ArticleParkinsonism & related disorders2022
Natural speech markers of Alzheimer's disease co-pathology in Lewy body dementias.
Article in Parkinsonism & related disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Digital Biomarkers for the Assessment of Non-Cognitive Symptoms in Patients with Dementia with Lewy Bodies: A Systematic Review.Journal of Alzheimer's disease : JAD · 2024Pooled it
- Where do PDD and DLB SYNdromes fit in neuronal alpha-SYNuclein biological frameworks?Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- The Utility of Speech and Language Analytics for Screening Alzheimer's Disease.Neuro-degenerative diseases · 2026Review
- Automatic classification of AD pathology in FTD phenotypes using natural speech.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Speech patterns during memory recall relates to early tau burden across adulthood.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Evaluation of ATNNeurology · 2024Article
- Changes in Digital Speech Measures in Asymptomatic Carriers of Pathogenic Variants Associated With Frontotemporal Degeneration.Neurology · 2024Article
- Plasma GFAP associates with secondary Alzheimer's pathology in Lewy body disease.Annals of clinical and translational neurology · 2023Article
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Authors and funding
15 authors at 5 institutions in 1 country.
Funding
Abstract
introductionAn estimated 50% of patients with Lewy body dementias (LBD), including Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB), have co-occurring Alzheimer's disease (AD) that is associated with worse prognosis. This study tests an automated analysis of natural speech as an inexpensive, non-invasive screening tool for AD co-pathology in biologically-confirmed cohorts of LBD patients with AD co-pathology (SYN + AD) and without (SYN-AD).
methodsWe analyzed lexical-semantic and acoustic features of picture descriptions using automated methods in 22 SYN + AD and 38 SYN-AD patients stratified using AD CSF biomarkers or autopsy diagnosis. Speech markers of AD co-pathology were identified using best subset regression, and their diagnostic discrimination was tested using receiver operating characteristic. ANCOVAs compared measures between groups covarying for demographic differences and cognitive disease severity. We tested relations with CSF tau levels, and compared speech measures between PDD and DLB clinical disorders in the same cohort.
resultsAge of acquisition of nouns (p = 0.034, |d| = 0.77) and lexical density (p = 0.0064, |d| = 0.72) were reduced in SYN + AD, and together showed excellent discrimination for SYN + AD vs. SYN-AD (95% sensitivity, 66% specificity; AUC = 0.82). Lower lexical density was related to higher CSF t-Tau levels (R = -0.41, p = 0.0021). Clinically-diagnosed PDD vs. DLB did not differ on any speech features.
conclusionAD co-pathology may result in a deviant natural speech profile in LBD characterized by specific lexical-semantic impairments, not detectable by clinical disorder diagnosis. Our study demonstrates the potential of automated digital speech analytics as a screening tool for underlying AD co-pathology in LBD.
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