Automatic classification of AD pathology in FTD phenotypes using natural speech.

INTRODUCTION: Screening for Alzheimer's disease neuropathologic change (ADNC) in individuals with atypical presentations is challenging but essential for clinical management. We trained automatic speech-based classifiers to distinguish frontotemporal dementia (FTD) patients with ADNC from those with frontotemporal lobar degeneration (FTLD). METHODS: We trained automatic classifiers with 99 speech features from 1 minute speech samples of 179 participants (ADNC = 36, FTLD = 60, healthy controls [HC] = 89). Patients' pathology was assigned based on autopsy or cerebrospinal fluid analytes. Structural network-based magnetic resonance imaging analyses identified anatomical correlates of distinct speech features. RESULTS: Our classifier showed 0.88 ± $ \pm $ 0.03 area under the curve (AUC) for ADNC versus FTLD and 0.93 ± $ \pm $ 0.04 AUC for patients versus HC. Noun frequency and pause rate correlated with gray matter volume loss in the limbic and salience networks, respectively. DISCUSSION: Brief naturalistic speech samples can be used for screening FTD patients for underlying ADNC in vivo. This work supports the future development of digital assessment tools for FTD. HIGHLIGHTS: We trained machine learning classifiers for frontotemporal dementia patients using natural speech. We grouped participants by neuropathological diagnosis (autopsy) or cerebrospinal fluid biomarkers. Classifiers well distinguished underlying pathology (Alzheimer's disease vs. frontotemporal lobar degeneration) in patients. We identified important features through an explainable artificial intelligence approach. This work lays the groundwork for a speech-based neuropathology screening tool.

Automated Measures of Syntactic Complexity in Natural Speech Production: Older and Younger Adults as a Case Study.

PURPOSE: Multiple methods have been suggested for quantifying syntactic complexity in speech. We compared eight automated syntactic complexity metrics to determine which best captured verified syntactic differences between old and young adults. METHOD: We used natural speech samples produced in a picture description task by younger (n = 76, ages 18-22 years) and older (n = 36, ages 53-89 years) healthy participants, manually transcribed and segmented into sentences. We manually verified that older participants produced fewer complex structures. We developed a metric of syntactic complexity using automatically extracted syntactic structures as features in a multidimensional metric. We compared our metric to seven other metrics: Yngve score, Frazier score, Frazier-Roark score, developmental level, syntactic frequency, mean dependency distance, and sentence length. We examined the success of each metric in identifying the age group using logistic regression models. We repeated the analysis with automatic transcription and segmentation using an automatic speech recognition (ASR) system. RESULTS: Our multidimensional metric was successful in predicting age group (area under the curve [AUC] = 0.87), and it performed better than the other metrics. High AUCs were also achieved by the Yngve score (0.84) and sentence length (0.84). However, in a fully automated pipeline with ASR, the performance of these two metrics dropped (to 0.73 and 0.46, respectively), while the performance of the multidimensional metric remained relatively high (0.81). CONCLUSIONS: Syntactic complexity in spontaneous speech can be quantified by directly assessing syntactic structures and considering them in a multivariable manner. It can be derived automatically, saving considerable time and effort compared to manually analyzing large-scale corpora, while maintaining high face validity and robustness. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24964179.

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease.

Introduction: Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods: Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results: Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion: We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.

Speech markers of depression dimensions across cognitive status.

Introduction: Depression and its components significantly impact dementia prediction and severity, necessitating reliable objective measures for quantification. Methods: We investigated associations between emotion-based speech measures (valence, arousal, and dominance) during picture descriptions and depression dimensions derived from the geriatric depression scale (GDS, dysphoria, withdrawal-apathy-vigor (WAV), anxiety, hopelessness, and subjective memory complaint). Results: Higher WAV was associated with more negative valence (estimate = -0.133, p = 0.030). While interactions of apolipoprotein E (APOE) 4 status with depression dimensions on emotional valence did not reach significance, there was a trend for more negative valence with higher dysphoria in those with at least one APOE4 allele (estimate = -0.404, p = 0.0846). Associations were similar irrespective of dementia severity. Discussion: Our study underscores the potential utility of speech biomarkers in characterizing depression dimensions. In future research, using emotionally charged stimuli may enhance emotional measure elicitation. The role of APOE on the interaction of speech markers and depression dimensions warrants further exploration with greater sample sizes. Highlights: Participants reporting higher apathy used more negative words to describe a neutral picture.Those with higher dysphoria and at least one APOE4 allele also tended to use more negative words.Our results suggest the potential use of speech biomarkers in characterizing depression dimensions.

