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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.

AbstractBackgroundNeuropsychiatric symptoms (NPS) are frequent in Alzheimer’s Disease dementia (ADD) but a higher NPS burden is found in dementia with Lewy bodies (DLB). Lewy body (LB) pathology frequently co‐occurs with AD pathology and may not meet neuropathological criteria for DLB (ADLB). Previous studies have shown that both ADLB and DLB cases have faster cognitive and/or functional decline compared to AD. However, the differences in NPS severity over disease course and survival in these pathologic subgroups is not well understood.MethodCases from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with a final neuropathologic diagnosis of DLB (±AD co‐pathology; n = 65), ADLB (n = 89), AD (without LB) (n = 140), and controls (no neuropathological diagnosis) (n = 82) were included. Total NPI‐Q (scores ranging from 0‐36) at time of enrollment and within 2.5 years of death were calculated for all groups. Statistical analysis utilizing ANCOVA (adjusting for age, sex, baseline MMSE and cognitive symptom duration) with pairwise comparisons, and Kaplan‐Meier curves were completed.ResultAge at onset of cognitive symptoms was not different between pathology groups. NPI‐Q scores at enrollment were highest in ADLB (7.33 ± 4.85), and higher (p<0.001) than DLB (5.10 ± 3.37), AD (4.54 ± 3.63) and controls (1.78 ± 1.70). At final evaluation, NPI‐Q scores were highest in DLB (10.04 ± 6.28), followed by ADLB (8.0 ± 4.), and ADD (7.61 ± 5.05) when compared to controls (2.78 ± 3.97) (all p<0.001). DLB and AD demonstrated significant increases in NPI‐Q severity during follow up (p < 0.001). AD had longer survival time (5.8 years) compared to ADLB (4.0 years) and DLB (3.9 years). Subjects with NPS had a shorter median survival time (3.4 years) compared to subjects without NPS (6.5 years; p = 0.002).ConclusionA higher NPS burden and shorter survival is seen in both DLB and ADLB, as compared with AD. This suggests that diffuse neocortical LB pathology is not the major driver of either NPS or survival.

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.

AbstractBackgroundPathological Lewy body disease (LBD) may commonly present clinically as Parkinson’s disease dementia (PDD), Dementia with Lewy bodies (DLB) or Alzheimer’s disease dementia (ADD). Neuropathological definitions also include a group in which ADD is present, but the postmortem Lewy pathology does not meet threshold density and distribution levels for the neuropathological diagnosis of DLB (ADLB). Little is known about the cognitive profiles of patients with ADLB and despite common underlying pathology, studies delineating neuropsychological profiles in LBD are fraught with inconsistencies. We characterized the longitudinal cognitive trajectories defined by neuropsychological profiles in cases along the pathological spectrum of LBD.MethodCases from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with a cognitive diagnosis of dementia at death and who at minimum, had two neuropsychological evaluations were included. Final neuropathological diagnosis was determined as LBD (neocortical or limbic LB ± AD), ADLB, and AD pathology only. LBD cases were categorized by their cognitive clinical syndromes as PDD and DLB. Global cognition was evaluated using MMSE. Neuropsychological domains of Memory, Executive function, language, attention, and visuospatial were evaluated. Mixed linear methods were used to predict longitudinal change for a given baseline MMSE.Result287 participants and 1874 participant‐years of data were included in this study. LBD (n = 115), and ADLB (52) groups were predominantly male, while AD (n = 114) group was primarily female. Baseline MMSE was similar across all pathologic groups. Linear mixed modelling methods showed faster decrease in memory domain scores (decreasing 0.22 units/year – 0.42 units/year faster, p = 0.01) in ADLB group compared to other groups. Significantly faster decline was noted in LBD and ADLB group in clock drawing (p<0.001), fluency scores (declining 1.02 unit/year faster p<0.001) compared to AD group. There was no difference between PDD and DLB clinical subgroups.ConclusionIn autopsy confirmed cases, ADLB had an accelerated trajectory of decline in memory tasks, while AD, and LBD appeared to have similar trajectories. In contrast, all groups with Lewy bodies progressed faster and showed accelerated decline compared to AD in measures of frontal‐subcortical functions. These results may inform antemortem classification of patients and diagnostic accuracy in these groups.

