Brushaber, Danielle

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 < .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.

Abstract The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. ‘Hub’ proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

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.

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.

AbstractBackgroundThe DEMQOL (Dementia Quality of Life) scale is a patient reported questionnaire and proxy form that captures subjective life quality. Participants in ALLFTD and their Study Partners (SP) complete these questionnaires at each study visit.MethodWe analyzed the DEMQOL in participants and their SPs when the SP was reported to be a spouse or equivalent. Analyses focused on the final overall quality of life (QoL) rating for the participant (poor, fair, good, or very good).ResultDEMQOL responses from 907 dyads (participant: mean age 58.3±13.4 years, 44% female, and mean education 15.9±2.5 years) were analyzed. Participants rated their overall QoL as very good (45.8%), good (36.5%), fair (14%), and poor (3.5%). SPs rated their participant’s overall QoL as very good (33.6%), good (41%), fair (19.4%), and poor (6%). There was a discordance in ratings between participants and SPs (p<0.0001); in almost 50% of cases, participants rated their QoL better (33.2%) or worse (15.2%) than their SP rated their QoL. When considering disease severity (CDR®+NACC‐FTLD global score), participants rated their QoL better than their SP rated their QoL (CDR®+NACC‐FTLD = 0: 19.4%, CDR®+NACC‐FTLD = 0.5: 42%, and CDR®+NACC‐FTLD = 1+: 33.2%), worse than (CDR®+NACC‐FTLD = 0: 15.1%, CDR®+NACC‐FTLD = 0.5: 13.3%, and CDR®+NACC‐FTLD = 1+: 15.2%), or the same (CDR®+NACC‐FTLD = 0: 65.6%, CDR®+NACC‐FTLD = 0.5: 44.8%, and CDR®+NACC‐FTLD = 1+: 51.6%).ConclusionAmong participants and SPs, similarities and differences in QoL ratings are fairly consistent regardless of global CDR®+NACC‐FTLD rating. Generally, participants are equally or more optimistic about QoL than their SPs. Longitudinal analyses are forthcoming.

This cross-sectional study of US medical students assesses the association of COVID-19 intensity in the clinical learning environment with student burnout and perceptions regarding residency preparedness.