Boeve, Bradley F.

AbstractBackgroundThe Progressive Supranuclear Palsy Quality of Life (PSP‐QoL) scale is a 45‐question participant‐completed questionnaire used to evaluate physical and cognitive task difficulties. Participants enrolled in the ALLFTD research program are asked to complete this questionnaire annually during their study visits.MethodPSP‐QoL responses were analyzed at baseline visits. Our analysis focused on responses to the overall satisfaction of life (range 0‐100, with 0 being extremely dissatisfied and 100 being extremely satisfied) relative to disease severity (CDR®+NACC‐FTLD global scores) and as a function of clinical phenotypes. A Kruskal‐Wallis test was used to compare overall satisfaction ratings against CDR®+NACC‐FTLD global score.Result788 PSP‐QoL survey responses were analyzed (participant mean age 55.3 ±15 years, 50.5% female). Analysis included responses from 372 (47.2%) asymptomatic participants (CN; CDR®+NACC‐FTLD = 0), 140 prodromal (17.8%) CDR®+NACC‐FTLD = 0.5, 160 (20.3%) CDR®+NACC‐FTLD = 1, 106 (13.5%) CDR®+NACC‐FTLD 2, and 10 (1.3%) CDR®+NACC‐FTLD = 3. All symptomatic groups were similar in PSP‐QOL overall satisfaction of life rating: (mean overall satisfaction CDR®+NACC‐FTLD = 0.5: 74.5 (SD 22.5); CDR®+NACC‐FTLD = 1: 74.1 (SD 24.7) and CDR®+NACC‐FTLD = 2/3: 74.1 (SD 25.8)), but these differed from asymptomatic (cognitively normal): (mean 83.7, (SD 14.6); p<0.0001). Similarly, when including the CN group and symptomatic phenotype groups, a statistically significant difference in ratings was seen: mean overall satisfaction CN = 83.7 (SD 14.7), MCI = 78.3 (SD 16.6), PPA = 71.6 (SD 26.9), PSP = 66.3 (SD 28.2), bvFTD = 76.8 (SD 23.8), and other = 70.6 (SD 23.2). However, even after removing the CN group, a difference amongst symptomatic phenotypes remained (p = 0.036).ConclusionMean overall life satisfaction as measured by the PSP QoL questionnaire was lower in all symptomatic compared to clinically normal participants, regardless of disease severity or phenotype. Further longitudinal analyses are needed to better understand how clinical progression impacts overall satisfaction of life.

AbstractBackgroundMany treatments targeting frontotemporal lobar degeneration (FTLD) are in the developmental pipeline, but the rarity of the disease, coupled with the behavioral and motor features of FTLD, make it challenging to identify sufficient trial participants who can attend frequent in‐person visits. Decentralized clinical trial designs with remote evaluations are attractive alternatives but require validated tools for symptom tracking. Our previous cross‐sectional analyses showed that cognitive tasks deployed via the ALLFTD Mobile App are reliable and sensitive to early stages of disease. The current study seeks to evaluate whether unsupervised smartphone cognitive tests are sensitive to longitudinal changes that occur with increasing FTLD disease stage.MethodThe study included 194 participants (mean baseline age 54.30, SD = 15.66; mean education = 16.52, SD = 2.31; 55.2% women) who were asymptomatic (Clinical Dementia Rating plus FTLD (CDR®+NACC‐FTLD) = 0 [n = 109; 43 carriers of FTLD‐associated genetic variants]), prodromal (CDR®+NACC‐FTLD = 0.5 [n = 39]), or symptomatic (CDR®+NACC‐FTLD>0.5 [n = 46]) at baseline. Participants completed ALLFTD Mobile App smartphone versions of Stroop, flanker, and 2‐back tasks, as well as an adaptive associative memory task, every six months for up to two years. Linear‐mixed effects models investigated the effect of disease severity on cognitive trajectories by testing the interaction of baseline CDR®+NACC‐FTLD box score and time on smartphone test scores. Analyses were repeated in the subsample of asymptomatic/prodromal CDR®+NACC‐FTLD<1) familial FTLD mutation carriers (C9orf72, n = 27; MAPT, n = 16). All models controlled for age, education, and sex.ResultGreater baseline disease severity was associated with lower cognitive scores across all tasks (β range: ‐0.28 to ‐0.13; p’s < 0.001), and faster rates of decline on the memory and 2‐back tasks (β range: ‐0.15 to ‐0.07; p’s<0.04). When the sample was restricted to asymptomatic and prodromal individuals (CDR®+NACC FTLD<1), greater baseline disease severity was still associated with lower scores across most tasks (β range: ‐0.48 to ‐0.27; p’s<0.002; 2‐back: β = ‐0.19, p = 0.26). When the sample was restricted to asymptomatic/prodromal mutation carriers, disease severity remained associated with the memory and flanker tasks (β range: ‐0.85 to ‐0.45; p’s<0.01).ConclusionThis study provides initial evidence that longitudinal smartphone‐based cognitive measurements capture the accelerated cognitive worsening that accompanies increasing disease progression in FTLD.