Tau maturation in the clinicopathological spectrum of Lewy body and Alzheimer's disease.

OBJECTIVE: Alzheimer's disease neuropathologic change and alpha-synucleinopathy commonly co-exist and contribute to the clinical heterogeneity of dementia. Here, we examined tau epitopes marking various stages of tangle maturation to test the hypotheses that tau maturation is more strongly associated with beta-amyloid compared to alpha-synuclein, and within the context of mixed pathology, mature tau is linked to Alzheimer's disease clinical phenotype and negatively associated with Lewy body dementia. METHODS: We used digital histology to measure percent area-occupied by pathology in cortical regions among individuals with pure Alzheimer's disease neuropathologic change, pure alpha-synucleinopathy, and a co-pathology group with both Alzheimer's and alpha-synuclein pathologic diagnoses. Multiple tau monoclonal antibodies were used to detect early (AT8, MC1) and mature (TauC3) epitopes of tangle progression. We used linear/logistic regression to compare groups and test the association between pathologies and clinical features. RESULTS: There were lower levels of tau pathology (ß = 1.86-2.96, p < 0.001) across all tau antibodies in the co-pathology group compared to the pure Alzheimer's pathology group. Among individuals with alpha-synucleinopathy, higher alpha-synuclein was associated with greater early tau (AT8 ß = 1.37, p < 0.001; MC1 ß = 1.2, p < 0.001) but not mature tau (TauC3 p = 0.18), whereas mature tau was associated with beta-amyloid (ß = 0.21, p = 0.01). Finally, lower tau, particularly TauC3 pathology, was associated with lower frequency of both core clinical features and categorical clinical diagnosis of dementia with Lewy bodies. INTERPRETATION: Mature tau may be more closely related to beta-amyloidosis than alpha-synucleinopathy, and pathophysiological processes of tangle maturation may influence the clinical features of dementia in mixed Lewy-Alzheimer's pathology.

Changes in Digital Speech Measures in Asymptomatic Carriers of Pathogenic Variants Associated With Frontotemporal Degeneration.

BACKGROUND AND OBJECTIVES: Clinical trials developing therapeutics for frontotemporal degeneration (FTD) focus on pathogenic variant carriers at preclinical stages. Objective, quantitative clinical assessment tools are needed to track stability and delayed disease onset. Natural speech can serve as an accessible, cost-effective assessment tool. We aimed to identify early changes in the natural speech of FTD pathogenic variant carriers before they become symptomatic. METHODS: In this cohort study, speech samples of picture descriptions were collected longitudinally from healthy participants in observational studies at the University of Pennsylvania and Columbia University between 2007 and 2020. Participants were asymptomatic but at risk for familial FTD. Status as "carrier" or "noncarrier" was based on screening for known pathogenic variants in the participant's family. Thirty previously validated digital speech measures derived from automatic speech processing pipelines were selected a priori based on previous studies in patients with FTD and compared between asymptomatic carriers and noncarriers cross-sectionally and longitudinally. RESULTS: A total of 105 participants, all asymptomatic, included 41 carriers: 12 men [30%], mean age 43 ± 13 years; education, 16 ± 2 years; MMSE 29 ± 1; and 64 noncarriers: 27 men [42%]; mean age, 48 ± 14 years; education, 15 ± 3 years; MMSE 29 ± 1. We identified 4 speech measures that differed between carriers and noncarriers at baseline: mean speech segment duration (mean difference -0.28 seconds, 95% CI -0.55 to -0.02, p = 0.04); word frequency (mean difference 0.07, 95% CI 0.008-0.14, p = 0.03); word ambiguity (mean difference 0.02, 95% CI 0.0008-0.05, p = 0.04); and interjection count per 100 words (mean difference 0.33, 95% CI 0.07-0.59, p = 0.01). Three speech measures deteriorated over time in carriers only: particle count per 100 words per month (ß = -0.02, 95% CI -0.03 to -0.004, p = 0.009); total narrative production time in seconds per month (ß = -0.24, 95% CI -0.37 to -0.12, p < 0.001); and total number of words per month (ß = -0.48, 95% CI -0.78 to -0.19, p = 0.002) including in 3 carriers who later converted to symptomatic disease. DISCUSSION: Using automatic processing pipelines, we identified early changes in the natural speech of FTD pathogenic variant carriers in the presymptomatic stage. These findings highlight the potential utility of natural speech as a digital clinical outcome assessment tool in FTD, where objective and quantifiable measures for abnormal behavior and language are lacking.

