Staffaroni, Adam M.

AbstractBackgroundFrontotemporal Dementia (FTD) patients are geographically dispersed and often have behavioral and/or motor deficits that limit access to in‐person clinical trials and research. To address these participation barriers, we investigated the feasibility of installing in‐home sensor technologies to remotely assess everyday functioning in FTD.MethodWe aimed to recruit 20 FTD participants with a variety of clinical syndromes, including behavioral variant FTD (bvFTD), primary progressive aphasia (PPA), corticobasal syndrome (CBS), and progressive supranuclear palsy (PSP). We also aimed to enroll a study partner for each participant that lived in the same home to serve as a control. The Collaborative Aging Research Using Technology (CART) platform was installed in participants’ homes to collect continuous data for up to two years, using motion sensors, physiological monitoring devices (e.g., scales, sleep sensors), electronic pillboxes, and wearable actigraphs. Computer use and driving patterns were also tracked. Technology was installed either via a study coordinator visit or remotely through video and written instructions, based on schedule and logistics. Participants were asked to complete a weekly Qualtrics survey about time away from home, visitors, and health changes.ResultOf the 159 UCSF participants available for recruitment through ALLFTD and other FTD projects, 28% (N = 45) met inclusion criteria. Of those 45, ten were ineligible due to advanced disease severity or relocation to an assisted living facility. A third (36%, N = 17) declined due to overwhelmed study partners (N = 3), declined any subproject participation (N = 7), sensitivity to participant’s diagnosis (N = 2), or lack of response (N = 5). Two additional participants were recruited through UCLA’s ALLFTD cohort. The platform has been installed in 19 homes (bvFTD: n = 10; PPA: n = 5; CBS/PSP: n = 4). Two homes discontinued due to death or relocation to assisted living facility. Mean data collection is 360 days (max = 527). Of 103 reported technological issues, 92% were resolved without additional home visits, either by phone or email. Participants completed 65% of weekly health questionnaires.ConclusionsAlthough there were some recruitment and retention challenges, these findings generally provide preliminary support for the feasibility and sustainability of conducting comprehensive in‐home passive data research in FTD.

AbstractBackgroundThere has been a rise in remote cognitive testing for neurodegenerative diseases. The ALLFTD Mobile App is designed to capture clinical features of frontotemporal dementia (FTD) through repeated remote assessment on smartphones. This is a departure from traditional neuropsychological practice in which a single examiner‐led assessment occurs in a controlled setting. When participants complete tasks on their own, those with greater disease severity may be more variable in their performance for a variety of reasons (e.g. greater distractibility, less engagement). Here we study whether intraindividual cognitive variability (IIV) is associated with older age and increasing disease severity.MethodParticipants were 279 (mean age = 54.9) healthy controls and participants with sporadic FTD or from familial FTD kindreds with a range of disease severities based on FTLD Clinical Dementia Rating scale (CDR®+NACC‐FTLD Global) scores: 0 (n = 132), 0.5 (n = 54), and ≥1 (n = 47). Participants completed three cognitive tasks at least two times across twelve days. Measures included an adaptive memory task and gamified versions of Flanker and Go/no‐go tasks. IIV was operationalized as the standard deviation in performance on each task. Regression analyses investigated the relationship of IIV with CDR®+NACC‐FTLD group, and with age in those without symptoms. Education and gender were included as covariates in all analyses.ResultGreater disease severity (CDR®+NACC‐FTLD) was associated with greater variability on Flanker (p<.001) and Go/No‐go (p = .02) tasks; a positive but non‐significant association was seen with memory testing (p = .16). Post‐hoc comparisons found that those with CDR®+NACC‐FTLD of 0.5 had significantly more IIV on the Flanker task (𝛃 = .39, p = .004) than those with CDR®+NACC‐FTLD’s of 0. Moreover, those with a CDR®+NACC‐FTLD ≥1 had significantly greater IIV on the Flanker (𝛃 = .85, p<.001) and Go/No‐go tasks (𝛃 = .51, p = .007) than those with a CDR®+NACC‐FTLD of 0. In those without symptoms (CDR®+NACC‐FTLD = 0), age was associated with increased IIV on the Flanker (𝛃 = .27, p<.001) and Go/no‐go (𝛃 = .23, p<.001) tasks.ConclusionIncreased IIV, particularly on processing speed/executive functioning tasks, was associated with greater age and greater functional impairment, even in the mildest stages. Future investigations exploring predictors of IIV and the prognostic value of IIV are warranted.

AbstractBackgroundMemory impairment is generally considered minimal to absent in those with behavioral variant frontotemporal dementia (bvFTD). We sought to assess the frequencies of subjective and objective memory impairment in individuals with mild bvFTD according to consensus criteria.MethodAssessments were performed in mildly symptomatic bvFTD [defined by global FTLD Clinical Dementia Rating scale (CDR®+NACC FTLD) = 1] mutation carriers (Familial) and non‐mutation carriers (Sporadic) who are participants in the ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD, www.allftd.org) study. Mutation carriers had a pathogenic mutation in the MAPT, GRN or C9orf72 gene. The presence of subjective memory impairment was defined by a rating >0 on the memory domain of the CDR®+NACC FTLD. Evidence of objective memory impairment was based on performance across 7 memory measures, which include the National Alzheimer’s Coordinating Center Uniform Data Set Version 3 – Craft Story Immediate Recall (CSImm) and Delayed Recall (CSDel), Benson Figure Delayed Recall (BenDel), and the California Verbal Learning Test – Learning (CVLearn), Immediate Recall (CVImm), Delayed Recall (CVDel), and Recognition (CVRecog). Performance was considered abnormal for z‐scores ≤ ‐1.5.ResultData from 38 Familial (mean age 60±8 years, 61% male), and 109 Sporadic (mean age 63±7 years, 70% male) participants were analyzed. Memory ratings >0 on the CDR®+NACC FTLD were common for both Familial (84%) and Sporadic (88%). The frequencies of abnormal performance in the Familial vs Sporadic groups, respectively, per memory measure were: CSImm 43.8% vs 45.9%, p = 0.83; CSDel 46.9% vs 52.6%, p = 0.58; BenDel 29.4% vs 46.4%, p = 0.08; CVLearn 54.8% vs 39.8, p = 0.14; CVImm 64.5% vs 50%, p = 0.16, CVDel 80.6% vs 55.1%, p = 0.01, and CVRecog 51.6 vs 49%, p = 0.80. The frequencies of abnormal performance did not differ (all p>0.05) between Familial and Sporadic for ≥2 tests (79.3% vs 67.7%), ≥4 tests (55.2% vs 44.1%) and ≥6 tests (34.5% vs 31.2%).ConclusionThese data suggest that among those with a mild global severity of bvFTD features: 1) subjective and objective memory impairment are relatively frequent, and 2) the frequency of impairment across memory measures is largely similar between familial and sporadic bvFTD. The presence of memory impairment should not preclude a diagnosis of bvFTD.