AbstractBackgroundQuantified accelerated aging, or “age gap,” defined as the difference between a person’s estimated age using a biological measurement, such as a brain image, and their true age, has strong associations with multiple neurodegenerative etiologies. As an alternative to imaging‐based measurements, in this study we developed an age prediction model based on gait patterns and used this model to quantify accelerated aging as an indicator of cognitive impairment and predictor of future cognitive decline.MethodA database of 16,917 pressure sensitive walkway exams from 5,307 participants in the Mayo Clinic Study of Aging was used to develop an age estimation model that included two main components. First, a novel dimensionality reduction and feature selection algorithm was used to extract gait features. Second, a regularized linear model was trained using these features to produce a sparse, clinically interpretable estimator. This model was used to calculate a gait age gap metric, which was tested for association with measures of cognitive impairment and future cognitive decline.ResultThe distributions of gait age gap in age‐matched participants defined as having no cognitive impairment (CU, n = 573), mild cognitive impairment (MCI, n = 520), or a clinical diagnosis of dementia due to Alzheimer’s (AD, n = 53) are shown in Fig 1a. A significant shift in the mean is observed between all three groups. Fig 1b. shows the distributions of baseline gait age gap values amongst individuals categorized by cognitive decline: stable CU (n = 644), MCI converters (n = 89), stable MCI (n = 78), and significant impairment converters (SI, n = 35). The baseline gait age gap in stable CU individuals was found to be significantly lower than in the already impaired or converter groups.ConclusionIn this study, we developed a model for estimating accelerated aging from gait variables in the form of a gait age gap metric. This metric was shown to be strongly associated with AD‐driven cognitive impairment as well as predictive of future cognitive decline. These results highlight the potential clinical utility of quantitative gait analysis in behavioral neurologic assessment of cognitive impairment in AD.

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.

AbstractBackgroundGiven the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.MethodsGenome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsFirst, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.ConclusionsThese lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.

AbstractBackgroundThe ALLFTD Consortium aims to characterize preclinical and prodromal stage of familial Frontotemporal Lobar Degeneration (f‐FTLD) to prepare for clinical trials in FTLD.MethodWe prospectively followed 320 asymptomatic participants of the ALLFTD Consortium who are family members of f‐FTLD with a mutation in MAPT (n = 106), GRN (n = 74), or C9orf72 (n = 140), and describe the ratings on the eight domains of CDR® plus NACC FTLD (FTLD‐CDR) in those who phenoconverted to Mild Behavioral and/or Cognitive Impairment (MBCI). MBCI was diagnosed by the proposed research criteria for MBCI‐FTD (Barker MS, et al. Brain 2022). Participants who were diagnosed as MBCI but returned to asymptomatic at the following visit were excluded from the FTLD‐CDR assessment. ANOVA was used to compare continuous variables, and chi‐square test was used to compare categorical variables across the groups.ResultThirty‐six participants (15 MAPT, 9 GRN, 12 C9orf72) developed MBCI during follow‐up visits, 13 participants (5 MAPT, 3 GRN, 5 C9orf72) were diagnosed as MBCI but were characterized as asymptomatic at the following visit, and 271 participants stayed asymptomatic. Percentage of male in MBCI participants was 50% (MAPT 60%, GRN 33%, C9orf72 50%, p = 0.45). Age at phenoconversion to MBCI was 53.6±13.0 years old, the youngest in MAPT and the oldest in GRN participants (MAPT 44.3±8.3, GRN 63.1±11.3, C9orf72 56.4±10.8, p<0.001). Abnormal rating on each of the eight CDR® plus NACC FTLD domains at the initial visit of MBCI phenoconversion were observed in: “Memory” 36% (MAPT 33%, GRN 33%, C9orf72 44%, p = 0.95); “Orientation” 8% (MAPT 7%, GRN 8%, C9orf72 11%, p = 0.93); “Judgment/Problem Solving” 44% (MAPT 47%, GRN 50%, C9orf72 33%, p = 0.73); “Community Affairs” 22% (MAPT 27%, GRN 17%, C9orf72 22%, p = 0.82); “Home/Hobbies” 25% (MAPT 40%, GRN 8%, C9orf72 22%, p = 0.16); “Personal Care” 0%; “Behavior/Comportment/Personality” 44% (MAPT 60%, GRN 42%, C9orf72 22%, p = 0.19); “Language” 31% (MAPT 13%, GRN 50%, C9orf72 33%, p = 0.12).ConclusionThe three most common FTLD‐CDR domains initially disturbed in the prodromal stage of fFTLD were “Behavior/Comportment/Personality”, “Judgment/Problem Solving”, and “Memory”, while “Orientation” was intact in the majority of the individuals. Memory impairment without disorientation was seen in one‐third of the prodromal fFTLD participants.