CSF Proteomics in Patients With Progressive Supranuclear Palsy.

BACKGROUND AND OBJECTIVES: Identification of fluid biomarkers for progressive supranuclear palsy (PSP) is critical to enhance therapeutic development. We implemented unbiased DNA aptamer (SOMAmer) proteomics to identify novel CSF PSP biomarkers. METHODS: This is a cross-sectional study in original (18 clinically diagnosed PSP-Richardson syndrome [PSP-RS], 28 cognitively healthy controls]), validation (23 PSP-RS, 26 healthy controls), and neuropathology-confirmed (21 PSP, 52 non-PSP frontotemporal lobar degeneration) cohorts. Participants were recruited through the University of California, San Francisco, and the 4-Repeat Neuroimaging Initiative. The original and neuropathology cohorts were analyzed with the SomaScan platform version 3.0 (5026-plex) and the validation cohort with version 4.1 (7595-plex). Clinical severity was measured with the PSP Rating Scale (PSPRS). CSF proteomic data were analyzed to identify differentially expressed targets, implicated biological pathways using enrichment and weighted consensus gene coexpression analyses, diagnostic value of top targets with receiver-operating characteristic curves, and associations with disease severity with linear regressions. RESULTS: A total of 136 participants were included (median age 70.6 ± 8 years, 68 [50%] women). One hundred fifty-five of 5,026 (3.1%), 959 of 7,595 (12.6%), and 321 of 5,026 (6.3%) SOMAmers were differentially expressed in PSP compared with controls in original, validation, and neuropathology-confirmed cohorts, with most of the SOMAmers showing reduced signal (83.1%, 95.1%, and 73.2%, respectively). Three coexpression modules were associated with PSP across cohorts: (1) synaptic function/JAK-STAT (ß = -0.044, corrected p = 0.002), (2) vesicle cytoskeletal trafficking (ß = 0.039, p = 0.007), and (3) cytokine-cytokine receptor interaction (ß = -0.032, p = 0.035) pathways. Axon guidance was the top dysregulated pathway in PSP in original (strength = 1.71, p < 0.001), validation (strength = 0.84, p < 0.001), and neuropathology-confirmed (strength = 0.78, p < 0.001) cohorts. A panel of axon guidance pathway proteins discriminated between PSP and controls in original (area under the curve [AUC] = 0.924), validation (AUC = 0.815), and neuropathology-confirmed (AUC = 0.932) cohorts. Two inflammatory proteins, galectin-10 and cytotoxic T lymphocyte-associated protein-4, correlated with PSPRS scores across cohorts. DISCUSSION: Axon guidance pathway proteins and several other molecular pathways are downregulated in PSP, compared with controls. Proteins in these pathways may be useful targets for biomarker or therapeutic development.

Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration.

Importance: Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD. Objective: To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations. Design, Setting, and Participants: In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes. Exposure: Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests. Main Outcomes and Measures: Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy. Results: In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized ß range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back ß = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (ß = -0.14 [95% CI, -0.42 to 0.14]; P = .32). Conclusions and Relevance: The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.