AbstractBackgroundFrontotemporal dementia (FTD) is a leading cause of dementia in individuals under age 65. Due to limitations in access to in‐person evaluations, there is an urgent need to examine remote, accessible, and low‐burden assessment techniques for FTD. Unobtrusive monitoring of at‐home computer use in older adults has shown that those with mild cognitive impairment (MCI) have significant declines in computer use over time. To extend these findings, we characterized daily trajectories in smartphone battery percentage, a proxy of smartphone use, and examined relationships with clinical indicators of disease severity in FTD.MethodParticipants included 250 adults enrolled in the ALLFTD Mobile App study (mean age = 53.9 [SD = 14.9]; 59% women; 94% White). To assess clinical disease severity, all participants completed the FTLD Clinical Dementia Rating scale (CDR®+NACC FTLD), a brief neuropsychological battery, the Neuropsychiatric Inventory Questionnaire (NPI‐Q), and brain MRI. The ALLFTD Mobile App was installed onto participants’ smartphones for remote, passive, continuous monitoring of smartphone use (average days of monitoring = 82 [range = 7‐541]). Battery percentage was collected every 15 minutes. Linear mixed effects models examined linear, quadratic, and cubic effects of time of day (i.e., hour; modeled as person‐specific random effects) and their interactions with each measure of disease severity on battery percentage. Models covaried for age.Result57% of participants were clinically normal, 21% had MCI, and 22% had dementia. CDR®+NACC FTLD Global score interacted with hour such that participants with MCI and dementia had flatter battery curves (i.e., less change in battery percentage throughout the day – a proxy of less smartphone use) than clinically normal participants (ps<0.001). Additional models showed that worse memory (hour3 x memory score: 𝛃 = 0.59, p<0.001) and executive functioning (hour3 x executive score: 𝛃 = 0.64, p<0.001), more neuropsychiatric symptoms (hour3 x NPI‐Q: 𝛃 = ‐0.22, p = 0.004), and smaller gray matter volumes (controlling for intracranial volume; hour3 x volume: 𝛃 = 0.49, p<0.001) were also statistically significantly related to less battery usage throughout the day.ConclusionThese findings are proof‐of‐concept that passively acquired smartphone data, specifically battery usage, can provide insights about disease progression in FTD. Results support future research focusing on the development of passively collected digital metrics sensitive to clinical declines in neurodegenerative disease.

AbstractBackgroundPathogenic mutations in the MAPT (tau) gene cause familial frontotemporal lobar degeneration (f‐FTLD). No disease‐modifying treatments exist. Tau therapeutics being tested in other tauopathies may be suitable candidates, but the small number of identified mutation carriers prohibits traditional clinical trial designs from achieving adequate power. Platform trial designs permit multiple therapies to be tested in parallel and improve power by sharing placebo groups across treatment arms. We evaluate whether a platform design could improve the likelihood of identifying an effective treatment for MAPT mutation carriers.MethodALLFTD and GENFI observational data were used to simulate MAPT prevention and early symptomatic clinical trials (CDR®+NACC‐FTLD≤1). Only presymptomatic participants (CDR®+NACC‐FTLD = 0) within 2.5 years of expected symptom onset based on disease progression models (DPM) were included. First, we evaluated the time and sample size required to test five treatments using a platform design compared to sequential randomized control trials. Platform designs assumed a max of three treatment arms at any time, with new arms enrolling upon completion of prior arms. Each arm randomized 60 mutations carriers 3:1 treatment to placebo, with a placebo group shared across arms. Minimum follow up was 1.5 years with common close. Sequential trials assumed 90 participants allocated 1:1 treatment to placebo, with three‐month intervals between trials. Using a platform design, we compared a novel method for testing therapeutic effects using DPMs to account for differential rates of expected progression compared to traditional mixed models for repeated measures (MMRM) tests controlling for baseline CDR®+NACC‐FTLD.ResultFive treatments could be tested in a platform design using 300 participants (75% treated) over five years, compared to 450 participants (50% treated) over 13 years using traditional, sequential trials. Platform trial simulations indicated that with 80% power, DPM‐based analytic approach could detect a 25% treatment effect, whereas traditional MMRM could only detect a 40% effect.ConclusionPlatform designs combined with DPM‐based analyses provide a path to testing more treatments with fewer participants. Adequately powered MAPT platform trials are feasible but require a global clinical trial infrastructure.

