Staffaroni, Adam M.

Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility of passive smartphone monitoring in FTLD using a multi-domain mobile assessment platform. Methods: Participants were 567 adults (53% clinically normal, 21% prodromal FTLD, 26% symptomatic FTLD) who completed an in-person study visit and downloaded the ALLFTD Mobile App on their personal smartphones. The app delivered unsupervised cognitive tests and passively collected continuous data on battery percentage (proxy for smartphone use) and step count. Longitudinal follow-up included smartphone monitoring and annual in-person study visits. Primary analyses examined associations between passive smartphone features and markers of disease severity at baseline and longitudinally, and tested whether passive features added incremental value beyond app-based cognitive testing. Results: Passive smartphone features were feasible to collect and showed excellent reliability with <2 weeks of monitoring (ICCs>0.9). Features capturing smartphone use and movement demonstrated sensitivity to gold-standard clinical measures of disease severity both at baseline and longitudinally. A classification model combining passive features, the app-based cognitive composite score, and demographics detected longitudinal functional decline (AUC=0.89); passive features alone (AUC=0.84) performed comparably to a cognitive screener (AUC=0.85). Discussion: Passive smartphone monitoring is a valid, zero-burden measure of disease severity and progression in FTLD that adds modest incremental value beyond app-based cognitive testing. Findings support its use as a scalable digital endpoint in longitudinal FTLD research.

Importance Classifying disease based on underlying pathobiology rather than clinical phenotype has implications for the development of biomarkers and therapy development. Observations Transactive response DNA-binding protein 43 kDa (TDP-43) pathology is observed across a range of clinically defined neurodegenerative disorders including limbic predominant age-related encephalopathy (LATE), most cases of amyotrophic lateral sclerosis (ALS), inclusion body myositis, multisystem proteinopathy, and approximately half the cases of frontotemporal dementia (FTD). Despite this shared biology, the current nosology for these neurodegenerative disorders is based on their distinct clinical phenotypes. An alternative approach recognizes the central role of TDP-43 pathology in disease pathogenesis, reserving the use of clinical terms like ALS, FTD, or LATE to describe phenotypic manifestations of underlying pathobiology. This approach also recognizes the converging biomarker and neuropathological data indicating that pathology begins presymptomatically, before the overt clinical manifestations of disease appear. Conclusions and Relevance In proposing a pathobiological definition of disease, the goal is to provide a road map for developing biomarkers that accurately reflect the underlying pathobiology of disease and for advancing therapeutic candidates that effectively target fundamental disease mechanisms.

Background Motor disturbances are common in neurologic and neurodegenerative syndromes. A standard motor speed and dexterity measure is the finger tapping test (FTT). The FTT has traditionally been administered in clinic using a mechanical FTT, limiting accessibility and early motor change quantification. This study assessed the validity of a smartphone app-based FTT, which may expand access and enable more frequent testing. Methods The cohort was diagnostically diverse, including participants with frontotemporal dementia (FTD), progressive supranuclear palsy (PSP), corticobasal syndrome, primary progressive aphasia, multiple sclerosis, and clinically unimpaired controls. Participants completed a 20-second ALLFTD Mobile App (mApp)-FTT with each hand. Tapping speed metrics were extracted. Participants completed the gold-standard mechanical FTT, a neurologist-administered finger tapping exam, the PSP Rating Scale (PSPRS) and the Unified Parkinson’s Disease Rating Scale (UPDRS). Correlations assessed mApp-FTT and mechanical FTT relationships; regressions evaluated associations with neurologist-rated finger tapping impairment, PSPRS and UPDRS, adjusting for age and sex. Results The mApp-FTT showed moderate-to-strong correlations with the mechanical FTT (dominant: r=0.63, p<0.001; non-dominant: r=0.55, p<0.001). Taps per second were associated with PSPRS motor severity (dominant hand: std. β=-0.59, 95% CI [-0.91, -0.27], p<0.001) and the UPDRS (dominant hand: std. β=-0.41, 95% CI [-0.82, 0.00], p=0.049). Flight time was modestly associated with neurologist-rated finger tapping impairment (dominant hand: std. β=0.15, 95% CI [0.00, 0.29], p=0.044). Conclusion These findings support mApp-FTT validity as a measure of motor function across neurodegenerative conditions. Validation in longitudinal and unsupervised remote settings is warranted to understand scalability and evaluate change over time.

