatum in language processing is that the disorders observed in patients with striatal dysfunction may result from the striatal role in cognitive functions beyond language, and not from the impairment of language itself. Indeed, unraveling the role of the striatum and the frontal cortex, linked by the fronto-striatal pathway, is a challenge. Here, we first reviewed the studies that explored the link between striatal functions and the different levels of language (phonetics, phonology, morphology, syntax, and lexico-semantics). We then looked at the language models, which included the striatum, and found that none of them captured the diversity of experimental data in this area. Finally, we propose an integrative anatomo-functional model of language processing combining traditional language processing levels and some "executive" functions, known to improve the efficiency and fluidity of language: control, working memory, and attention. We argue that within this integrative model, the striatum is a central node of a verbal executive network that regulates, monitors, and controls the allocations of limited cognitive resources (verbal working memory and verbal attention), whatever the language level. This model combines data from neurology, psycholinguistics, and cognitive science.

Classification of Manifest Huntington Disease using Vowel Distortion Measures

Huntington disease (HD) is a fatal autosomal dominant neurocognitive disorder that causes cognitive disturbances, neuropsychiatric symptoms, and impaired motor abilities (e.g., gait, speech, voice). Due to its progressive nature, HD treatment requires ongoing clinical monitoring of symptoms. Individuals with the Huntingtin gene mutation, which causes HD, may exhibit a range of speech symptoms as they progress from premanifest to manifest HD. Speech-based passive monitoring has the potential to augment clinical information by more continuously tracking manifestation symptoms. Differentiating between premanifest and manifest HD is an important yet under-studied problem, as this distinction marks the need for increased treatment. In this work we present the first demonstration of how changes in speech can be measured to differentiate between premanifest and manifest HD. To do so, we focus on one speech symptom of HD: distorted vowels. We introduce a set of Filtered Vowel Distortion Measures (FVDM) which we extract from read speech. We show that FVDM, coupled with features from existing literature, can differentiate between premanifest and manifest HD with 80% accuracy.