AbstractBackgroundSmartphone‐based cognitive and motor tests enable frequent remote assessments in observational research studies and clinical trials, limiting travel burden and increasing access to research for underrepresented groups. One such smartphone tool is the ALLFTD Mobile App, which was designed to capture the clinical features of neurodegenerative diseases via a battery of cognitive, speech, and motor tasks. In this study, we focus on recruiting a demographically diverse normative sample. We have partnered with the UCSF Brain Health Registry (BHR) to recruit 1,000 cognitively healthy participants across the lifespan. Here we describe the study design and initial feasibility results.MethodsWe designed an automated workflow in which participants never interact with the study team except for troubleshooting. BHR participants without reported cognitive impairment were contacted by email to participate in this study (n = 668). Interested participants downloaded the app onto their smartphone and completed in‐app electronic consent. They were asked to complete three ∼30‐minute sessions of cognitive, motor and speech measures over two weeks. Adherence was determined by evaluating the completion rate of app tasks. In a subset who completed a user experience questionnaire (n = 116), responses were quantified using descriptive statistics.ResultsThe current enrollment rate is 23.20% (155/668) of contacted participants. Average age is 62 (SD = 8.2, range = 25‐84). Average adherence is 76%. Participants reported a range of perceived task difficulty: 38% indicated tasks were “very easy” or “somewhat easy”, 26% indicated they were “neutral,” 36% found the tasks “somewhat difficult,” and none reported them to be “very difficult.” The time commitment was reported to be acceptable by 97% of participants, and 20% were willing to complete additional tasks. Over half (59%) of participants indicated that they preferred using a smartphone to complete cognitive assessments over traditional pen‐and‐paper measures.ConclusionsOur preliminary results demonstrate the feasibility and acceptability of recruiting participants, including older adults, through a registry and conducting remote smartphone testing via a fully automated workflow that is highly scalable. Future analysis will study the effects of demographic factors on feasibility and investigate the reliability and validity of the app measures in this sample.

AbstractBackgroundCharacterizing disease trajectories in frontotemporal lobar degeneration (FTLD) is essential to determine the optimal timing for initiating therapeutic interventions, and there is an urgent need for novel and sensitive disease biomarkers. Intrinsic connectivity network (ICN) mapping using task‐free fMRI is a promising biomarker which reveals early abnormalities even before symptomatic onset (Dopper et al. 2014; Lee et al. 2016). Yet, ICN trajectories from the presymptomatic to symptomatic stages in FTLD mutation carriers remain unclear.MethodIn this cross‐sectional study, we used UCSF and ALLFTD Consortia data to study 129 carriers with variants in MAPT (presymptomatic/prodromal/symptomatic: 34/4/7), C9orf72 (30/9/12) and GRN (22/4/7). Using cross‐sectional data to construct ICN trajectories by genotype, we built separate generalized additive models for each genetic group to estimate non‐linear relationships between standardized connectivity changes and disease age across clinical stages. ICN connectivity was based on seed‐based analyses for networks associated with common clinical syndromes for each genetic group (i.e., salience and default mode [MAPT/C9orf72/GRN], corticobasal syndrome [MAPT/GRN], progressive supranuclear palsy syndrome [MAPT], sensorimotor and medial pulvinar‐related [C9orf72], and non‐fluent variant primary progressive aphasia (nfvPPA) syndrome networks [GRN]). We included 127 healthy controls as a reference to calculate ICN z‐scores for each carrier. Each carrier’s disease age was defined as the difference between the carrier’s chronological age and estimated age of onset based on multimodal measures of structural imaging, fluid biomarker and clinical assessments (Staffaroni et al. 2022).ResultIn MAPT+, presymptomatic carriers showed declining salience network connectivity starting approximately 30 years before estimated onset, which plateaued about 20 years before onset. In C9orf72+, salience network hyperconnectivity emerged about 30 years before onset and declined throughout the presymptomatic and symptomatic stages. For GRN+, connectivity changes as a function of disease age were found within the salience and nfvPPA networks, with connectivity stable until around 10 years before estimated onset, followed by decline starting in the late presymptomatic phase and continuing through the prodromal and symptomatic stages.ConclusionThese findings demonstrate that FTLD genes show distinct ICN trajectories throughout the clinical spectrum. These results help pave the way for determining the optimal timing to initiate therapeutic interventions.