AbstractBackgroundFrontotemporal degeneration (FTD) is an umbrella term encompassing a range of rare neurodegenerative disorders that cause progressive changes to behavior, personality, language, and movement with onset typically before age 60. Currently, several potential FTD therapies are under investigation, underscoring the need for increased diversity in research participation. Two validated scores describe socioeconomic and geographic factors that may impact willingness to participate in research. The Area Deprivation Index (ADI) assesses socioeconomic disadvantages and captures social determinants of health. The Rural‐Urban Commuting Area Codes (RUCA) measures population density, urbanization, and daily commuting to determine individuals living in urban versus rural communities. FTDDR is a compliant, web‐based registry to facilitate FTD research. ADI and RUCA analyses of FTDDR participants can provide insight into current participants’ demographics and areas for recruitment prioritization.MethodFTDDR participants living in the United States were divided into two cohorts: (1‐FTDDR) enrolled in FTDDR only and (2‐ALLFTD) enrolled in FTDDR through ALLFTD, a longitudinal natural history study. ADI was calculated from self‐reported zip codes for 1392 participants in cohort 1 and 983 participants in cohort 2. RUCA scores were generated using self‐reported zip codes for 4565 participants from cohort 1 and 1174 participants from cohort 2.ResultADI analysis showed a low percentage (6.9% FTDDR, 5.7% ALLFTD) of participants lived in highly disadvantageous communities. 40.5% of FTDDR cohort and 49.3% of ALLFTD cohort lived in communities considered “low disadvantage,” suggesting they may have fewer socioeconomic risk factors or impediments to research participation. Most participants in both cohorts lived in urban areas (87.9% FTDDR, 85.8% ALLFD); only 3.2% of both cohorts lived in rural communities.ConclusionSocioeconomic and geographic factors may play a role in accurate diagnosis, access to medical centers, and ability to participate in research. ADI and RUCA analyses indicate that the majority of FTDDR participants, including those actively enrolled in FTD research, live in less disadvantageous neighborhoods and in urban areas, highlighting the need for outreach to more disadvantaged and rural communities. FTDDR prioritizing an engagement strategy to identify, recruit, and retain diverse individuals willing to participate in research could accelerate advancements in FTD research.

AbstractBackgroundSubjective cognitive concerns are common in functionally intact adults, potentially indicating future cognitive decline. Remote smartphone cognitive testing holds promise for objectively tracking cognition in individuals reporting complaints. In our initial exploration of the link between subjective cognitive complaints and digital clinical outcomes, we examined participants' self‐reported cognitive complaints' association with smartphone tests on memory and executive functioning.MethodsParticipants, without self‐reported MCI or dementia, were recruited from the UCSF Brain Healthy Registry (BHR) to complete cognitive tasks on their personal smartphone with the ALLFTD Mobile App. Participants also completed the 12‐item Everyday Cognition Screening Tool (ECog‐12), assessing subjective cognitive impairment, online as part of BHR. Average ECog‐12 scores, including Memory and Executive Functioning subdomains, were calculated. Correlations between scores from online ECog‐12 scores and app‐based smartphone tasks were examined. Regression analyses, adjusting for age, education, and sex, were performed to evaluate the relationship between ECog‐12 and smartphone tasks (Stroop & Flanker) measuring executive function and memory.ResultsOut of 2,283 invited BHR participants, 456 (mean age: 64.6 years (SD = 11.8) and education: 16.3 years (SD = 2.4)) completed smartphone tasks (81.1% completion rate). Age was negatively associated with executive functioning and memory tasks (ß’s = ‐0.51 to ‐0.54, p’s<0.05), while higher education correlated with better performance (ß’s = 0.10‐0.14, p’s<0.05). Sex was not significantly associated with performance on any task (ß’s = ‐0.04 to 0.09, p’s>0.05). Subjective cognitive concerns were linked to tasks of executive functioning (Stroop: ß = ‐0.18, p = 0.002) and memory (ß = ‐0.14, p = 0.02). Endorsement of executive functioning items on ECog‐12 associated with Stroop performance (ß = ‐0.16, p = 0.005), and memory‐specific complaints were related to memory performance (ß = ‐0.1, p = 0.09). The relationship with flanker scores was not significant (ß = ‐0.08, p = 0.17). Similar patterns emerged with the online ECog‐12; online and app‐based scores are strongly correlated (ß = 0.75, p<0.05).ConclusionsIn this cognitively intact sample, subjective cognitive concerns were linked to poorer performance on ALLFTD Mobile App tasks assessing executive functioning and memory. These findings suggest that unsupervised remote smartphone testing merits further consideration to monitor cognition in individuals with subjective cognitive concerns. Subsequent studies in deeply phenotyped cohorts with follow‐up assessments are essential for understanding the clinical relevance of these results.

