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

T. Kouba, W. Frank, T. Tykalova, A. Mühlbäck, J. Klempíř, KS. Lindenberg, GB. Landwehrmeyer, J. Rusz

. 2023 ; 30 (5) : 1262-1271. [pub] 20230222

Language English Country England, Great Britain

Document type Journal Article, Research Support, Non-U.S. Gov't

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.

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$a Kouba, Tomas $u Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
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$a Frank, Wiebke $u Department of Neurology, University Ulm, Ulm, Germany
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$a Tykalova, Tereza $u Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
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$a Mühlbäck, Alzbeta $u Department of Neurology, University Ulm, Ulm, Germany $u Department of Neuropsychiatry, Huntington Center South, kbo-Isar-Amper-Klinikum Taufkirchen (Vils), Taufkirchen, Germany $u Department of Neurology and Center of Clinical Neuroscience, 1st Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
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