AbstractBackgroundTMEM106B, a lysosomal trafficking protein, is an important genetic susceptibility risk factor for frontotemporal lobar degeneration (FTLD). In GRN mutation carriers, minor allele homozygosity in the TMEM106B rs1990622 SNP modulates the risk of FTLD. TMEM106B is often the main component of amyloid fibrils in FTLD with TDP43 aggregates. TMEM106B has been quantified in human brain specimens, but its role as a fluid biomarker is unknown. Here, we investigate the clinical value of CSF TMEM106B in FTLD.MethodsCSF TMEM106B was quantified with SOMAmer proteomics (v3.0, SomaLogic®) in an original cohort of C9orf72, GRN and MAPT symptomatic and asymptomatic mutation carriers and family non‐carrier controls, recruited through ALLFTD (n = 182), and a validation cohort of sporadic neuropathology‐confirmed FTLD‐tau and FTLD‐TDP43, clinically‐diagnosed progressive supranuclear palsy – Richardson syndrome (PSP‐RS) and age‐matched controls (n = 96). CSF TMEM106B was correlated with disease severity, measured by the Frontotemporal Lobar Degeneration module global scores (CDR+NACC/FTLD); brain volume, measured with Bayesian linear mixed‐effect modeling, using age, sex and total‐intracranial volume‐corrected permutations with threshold‐free cluster enhancement; and CSF neurofilament light chain (NfL) measured with Simoa. TMEM106B SOMAmer specificity was validated in cell culture overexpression systems and human brain specimens with high TMEM106B burden.ResultsIn both cohorts, there were no differences in CSF TMEM106B by sex, phenotype or neuropathological diagnosis, except for lower levels in PSP‐RS compared to controls (‐0.31 Log2‐fold change, p < 0.001). CSF TMEM106B did not correlate with age. Regardless of disease‐causing mutation, lower CSF TMEM106B was associated with worse disease severity (Figure 1 and 2). CSF TMEM106B was lower in homozygous TMEM106B rs1990622 protective allelein C9orf2 and MAPT, but not in GRN mutation carriers (Figures 3). CSF TMEM106B showed a trend for inverse correlation with NfL in the whole sample (r = ‐0.135, p = 0.052), and correlated positively with left frontal volume in symptomatic FTLD mutation gene carriers (p < 0.05).ConclusionCSF TMEM106B is quantifiable in CSF in vivo. CSF TMEM106B levels are affected by an interaction of disease severity and FTLD and TMEM106B genotypes. Further work is needed to determine its value as a clinical biomarker.