AbstractBackgroundAutosomal dominant progranulin (GRN) mutations are a common genetic cause of frontotemporal lobar degeneration. Though clinical trials for GRN‐related therapies are underway, there is an unmet need for biomarkers that can predict symptom onset and track disease progression. We previously showed that presymptomatic GRN carriers exhibit thalamocortical hyperconnectivity that increases with age when they are presumably closer to symptom onset. However, whether hyperconnectivity arises concomitantly with markers of neurodegeneration remains unclear.MethodUtilizing T1 and task‐free functional magnetic resonance imaging (tf‐fMRI) from 49 presymptomatic and 26 symptomatic GRN mutation carriers, we determined the relationships between functional connectivity as measured by voxel‐wise whole brain degree and GRN‐relevant markers of disease progression, which included plasma neurofilament light chain (NfL) concentrations, CSF complement C1q and C3b protein levels, grey matter atrophy, and OCD symptom severity.ResultNfL concentrations were associated with frontotemporoparietal and thalamic hyperconnectivity in presymptomatic GRN carriers and extensive regions of atrophy in symptomatic carriers. Complement levels were associated with regions of hyperconnectivity, but not gray matter, in symptomatic carriers. Presymptomatic carriers with thalamic hyperconnectivity tended to have lower grey matter volume in bilateral insula and left lateral parietal cortex, which are among regions that deteriorate in GRN‐FTD. OCD symptom severity was associated with hypoconnectivity across all GRN carriers.ConclusionIn presymptomatic carriers, the co‐occurrence of hyperconnectivity, high NfL, and low gray matter suggests that tf‐fMRI hyperconnectivity may portend the onset of the neurodegenerative phase. These findings point toward hyperconnectivity as an indicator of approaching symptomatic onset.

AbstractBackgroundThe Uniform Data Set (UDS) neuropsychological battery, administered across Alzheimer’s Disease Centers (ADC), includes memory tests but lacks a list‐learning paradigm. ADCs often supplement the UDS with their own preferred list‐learning task. Given the importance of list‐learning for characterizing memory, we aimed to develop a harmonized memory score that incorporates UDS memory tests while allowing centers to contribute differing list‐learning tasks.MethodWe applied item‐banking confirmatory factor analysis to develop a composite memory score in 5,287 participants (mean age 67.1; SD = 12.2) recruited through 18 ADCs and four consortia (DiverseVCID, MarkVCID, ALLFTD, LEADS) who completed UDS memory tasks (used as linking‐items) and one of five list‐learning tasks. All analyses used linear regression. We tested whether memory scores were affected by which list‐learning task was administered. To assess construct validity, we tested associations of memory scores with demographics, disease severity (CDR Box Score), an independent memory task (TabCAT Favorites, n = 675), and hippocampal volume (n = 811). We compared performances between cognitively unimpaired (n = 279), AD‐biomarker+ MCI (n = 26), and AD‐biomarker+ dementia (n = 98). In a subsample with amyloid‐ and tau‐PET (n = 49), we compared memory scores from participants with positive vs negative scans determined using established quantitative cutoffs.ResultModel fit indices were excellent (e.g., CFI = 0.998) and factor loadings were strong (0.43‐0.93). Differences in list‐learning task had a negligible effect on scores (average Cohen’s d = 0.11). Higher memory scores were significantly (p’s<.001) correlated with younger age (β = ‐0.18), lower CDR Box Scores (β = ‐0.63), female sex (β = 0.12), higher education (β = 0.19), larger hippocampal volume (β = 0.42), and an independent memory task (β = 0.71, p<0.001). The memory composite declined in a stepwise fashion by diagnosis (cognitively unimpaired>MCI>AD dementia, p<0.001). On average, amyloid‐PET positivity was associated with lower composite scores, but was not statistically significant (β = ‐0.34; p = 0.25; d = 0.40). Tau‐PET positivity was associated with worse performance, demonstrating a large effect size (β = ‐0.75; p<0.002; d = 0.91).ConclusionThe harmonized memory score developed in a large national sample was stable regardless of contributing list‐learning task and its validity for cross‐cohort ADRD research is supported by expected associations with demographics, clinical measures, and Alzheimer’s biomarkers. A processing script will be made available to enhance cross‐cohort ADRD research.