Importance TMEM106B is a frontotemporal lobar degeneration (FTLD) genetic susceptibility factor, and TMEM106B protein aggregates are a feature of aging and neurodegeneration. Whether TMEM106B protein levels are associated with clinical features is unknown. Objective To investigate the clinical associations of cerebrospinal fluid (CSF) TMEM106B in FTLD. Design, Setting, and Participants This cross-sectional study was conducted in 2 independent frontotemporal dementia (FTD) cohorts (recruitment from April 2009 through July 2023, with analyses from January 2025 through April 2026), with a 2-year follow up. This multicenter clinical study integrated clinical, genetic, biomarker, and neuroimaging data. Individuals were recruited through the University of California, San Francisco (n = 3733), or ALLFTD (n = 2343). Participants with available CSF were included. A discovery cohort (n = 271) included participants with sporadic neuropathology-confirmed FTLD; presymptomatic or symptomatic carriers of pathogenic variants in C9orf72 , GRN , or MAPT ; or controls. An independent validation cohort (n = 383) included participants with clinically diagnosed sporadic FTD, Alzheimer disease (AD), and controls. Exposures CSF samples for TMEM106B quantification with aptamer proteomics (SomaScan version 3.0 [discovery cohort] and SomaScan version 4.1 [validation cohort]). Main Outcomes and Measures Parametric tests compared the primary outcome, CSF TMEM106B, by disease severity, TMEM106B rs1990622 genotype, sex, clinical syndrome, pathological diagnosis, and pathogenic variant and determined associations with brain volume. Results In the discovery (n = 271; 136 women [51%]; median [IQR] age, 59 [38-80] years) and validation (n = 383; 183 women [48%]; median [IQR] age, 64 [50-78] years) cohorts, lower CSF TMEM106B was associated with more severe disease (β, −0.15; 95% CI, −0.24 to −0.04; P = .003), lower frontotemporal brain volumes (β, 0.42; 95% CI, 0.24-0.61; P &amp;lt; .001), and faster clinical progression (β, −2.21; 95% CI, −3.70 to −0.72; P = .001). Associations of TMEM106B with clinical disease severity were independent of those with neurofilament light chain. TMEM106B levels were influenced by TMEM106B rs1990622 genotype, where individuals with the protective G/G genotype had lower levels than the risk A/A genotype. CSF TMEM106B levels did not differentiate between FTLD subtypes or between FTLD and AD. Conclusions and Relevance Per the results of this cross-sectional study, TMEM106B is detectable in CSF and levels reflect disease severity in sporadic and genetic FTLD and AD, but levels are also influenced by the TMEM106B rs1990622 genotype. CSF TMEM106B could support further studies to understand the mechanisms of disease and develop clinical tools in FTLD and other neurodegenerative diseases.

Abstract BACKGROUND Remote, smartphone‐based cognitive testing may improve access to cognitive assessments for Alzheimer's disease and related dementias. We evaluated the feasibility, reliability, and validity of unsupervised smartphone‐based cognitive tests in a registry‐based cohort. METHODS Adults without a record of cognitive impairment ( N = 1815; ages 18–92) were recruited from the University of California, San Francisco (UCSF) Brain Health Registry to complete three unsupervised smartphone cognitive testing sessions within 2 weeks. Reliability was assessed with correlations between sessions. Linear regression models tested associations of smartphone tasks with demographics, self‐ and informant‐rated cognitive concerns, and web‐based cognitive testing (Cogstate Brief Battery). RESULTS Adherence was high (82.2%) and usability favorable. Test–retest reliability was moderate to strong ( ρ ’s = 0.61–0.85, all p ’s < 0.001). Lower smartphone scores were associated with older age, lower education, cognitive concerns, and worse Cogstate performance. DISCUSSION Findings support the feasibility, reliability, and validity of remote digital assessments in adults without a record of cognitive impairment.

ABSTRACT Background and Objectives Converging evidence hints at neurodevelopmental effects in genetic frontotemporal degeneration (FTD). In cross-sectional studies, for some genes, young adult FTD variant carriers show differences in brain volumes and cognition compared to familial non-carriers. However, longitudinal trajectories may more sensitively capture FTD-related neurodevelopmental vs. neurodegenerative changes than cross-sectional approaches. This study examined longitudinal trajectories of brain volumes, executive function, and plasma biomarkers in young adult carriers compared to familial non-carriers, as measures of neurodevelopmental and neurodegenerative outcomes of FTD-causing variants. Methods This longitudinal cohort study comprised participants, aged 18-30 years, from the FTD Prevention Initiative across Europe, Canada, and the USA. Genetic groups included C9orf72 (47%), MAPT (30%), and GRN (23%). Linear mixed-effects models were computed to assess longitudinal outcomes across age between groups, controlling for sex, scanner (for brain volumes), and education (for executive function); random effects accounted for between-subject variability nested within family membership. Results Variant carriers ( n =147) and familial non-carriers ( n =113) did not differ in age (mean±SD, 25.9±3.2 years), sex (53% female), or number of visits (2.1±1.7). Young adult C9orf72 repeat expansion carriers exhibited smaller thalamic volumes than non-carriers at the reference age of 26 years ( b =-982.8mm 3 , SE=317.0, p= 0.0046, f 2 =0.32), with relatively stable trajectories across ages 18-30 (i.e., no change over time). Trajectories of rostral anterior cingulate volumes differed in C9orf72 carriers and non-carriers across age, where carriers showed relatively stable trajectories and non-carriers showed age-appropriate declines ( b =64.4mm 3 , SE=29.9, p= 0.035, f 2 =0.07). For MAPT and GRN , there were little to no differences in total brain, cortical, or subcortical volumes between groups and over time. No longitudinal differences were observed between carriers and non-carriers in executive function, or plasma NfL or GFAP for any genetic group. Discussion C9orf72 repeat expansions were linked to smaller average thalamic volumes and stable trajectories between ages 18 to 30, supporting potential neurodevelopmental origins. The modest evidence supporting an absence of difference in neurodegenerative biomarkers and executive function suggests minimal early neurodegeneration and functional preservation in young adulthood.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Abstract Background TMEM106B encodes a lysosomal protein and is a genetic susceptibility factor for frontotemporal lobar degeneration (FTLD). Aptamer‐based proteomics quantifies TMEM106B protein levels in CSF. The associations of CSF TMEM106B with measures of disease severity have not been previously evaluated, and the value of CSF TMEM106B as a clinical biomarker is unknown. Method CSF TMEM106B and NfL protein levels were quantified with aptamer‐based proteomics in participants from two independent cohorts: sporadic FTLD with neuropathology‐confirmed FTLD‐tau and FTLD‐TDP, clinically diagnosed PSP‐Richardson Syndrome, and controls (UCSF MAC, n = 95; mean age = 69 ± 6 yrs; 48% female) and familial FTLD comprised of presymptomatic and symptomatic FTLD mutation carriers with family non‐carrier controls (ALLFTD, n = 179; mean age = 49 ± 13 yrs; 53% female). The association between biomarkers and diverse measures of disease severity, including the CDR®+NACC‐FTLD and CDR®+NACC‐FTLD sum of boxes, were determined with linear regressions or mixed linear models. Associations with brain volumes were determined within the framework of voxel‐based morphometry. Result In both cohorts, at baseline, CSF TMEM106B did not differ by sex, age, FTLD phenotype, or CSF NfL. CSF TMEM106B was lower in cases with worse disease severity (Figure 1) and in participants with the protective TMEM106B rs1990622 G/G genotype, regardless of pathological diagnosis or FTLD‐causing mutation. Low CSF TMEM106B was associated with more severe longitudinal worsening in FTLD disease severity (Figure 2), basic and instrumental function, global cognition, executive function, and depression scores. These associations were weaker than those of NfL. Low CSF TMEM106B was associated with low brain volumes in frontal, parietal, and temporal regions (FWE‐corrected p < 0.05) (Figure 3A). CSF NfL negatively correlated (FWE‐corrected p < 0.05) with brain volumes in frontotemporal regions (Figure 3B). Conclusion CSF TMEM106B concentrations are influenced by the TMEM106B rs1990622 genotype, and correlate with disease severity and brain volume in both genetic and sporadic FTLD. Lower levels of CSF TMEM106B correlate with more severe disease and brain atrophy. Disease severity is more strongly associated with CSF NfL, while brain volumes are more strongly associated with CSF TMEM106B. CSF TMEM106B may have value as a biomarker of neurodegeneration in FTLD.