AbstractBackgroundThe pathophysiological mechanisms driving frontotemporal lobar degeneration (FTLD) disease progression and corresponding biomarkers that capture these changes are not fully understood. We leveraged high‐throughput proteomics to identify networks of co‐expressed CSF proteins and candidate biomarkers for prediction of disease progression in adults with autosomal dominant FTLD mutations.Method113 adults carrying autosomal dominant FTLD mutations (C9orf72/GRN/MAPT) and 38 noncarrier controls from the ALLFTD consortium completed baseline lumbar puncture and longitudinal neuropsychological testing. CSF was assayed for SOMAmer proteomics on SOMAscan® v3.0 (4,140 proteins). Network analysis identified weighted protein co‐expression modules, which were annotated via gene ontology and cell‐type enrichment analysis. Disease age estimates that capture proximity to symptom onset were derived from a Bayesian disease progression model incorporating genotype‐specific clinical (cognition, CDR®+NACC FTLD) and biomarker (brain volume, plasma NfL) information. At baseline, local‐weighted regression examined module z‐scores (based on mean/SD of module levels [first principal component] in noncarriers) in relation to disease age. Longitudinal linear mixed‐effects models examined global cognitive trajectories in relation to baseline module z‐scores, as well as individual proteins within prognostic modules.ResultNetwork analysis identified 32 CSF protein co‐expression modules (37 to 223 proteins/module). 16 modules showed mutation‐related deviations from noncarriers. Deviations in ion transport, neurodevelopmental, metabolic, and transcriptional modules occurred several decades before estimated symptom onset (disease age: ‐30 to ‐20 years) and persisted across disease age. Deviations in neuroinflammatory and ubiquitination/autophagy modules occurred ∼10 years before estimated symptom onset. Sharp deviations in RNA binding, protein phosphorylation, neurogenesis, synaptic function, and lysosomal modules occurred near symptom onset (disease age: ‐1 to 4 years). Baseline synaptic and neurogenesis modules were the strongest prognosticators of cognitive decline (module x time: bs>.10, ps<.05). Within these modules, individual proteins with stronger intramodular connectivity exhibited stronger associations with cognitive decline (e.g., synaptic/transmembrane module: r = .40, p = 2.85e‐6; e.g., EPHA5, LRRTM2).ConclusionLarge‐scale analysis of the CSF proteome reveals a biologically‐diverse landscape of protein networks associated with presymptomatic and symptomatic stages of autosomal dominant FTLD. Synaptic and neuron‐enriched protein networks exhibited prodromal deviations that forecasted incipient cognitive decline. ‘Hub’ proteins derived from these affected networks warrant further validation as candidate biomarkers for early FTLD disease progression.

AbstractBackgroundCharacterizing disease trajectories in frontotemporal lobar degeneration (FTLD) is essential to determine the optimal timing for initiating therapeutic interventions, and there is an urgent need for novel and sensitive disease biomarkers. Intrinsic connectivity network (ICN) mapping using task‐free fMRI is a promising biomarker which reveals early abnormalities even before symptomatic onset (Dopper et al. 2014; Lee et al. 2016). Yet, ICN trajectories from the presymptomatic to symptomatic stages in FTLD mutation carriers remain unclear.MethodIn this cross‐sectional study, we used UCSF and ALLFTD Consortia data to study 129 carriers with variants in MAPT (presymptomatic/prodromal/symptomatic: 34/4/7), C9orf72 (30/9/12) and GRN (22/4/7). Using cross‐sectional data to construct ICN trajectories by genotype, we built separate generalized additive models for each genetic group to estimate non‐linear relationships between standardized connectivity changes and disease age across clinical stages. ICN connectivity was based on seed‐based analyses for networks associated with common clinical syndromes for each genetic group (i.e., salience and default mode [MAPT/C9orf72/GRN], corticobasal syndrome [MAPT/GRN], progressive supranuclear palsy syndrome [MAPT], sensorimotor and medial pulvinar‐related [C9orf72], and non‐fluent variant primary progressive aphasia (nfvPPA) syndrome networks [GRN]). We included 127 healthy controls as a reference to calculate ICN z‐scores for each carrier. Each carrier’s disease age was defined as the difference between the carrier’s chronological age and estimated age of onset based on multimodal measures of structural imaging, fluid biomarker and clinical assessments (Staffaroni et al. 2022).ResultIn MAPT+, presymptomatic carriers showed declining salience network connectivity starting approximately 30 years before estimated onset, which plateaued about 20 years before onset. In C9orf72+, salience network hyperconnectivity emerged about 30 years before onset and declined throughout the presymptomatic and symptomatic stages. For GRN+, connectivity changes as a function of disease age were found within the salience and nfvPPA networks, with connectivity stable until around 10 years before estimated onset, followed by decline starting in the late presymptomatic phase and continuing through the prodromal and symptomatic stages.ConclusionThese findings demonstrate that FTLD genes show distinct ICN trajectories throughout the clinical spectrum. These results help pave the way for determining the optimal timing to initiate therapeutic interventions.