AbstractBackgroundThe ALLFTD (ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration) study is an NIH‐funded effort to prepare for clinical trials in sporadic (s‐FTLD) and familial (f‐FTLD) FTLD syndromes by characterizing cohorts, developing new clinical trial outcome measures, and evaluating disease progression. To understand disease trajectories in the context of potential preventative or disease‐modifying therapeutic agents, comprehensive evaluation across multiple time‐points is crucial.MethodALLFTD evaluates participants with FTLD spectrum disorders (bvFTD, svPPA, nfvPPA, FTD‐ALS, CBS, PSP), with strong family histories of FTLD, or known FTLD‐associated genetic variants within the family. ALLFTD has expanded to include 28 expert sites in North America conducting clinical and neuropsychological evaluations, MR Imaging, blood draws, and CSF collection in willing participants, providing detailed data on participant status and disease progression. Participants are asked to return for annual evaluations. The central data management staff assist sites in retention efforts by providing monthly reports of follow‐up visits that are pending, due, or overdue, based on a 15‐month period from previous visit.ResultSince enrollment began in January 2020, ALLFTD has conducted 1363 baseline visits, including 339 participants previously enrolled in ALLFTD’s predecessor studies (ARTFL and LEFFTDS). Excluding individuals not anticipated to return due to disease progression (123), participant death (55), or recent enrollment (<15 months; 318), ALLFTD has a retention rate of 83% for a second visit despite early enrollment occurring during COVID restrictions. Retention rates for third and fourth visits are even higher (90% and 97% respectively), suggesting a high degree of engagement in longitudinal participants. Including historic data from ARTFL and LEFFTDS, >1000 participants have multiple visits.ConclusionLongitudinal assessment of clinical and biomarker profiles in f‐FTLD and s‐FTLD can inform models of disease onset and progression, allowing analysis of disease trajectories and identification of the most sensitive clinical outcome measures over time. ALLFTD has been successful at recruiting and retaining a large active cohort to obtain detailed clinical and biomarker characterizations; data are available by request.

AbstractBackgroundSex differences in neurodegenerative diseases can impact accurate diagnosis and management. Emerging data suggest there may be sex differences in frontotemporal dementia (FTD) prevalence and clinical manifestation. However, prior studies lacked longitudinal assessment and were limited in capturing sex differences in earliest stages of disease (e.g., preclinical). We evaluated how sex impacts longitudinal clinical outcomes in individuals carrying autosomal dominant variants for FTD.Method337 participants carrying pathogenic variants in MAPT, GRN, or C9orf72 completed longitudinal evaluations (2.4 average visits, range = 1‐6), including neuropsychological and functional assessments, and plasma analyzed for neurofilament light chain (NfL). FTLD Clinical Dementia Rating Scale (FTLD‐CDR) classified disease stage at study entry (FTLD‐CDR = 0: asymptomatic; FTLD‐CDR = 0.5: MCI; FTLD‐CDR> 0.5: Dementia). Linear mixed‐effects models evaluated the effect of sex on longitudinal clinical trajectories, including the effect of disease stage at study entry.ResultMale and female carriers were similarly distributed with respect to baseline demographics and most clinical outcomes. However, women exhibited higher baseline NfL than men. Not accounting for disease stage, men and women did not show statistical differences on cognitive, functional, or NfL trajectories. However, when accounting for disease stage, there was a significant interaction between baseline disease stage, sex, and time on cognitive, NfL, and functional trajectories. While sex differences were not statistically significant among asymptomatic carriers, women with MCI/dementia evidenced more rapid cognitive, NfL and functional decline over time compared to men. To evaluate the role of pathology burden, we tested the interaction between baseline NfL, sex, and time on clinical outcomes stratified by disease stage. In asymptomatic participants, women showed an attenuated adverse relationship between baseline NfL and clinical trajectories compared to men. No statistically significant sex differences were evident in the relationship between baseline NfL and clinical outcomes in participants with MCI/dementia.ConclusionIn familial FTD, women evidenced steeper clinical declines than men after symptom onset. Accounting for pathology, baseline NfL was a stronger predictor of clinical decline in asymptomatic men compared to women. NfL may be a less sensitive prognostic tool for clinical progression in women with FTD, particularly early in disease. This may reflect early “cognitive resilience” to neurodegeneration in women.

