Examining Associations Between Smartphone Use and Clinical Severity in Frontotemporal Dementia: Proof-of-Concept Study

BackgroundFrontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals aged <65 years. Several challenges to conducting in-person evaluations in FTLD illustrate an urgent need to develop remote, accessible, and low-burden assessment techniques. Studies of unobtrusive monitoring of at-home computer use in older adults with mild cognitive impairment show that declining function is reflected in reduced computer use; however, associations with smartphone use are unknown.ObjectiveThis study aims to characterize daily trajectories in smartphone battery use, a proxy for smartphone use, and examine relationships with clinical indicators of severity in FTLD.MethodsParticipants were 231 adults (mean age 52.5, SD 14.9 years; n=94, 40.7% men; n=223, 96.5% non-Hispanic White) enrolled in the Advancing Research and Treatment of Frontotemporal Lobar Degeneration (ARTFL study) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS study) Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) Mobile App study, including 49 (21.2%) with mild neurobehavioral changes and no functional impairment (ie, prodromal FTLD), 43 (18.6%) with neurobehavioral changes and functional impairment (ie, symptomatic FTLD), and 139 (60.2%) clinically normal adults, of whom 55 (39.6%) harbored heterozygous pathogenic or likely pathogenic variants in an autosomal dominant FTLD gene. Participants completed the Clinical Dementia Rating plus National Alzheimer's Coordinating Center Frontotemporal Lobar Degeneration Behavior and Language Domains (CDR+NACC FTLD) scale, a neuropsychological battery; the Neuropsychiatric Inventory; and brain magnetic resonance imaging. The ALLFTD Mobile App was installed on participants' smartphones for remote, passive, and continuous monitoring of smartphone use. Battery percentage was collected every 15 minutes over an average of 28 (SD 4.2; range 14-30) days. To determine whether temporal patterns of battery percentage varied as a function of disease severity, linear mixed effects models examined linear, quadratic, and cubic effects of the time of day and their interactions with each measure of disease severity on battery percentage. Models covaried for age, sex, smartphone type, and estimated smartphone age.ResultsThe CDR+NACC FTLD global score interacted with time on battery percentage such that participants with prodromal or symptomatic FTLD demonstrated less change in battery percentage throughout the day (a proxy for less smartphone use) than clinically normal participants (P<.001 in both cases). Additional models showed that worse performance in all cognitive domains assessed (ie, executive functioning, memory, language, and visuospatial skills), more neuropsychiatric symptoms, and smaller brain volumes also associated with less battery use throughout the day (P<.001 in all cases).ConclusionsThese findings support a proof of concept that passively collected data about smartphone use behaviors associate with clinical impairment in FTLD. This work underscores the need for future studies to develop and validate passive digital markers sensitive to longitudinal clinical decline across neurodegenerative diseases, with potential to enhance real-world monitoring of neurobehavioral change

Evidence against a temporal association between cerebrovascular disease and Alzheimer’s disease imaging biomarkers

Abstract Whether a relationship exists between cerebrovascular disease and Alzheimer’s disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer’s disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual’s amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = −0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET

Feasibility and acceptability of remote smartphone cognitive testing in frontotemporal dementia research.

IntroductionRemote smartphone assessments of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) could enable decentralized clinical trials and improve access to research. We studied the feasibility and acceptability of remote smartphone data collection in FTD research using the ALLFTD Mobile App (ALLFTD-mApp).MethodsA diagnostically mixed sample of 214 participants with FTD or from familial FTD kindreds (asymptomatic: CDR®+NACC-FTLD&nbsp;=&nbsp;0 [N&nbsp;=&nbsp;101]; prodromal: 0.5 [N&nbsp;=&nbsp;49]; symptomatic ≥1 [N&nbsp;=&nbsp;51]; not measured [N&nbsp;=&nbsp;13]) were asked to complete ALLFTD-mApp tests on their smartphone three times within 12 days. They completed smartphone familiarity and participation experience surveys.ResultsIt was feasible for participants to complete the ALLFTD-mApp on their own smartphones. Participants reported high smartphone familiarity, completed ∼ 70% of tasks, and considered the time commitment acceptable (98% of respondents). Greater disease severity was associated with poorer performance across several tests.DiscussionThese findings suggest that the ALLFTD-mApp study protocol is feasible and acceptable for remote FTD research.HighlightsThe ALLFTD Mobile App is a smartphone-based platform for remote, self-administered data collection.The ALLFTD Mobile App consists of a comprehensive battery of surveys and tests of executive functioning, memory, speech and language, and motor abilities.Remote digital data collection using the ALLFTD Mobile App was feasible in a multicenter research consortium that studies FTD. Data was collected in healthy controls and participants with a range of diagnoses, particularly FTD spectrum disorders.Remote digital data collection was well accepted by participants with a variety of diagnoses

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects