Rosen, Howard J.

AbstractBackgroundFrontotemporal dementia (FTD) is a common young‐onset dementia. Challenges to in‐person FTD evaluations (e.g., behavioral symptoms, disease rarity), highlight the need to develop remote, low‐burden assessment techniques. A growing literature supports passive digital phenotyping for monitoring neurobehavioral change. Thus, we examined the utility of passively collected data from smartphones to detect prodromal or symptomatic FTD compared to that of the Montreal Cognitive Assessment (MoCA), a common cognitive screener.Method199 adults enrolled in the ALLFTD Mobile App study (mean age = 53.4 [SD = 15.2]; 58% women) completed up to 6 months of passive smartphone monitoring via the ALLFTD Mobile App. 55% were unimpaired [CDR®+NACC FTLD = 0], 22% had prodromal FTD [CDR®+NACC FTLD = 0.5], and 23% had symptomatic FTD [CDR®+NACC FTLD≥1] with a variety of syndromic presentations. Battery percentage was collected frequently (median interval = 45 min), and total daily battery usage was calculated as a proxy for smartphone use (higher battery usage = more smartphone use). Daily step counts were also passively collected. Logistic regression classified prodromal or symptomatic FTD vs. unimpaired as a function of: MoCA score [Model 1]; 7 passive features characterizing average, inter‐day variability, and changes over time in smartphone use and movement [Model 2]; or passive smartphone features and MoCA [Model 3]. Analyses were repeated excluding participants with symptomatic FTD to detect prodromal FTD vs. unimpaired.ResultThe area under the curves (AUCs) for detecting prodromal or symptomatic FTD (vs. unimpaired) from the MoCA alone [Model 1] and passive smartphone features alone [Model 2] were 0.77 (95%CI: 0.70‐0.85) and 0.77 (95%CI: 0.70‐0.84), respectively. Their combination [Model 3] resulted in a significantly improved AUC of 0.86 (95%CI: 0.80‐0.92) compared to Model 1 (p = 0.001). Significant Model 3 predictors included average daily battery usage (p = 0.02), slopes of change in step count (p = 0.04), and MoCA score (p<0.01). When distinguishing prodromal FTD from unimpaired, passive smartphone features alone (AUC = 0.75) were significantly better than the MoCA alone (AUC = 0.66; p<0.01), and their combination had the largest AUC (0.80).ConclusionResults support the utility of novel passively collected information from smartphones for detecting and monitoring FTD without contributing to assessment burden. With continued validation, passive digital monitoring methodologies have potential to increase access to dementia care.

AbstractBackgroundFrontotemporal dementia (FTD) presents with heterogeneous neuropsychiatric symptoms (NPS). These symptoms often begin prior to the onset of FTD, and progress throughout the prodromal stages of FTD. Particularly, familial FTD due to autosomal dominant genetic mutations might display mutation‐specific NPS profiles. We hypothesized distinct NPS trajectories for chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), and microtubule‐associated protein tau (MAPT) mutation carriers during their transition from presymptomatic to symptomatic stages of FTD.MethodIn this study, we analyzed N = 1662 participants from the ARTFL‐LEFFTDS Longitudinal FTLD (ALLFTD) Study, with 342 C9orf72, 148 GRN, 168 MAPT mutation carriers, and 1004 noncarriers. We used the CDR plus NACC FTLD global scores to define the conversion status, and stratified participants into four stages of progression: 1) Presymptomatic (CDR = 0 throughout the follow‐up), 2) Early conversion (began with CDR = 0, then increased to 0.5), 3) Advanced conversion (began with CDR = 0.5, then increased to 1.0 or above), and 4) Symptomatic (CDR>1.0 throughout). Over up to seven visits, the Neuropsychiatric Inventory Questionnaire (NPI‐Q) assessed changes in NPS. We analyzed total NPI‐Q score trajectories using a generalized linear mixed‐effects model, adjusting for age and baseline NPI‐Q scores.ResultOur findings showed similar NPS trajectories among carriers and noncarriers during presymptomatic stages. However, in the early conversion stage, C9orf72 and GRN carriers exhibited significantly higher NPI‐Q score increases compared to MAPT carriers, primarily in the psychosis and hyperactivity domains. In the advanced and symptomatic stages, the rate of increase in NPS was not significantly different across groups.ConclusionThis study suggests that people with familial FTD, particularly those predicted to have underlying TDP‐43 pathology, may experience more severe neuropsychiatric symptoms like psychosis or hyperactivity as they progress from presymptomatic to prodromal phases. This trajectory appears distinct from those with tau pathology or sporadic FTD. Further studies are warranted to understand these unique progression patterns and their implications for FTD management.

Abstract Objective To identify and disseminate research priorities for the headache field that should be areas of research focus during the next 10 years. Background Establishing research priorities helps focus and synergize the work of headache investigators, allowing them to reach the most important research goals more efficiently and completely. Methods The Headache Research Priorities organizing and executive committees and working group chairs led a multistakeholder and international group of experts to develop headache research priorities. The research priorities were developed and reviewed by clinicians, scientists, people with headache, representatives from headache organizations, health‐care industry representatives, and the public. Priorities were revised and finalized after receiving feedback from members of the research priorities working groups and after a public comment period. Results Twenty‐five research priorities across eight categories were identified: human models, animal models, pathophysiology, diagnosis and management, treatment, inequities and disparities, research workforce development, and quality of life. The priorities address research models and methods, development and optimization of outcome measures and endpoints, pain and non‐pain symptoms of primary and secondary headaches, investigations into mechanisms underlying headache attacks and chronification of headache disorders, treatment optimization, research workforce recruitment, development, expansion, and support, and inequities and disparities in the headache field. The priorities are focused enough that they help to guide headache research and broad enough that they are widely applicable to multiple headache types and various research methods. Conclusions These research priorities serve as guidance for headache investigators when planning their research studies and as benchmarks by which the headache field can measure its progress over time. These priorities will need updating as research goals are met and new priorities arise.

Abstract Approximately 5% of Alzheimer’s disease patients develop symptoms before age 65 (early-onset Alzheimer’s disease), with either sporadic (sporadic early-onset Alzheimer’s disease) or dominantly inherited (dominantly inherited Alzheimer’s disease) presentations. Both sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer’s disease and dominantly inherited Alzheimer’s disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer’s disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer’s Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer’s disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50–70 cerebellar grey reference and FDG30–60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer’s disease, sporadic early-onset Alzheimer’s disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen’s d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer’s V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer’s disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer’s disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer’s disease versus sporadic early-onset Alzheimer’s disease. Sporadic early-onset Alzheimer’s disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer’s disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer’s disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer’s disease.

ImportanceFrontotemporal 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.ObjectiveTo evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations.Design, Setting, and ParticipantsIn 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.ExposureParticipants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests.Main Outcomes and MeasuresInternal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy.ResultsIn 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 β 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 β = −0.49 [95% CI, −0.72 to −0.25]; P &amp;lt; .001) but not a composite of traditional neuropsychological measures (β = −0.14 [95% CI, −0.42 to 0.14]; P = .32).Conclusions and RelevanceThe 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.

AbstractBackgroundThe rural‐urban commuting area (RUCA) codes classify communities using measures of population density, urbanization, and daily commuting from U.S. Census Bureau information. The ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study generated RUCA codes for enrolled participants to better understand our cohort demographics. The rural‐urban distribution of participants may provide important insights for clinical trial planning.MethodsThe current RUCA codes are generated from the 2010 decennial census and the 2006‐10 American Community Survey data. The codes are numbers (1‐10) that describe metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows.ResultsRUCA codes were generated on 784 ALLFTD participants. At their most recent visit, participant median age was 60, 51.1% female, and a median education of 16 years. Participants were classified as clinically normal (39.1%), behavioral variant FTD (25%), nonfluent PPA (6.7%), semantic variant PPA (6.6%), PSP (4.7%), MBCI (4.8%), corticobasal syndrome (5.9%), and the remaining 7% of participants had other dementia‐related diagnoses. For participants with sporadic disease, 87.4% live in a metropolitan area, 6.7% a micropolitan area, 3.2% a small‐town area, and 3.2% live in a rural area. In familial FTLD, a larger percentage of participants live in micropolitan or small town/rural community (18.8% combined; p = 0.029), driven largely by MAPT family participants (n = 101). 10% of those with a familial MAPT mutation live in a rural area; with an additional 18% in micropolitan (12.9%) or small‐town areas (5%). Among those with a familial C9orf72 expansion, 83.3% live in a metropolitan area, 8.9% micropolitan area, 5.6% in a small‐town area, and 2.2% in a rural area. Participants with a familial GRN mutation show a similar distribution: 84.7% live in a metropolitan area, 5.6% micropolitan, 6.9% small‐town, 2.8% rural.ConclusionsAdditional analyses to better understand if FTD families are disproportionately living in rural communities are underway. These analyses will better characterize sporadic and familial FTD demographics to assist with clinical trial design.

AbstractBackgroundCardiovascular health plays an important role in brain aging; yet its role in development of autosomal dominant forms of dementia and frontotemporal dementia (FTD) has not been fully elucidated. Life’s Simple 7 (LS7) is a metric of cardiovascular health associated with reduced dementia risk and may represent a transdiagnostic heuristic to promote brain health. We examined the extent to which baseline LS7 associated with cognitive and brain aging trajectories in individuals with genetic FTD.Method243 adults carrying autosomal dominant genetic mutations for FTD and 189 non‐carriers completed neuroimaging, neuropsychological testing, and medical interviews. LS7 at baseline was computed following established procedures based on physical activity, diet, body mass index, smoking, hypertension, diabetes, and hypercholesterolemia; higher scores indicate more optimal cardiovascular health. We examined interactions between baseline LS7 and mutation carrier status on cognitive and brain structural outcomes at baseline (via linear regression) and longitudinally (via linear mixed‐effects models). All models adjusted for baseline age, sex, and education, and CDR®+NACC FTLD.ResultMutation carriers and non‐carriers did not significantly differ on baseline LS7 (t = ‐1.42, p = 0.156). At baseline, there were significant interactions between LS7 and carrier status on frontotemporal (FTL) volume and executive functioning (all p‐values<0.046), such that positive associations between LS7 and neurobehavioral outcomes were stronger among mutation carriers versus noncarriers. Longitudinally, there was also a significant interaction between carrier status and baseline LS7 on memory over time (b = 0.04,p = 0.035) and the interaction approached significance for language trajectories (b = 0.03,p = 0.079); again, the association between higher LS7 and slower cognitive decline was stronger among mutation carriers versus noncarriers, even when excluding symptomatic carriers (b = 0.04,p = 0.047). Among mutation carriers only, higher baseline LS7 related to slower memory (b = 0.04,p = 0.006) and language declines over time (b = 0.044,p = 0.004), but did not significantly relate to FTL volume (b = ‐0.01,p = 0.307) or executive functioning trajectories (b = 0.004,p = 0.913)ConclusionBetter cardiovascular health relates to larger baseline frontotemporal volume and slower cognitive decline in individuals with autosomal dominant FTD. Interaction models suggested the degree to which cardiovascular health associates with better neurobehavioral outcomes is stronger in mutation carriers. Optimizing cardiovascular health may be a particularly important, modifiable approach to mitigate the symptoms associated with pathogenic variants of FTD.

Abstract Background The ALLFTD (ARTFL‐LEFFTDS Longitudinal Frontemporal 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. ALLFTD represents the merger and continuation of two prior studies: Advancing Research and Treatment of Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS). Methods ALLFTD recruits participants with FTLD spectrum disorders (bvFTD, svPPA, nfvPPA, FTD‐ALS, CBS or PSP), with strong family histories of FTLD, or known FTLD‐associated genetic variants within the family. 26 sites in North America enroll participants for clinical and neuropsychological evaluations, MR Imaging, blood draws, and CSF collection in willing participants; participants are requested to return annually for follow‐up evaluation. All participants are genotyped for dementia‐associated mutations. Participants also enroll in the FTD Disorders Registry for follow‐up surveys. A subset of participants undergo remote assessment via the ALLFTD app. Visits conducted under ARTFL and LEFFTDS are included in the ALLFTD dataset. Results ALLFTD has been successful in developing methods to conduct remote or hybrid visits and in actively evaluating participants. Since ALLFTD began in January 2020, 1034 participants (736 new; 298 previously enrolled in ARTFL or LEFFTDS) have been evaluated in the longitudinal arm; an additional 119 participants have been participated in a shortened, biofluid‐focused visit. 349 have returned for follow‐up visits. Including prior participants, the ALLFTD dataset contains 3871 visits from 2343 individuals. 1277 people have sporadic syndromes; 1045 were enrolled as familial. Among s‐FTLD, bvFTD is the most common phenotype (32.8%) followed by PSP (15.9%). 61.4% of f‐FTLD participants were clinically normal at first visit; bvFTD is the most common syndrome in symptomatic f‐FTLD (40%). 477 are confirmed carriers of FTLD‐associated genetic mutations. MRIs were obtained for 2594 visits; 3492 visits have associated blood biospecimens banked; 978 visits have associated CSF samples. Conclusions The ALLFTD consortium is actively evaluating participants across North America to better characterize FTLD syndromes and support the planning and development of FTLD clinical trials. Longitudinal datasets including clinical, genetic, and imaging data are available by request.