AbstractBackgroundAfrican Americans (AA) represent 12% of the United States population ≥65 years‐old, but 19% of persons with dementia. Inequalities in social determinants of health may influence access to healthcare resources contributing to increased dementia risk. Modifiable risk factors, including vascular risk factors and depression, may contribute up to 40% of dementia risk and are overrepresented in AA. Accordingly, risk factor modification in AA may improve disparities and decrease dementia risk.MethodDementia risk factors were evaluated in community‐dwelling AA (n = 261) and non‐Hispanic White (NHW; n = 193) participants who completed ≥2 research visits in studies of memory and aging at the Mayo Clinic Florida Alzheimer Disease Research Center. The association between modifiable risk factors and cognitive impairment (global Clinical Dementia Rating® [CDR] ≥0.5), and rates of decline in impaired participants (measured using the CDR Sum‐of‐Boxes; CDR‐sb) were compared between AA and NHW, while controlling for demographics, APOEe4 status, and Area Deprivation Index.ResultModifiable dementia risk factors were common in AA and NHW participants. The ADI was higher in AA denoting greater socioeconomic and environmental deprivation [7.8 (2.3) vs. 4.0 (2.1); p<0.001]. History of stroke/transient ischemic attack (OR, CI95% = 2.52, 1.08‐5.83) was associated with an increased odds of dementia in AA participants only, while depression was associated with an increased odds of dementia in both AA (3.10, 1.52‐6.30) and NHW (3.46, 1.14‐10.48) participants. Moreover, depression (β, CI95% = 1.55, 0.5‐2.6), p = 0.004) was associated with a faster rate of decline (CDR‐sb) in cognitively impaired AA participants. AA participants with depression were disproportionately less likely to report use of antidepressant medications than NHW counterparts (40/45, 89% vs. 21/44, 48%); p<0.001).ConclusionModifiable risk factors associated with dementia were common in AA and NHW participants. Depression was associated with dementia in both AA and NHW but uniquely associated with an accelerated rate of cognitive decline in AA participants. Disparities in use of antidepressant medications may contribute to these differences. Optimizing depression treatment in AA communities may improve cognitive trajectories and dementia risk in this population.

AbstractBackgroundEasily accessible and self‐administered cognitive assessments that can aide early identification of individuals at risk for Alzheimer’s disease (AD) dementia are critical for timely intervention. Mayo Test Drive (MTD) is a remote, self‐administered, multi‐device compatible, web‐based cognitive assessment (Stricker et al., 2022). We investigated continuous associations between MTD and amyloid and tau PET biomarkers and compared the strength of association to PET biomarkers and in‐person cognitive measures.Method556 adults from the Mayo Clinic Study of Aging participated (mean age = 70.6; mean education = 16.0 years; 50.7% female; 97.5% white). Participants were predominantly cognitively unimpaired (95.3%; 4.7% had a consensus diagnosis of mild cognitive impairment). Participants completed (1) brain amyloid and tau PET scans, (2) in‐person neuropsychological assessment including Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo‐PACC) and Global‐z, and (3) remote MTD comprised of the Stricker Learning Span (SLS) and the Symbols test, which are combined into an MTD composite. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers [amyloid meta‐region of interest (ROI), tau meta‐ROI, and tau entorhinal cortex (EC)‐ROI)] and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD composite and Mayo‐PACC were associated with higher amyloid meta‐ROI (p’s<.05; Table 1). MTD composite was also negatively associated with tau meta‐ROI and EC‐ROI (p’s<.05). For memory measures, SLS sum of trials was negatively associated with tau meta‐ROI (p = .01) and EC‐ROI (p<.001) with no associations between AVLT sum of trials and PET (p’s≥.06; Table 2). Among processing speed/executive function measures, worse Trails B performance was associated with higher amyloid meta‐ROI (p<.001). Symbols and Digit Symbol Coding were not associated with PET (p’s≥.29). A multivariable model with MTD explained significantly less variance (p = .04) for amyloid meta‐ROI (adjusted R‐squared = 0.165) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.176); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionMTD is associated with continuous measures of amyloid and tau PET biomarkers of AD, demonstrating criterion validity for MTD. Several associations were comparable to relationships between gold‐standard in‐person neuropsychological tests and imaging biomarkers.