AbstractBackgroundAutonomic dysfunction has been linked to empathy deficits in symptomatic frontotemporal degeneration (FTD), but less is known about pre‐symptomatic FTD mutation carriers (preFTD+). Our prior work found that increasing resting heart rate (RHR) over time predicts decline in emotional empathy in preFTD+. Here, we replicate previous findings in a large, multi‐site consortium sample and assess relationships between RHR and empathy loss across disease stages.MethodRHR and Interpersonal Reactivity Index (IRI) were obtained serially for up to 7 years in 348 preFTD+, 202 symptomatic FTD mutation carriers (FTD+), and 311 non‐carrier family members (FTD‐) enrolled in ALLFTD. IRI Perspective Taking (IRI‐PT) and Empathic Concern (IRI‐EC) subscales measured cognitive and emotional empathy, respectively. Separate multiple linear regressions related mutation status and annualized change in RHR to annualized change in IRI subscales and assessed interactions between RHR change and phenoconversion status among mutation carriers. Logistic regression was used to assess the association between change in RHR and phenoconversion among mutation carriers, and Wilcoxon signed‐rank tests were used to examine differences in change in RHR between all study groups.ResultIn asymptomatic participants (preFTD+ and FTD‐), increase in RHR over time was associated with greater decline in IRI‐EC (ß = ‐0.07, p<.001) and IRI‐PT (ß = ‐0.03, p = .011), regardless of mutation status. Among mutation carriers (preFTD+ and FTD+), increase in RHR was associated with greater decline in IRI‐EC (ß = ‐0.04, p = .041), and this effect was stronger in FTD+ compared to PreFTD+ (ß = ‐0.07, p = .038), while an increase in RHR was associated with decline in IRI‐PT only in FTD+ (ß = ‐0.07, p = .046). Change in RHR did not predict phenoconversion in mutation carriers (PreFTD+ and FTD+), but PreFTD+ showed less change in RHR over time relative to FTD+.ConclusionChanges in empathy in asymptomatic preFTD+ and FTD‐ are linked to variability in RHR regardless of genetic status, likely reflecting a non‐specific impact of autonomic functioning on empathy and prosocial behavior. In contrast, increasing RHR predicts decline in cognitive and emotional empathy in FTD mutation carriers but primarily after phenoconversion, suggesting that autonomic contributions to empathy in familial FTD increase with disease progression and could be an early marker of manifest disease.

AbstractBackgroundFrontotemporal dementia (FTD) is a diverse spectrum of neurodegenerative disorders impacting the frontal and temporal lobes, primarily manifesting as behavioral and/or language issues. Accurate diagnosis is crucial for effective management, potential treatment, and care planning. While speech analysis has shown promise in detecting cognitive markers of Alzheimer’s disease (AD), its exploration in FTD is limited. This study examined if linguistic features from remote, app‐based speech collection can differentiate healthy controls (HC) from individuals with behavioral variant FTD (bvFTD), the most common FTD variant.MethodParticipants included 15 bvFTD (mean age = 64.3, SD = 9.1 years) and 19 HC (mean = 55.8, SD = 14.2) from the ALLFTD Consortium. Participants were prompted to talk freely about a happy memory; audio recordings were collected with the ALLFTD Mobile App, transcribed using OpenAI’s large Whisper model, and manually quality‐checked. We extracted 98 linguistic features using our in‐house pipeline (Fig 1). Features were selected for classification analysis if they differed between groups based on a MANCOVA adjusted for age, sex/gender, and education, with feature reduction in case of collinearity. We then determined if these features could classify groups using multi‐variable logistic regression models, and subsequently calculated its ROC‐AUC score to measure sensitivity/specificity.ResultBased on the MANCOVA, three features were selected for classification analysis: average seconds of non‐speech (i.e., silence), ratio of number of complex nominal clauses to total clauses, and number of restarts (i.e., disfluency). The logistic model showed that this set could distinguish between groups (Omnibus p = .001; Nagelkerke R2 = .499), and their saved prediction probabilities indicated a ROC‐AUC score of 84.8% accuracy (Fig 2).ConclusionLeveraging a flexible speech capture app with remote accessibility and state‐of‐the‐art automated speech analysis, we identified linguistic features that can distinguish HC from bvFTD. This approach presents a promising screening tool for detecting bvFTD, offering quick, easily administered assessments with the potential for scalable implementation outside of clinical settings. Next steps are to investigate linguistic changes in presymptomatic mutation carriers and compare speech profiles between FTD and AD. These results hold meaningful implications for addressing current challenges in FTD therapeutics, potentially offering sensitive outcome measures for clinical trials and future tools for personalized cognitive assessment and long‐term monitoring.