Abstract Background Motor disturbances are common in neurodegenerative disorders. Digital health technologies can be a tool for remote, accessible, and low‐burden motor assessments. The ALLFTD Mobile App includes a finger‐tapping test (mApp‐FTT) to assess dexterity. We evaluated the reliability and construct validity of smartphone‐based measures of finger tapping in an in‐person sample. Methods Participants ( n = 33; mean age=68.2 [SD=8.6]) completed the mobile finger‐tapping test (mApp‐FTT) on iOS and Android devices (two counterbalanced 20‐second trials per hand) and the mechanical finger‐tapping test (FTT). The sample included cognitively unimpaired participants (22.2%) and those diagnosed with frontotemporal dementia‐spectrum disorders (41.7%), Alzheimer's dementia (22.2%), and progressive supranuclear palsy or corticobasal syndrome (13.9%). A motor domain was calculated based on neurological exam and added to the Clinical Dementia Rating® plus National Alzheimer's Coordinating Center–Frontotemporal Lobar Degeneration (CDR®+NACC‐FTLD). Pearson's correlations assessed associations between mApp‐FTT performance and FTT performance, clinical severity (CDR®+NACC‐FTLD Box Score), motor rating scales (Progressive Supranuclear Palsy Rating Scale [PSPRS] and Unified Parkinson's Disease Rating Scale [UPDRS]), and cognitive function. Due to small sample size, PSPRS subdomains were dichotomized, and t‐tests were performed to evaluate group differences based on symptom presence. Results Total mApp‐FTT taps on iOS and Android were strongly correlated ( r = 0.86, 95% CI [0.76, 0.92], p < .001). mApp‐FTT was associated with manual FTT on iOS ( r = 0.70, 95% CI [0.52, 0.82], p < .001) and Android ( r = 0.62, 95% CI [0.41, 0.77], p < .001). Among iOS users, total PSPRS score was negatively correlated with mApp‐FTT ( r = ‐0.60, 95% CI [‐0.75, ‐0.39], p < .001). Worse mApp‐FTT performance was observed in participants with higher limb rigidity (mean difference=15.46, 95% CI [3.40, 27.52], p < .001), limb dystonia (mean difference=19.22, 95% CI [5.67, 32.77], p < .001), and finger tapping (mean difference=12.74, 95% CI [3.42, 22.06], p < .001). Total UPDRS score correlated with lower mApp‐FTT ( r = ‐0.48, 95% CI [‐0.66, ‐0.28], p < .001), as did disease severity (CDR®+NACC‐FTLD Box Score; r=‐0.46, 95% CI [‐0.66, ‐0.22], p < .001). Conclusion Smartphone‐based finger‐tapping assessments effectively detect motor and cognitive impairment, with stronger associations for motor function. Findings in iOS users highlight the need to assess operating system‐related biases and validate in Android. Remote smartphone assessments offer a scalable tool for tracking disease progression, warranting larger longitudinal studies.