The role of phonological and orthographic information in lexical selection

Theoretical and Experimental Linguistic

Attitudes Toward Advance Care Planning Among Persons with Dementia and their Caregivers

Objectives: To examine factors that influence decision-making, preferences, and plans related to advance care planning (ACP) and end-of-life care among persons with dementia and their caregivers, and examine how these may differ by race. Design: Cross-sectional survey. Setting: 13 geographically dispersed Alzheimer's Disease Centers across the United States. Participants: 431 racially diverse caregivers of persons with dementia. Measurements: Survey on "Care Planning for Individuals with Dementia." Results: The respondents were knowledgeable about dementia and hospice care, indicated the person with dementia would want comfort care at the end stage of illness, and reported high levels of both legal ACP (e.g., living will; 87%) and informal ACP discussions (79%) for the person with dementia. However, notable racial differences were present. Relative to white persons with dementia, African American persons with dementia were reported to have a lower preference for comfort care (81% vs. 58%) and lower rates of completion of legal ACP (89% vs. 73%). Racial differences in ACP and care preferences were also reflected in geographic differences. Additionally, African American study partners had a lower level of knowledge about dementia and reported a greater influence of religious/spiritual beliefs on the desired types of medical treatments. Notably, all respondents indicated that more information about the stages of dementia and end-of-life health care options would be helpful. Conclusions: Educational programs may be useful in reducing racial differences in attitudes towards ACP. These programs could focus on the clinical course of dementia and issues related to end-of-life care, including the importance of ACP

Alternative splicing in a presenilin 2 variant associated with Alzheimer disease

Objective: Autosomal-dominant familial Alzheimer disease (AD) is caused by by variants in presenilin 1 (PSEN1), presenilin 2 (PSEN2), and amyloid precursor protein (APP). Previously, we reported a rare PSEN2 frameshift variant in an early-onset AD case (PSEN2 p.K115Efs*11). In this study, we characterize a second family with the same variant and analyze cellular transcripts from both patient fibroblasts and brain lysates. Methods: We combined genomic, neuropathological, clinical, and molecular techniques to characterize the PSEN2 K115Efs*11 variant in two families. Results: Neuropathological and clinical evaluation confirmed the AD diagnosis in two individuals carrying the PSEN2 K115Efs*11 variant. A truncated transcript from the variant allele is detectable in patient fibroblasts while levels of wild-type PSEN2 transcript and protein are reduced compared to controls. Functional studies to assess biological consequences of the variant demonstrated that PSEN2 K115Efs*11 fibroblasts secrete less Aβ₁-₄₀ compared to controls, indicating abnormal γ-secretase activity. Analysis of PSEN2 transcript levels in brain tissue revealed alternatively spliced PSEN2 products in patient brain as well as in sporadic AD and age-matched control brain. Interpretation: These data suggest that PSEN2 K115Efs*11 is a likely pathogenic variant associated with AD. We uncovered novel PSEN2 alternative transcripts in addition to previously reported PSEN2 splice isoforms associated with sporadic AD. In the context of a frameshift, these alternative transcripts return to the canonical reading frame with potential to generate deleterious protein products. Our findings suggest novel potential mechanisms by which PSEN variants may influence AD pathogenesis, highlighting the complexity underlying genetic contribution to disease risk.Jacquelyn E. Braggin, Stephanie A. Bucks, Meredith M. Course, Carole L. Smith, Bryce Sopher, Leah Osnis, Kiel D. Shuey, Kimiko Domoto-Reilly, Christina Caso, Chizuru Kinoshita, Kathryn P. Scherpelz, Chloe Cross, Thomas Grabowski, Seyyed H.M. Nik, Morgan Newman, Gwenn A. Garden, James B. Leverenz, Debby Tsuang, Caitlin Latimer, Luis F. Gonzalez-Cuyar, Christopher Dirk Keene, Richard S. Morrison, Kristoffer Rhoads, Ellen M. Wijsman, Michael O. Dorschner, Michael Lardelli, Jessica E. Young, Paul N. Valdmanis, Thomas D. Bird, Suman Jayade

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

Age at symptom onset and death and disease duration in genetic frontotemporal dementia : an international retrospective cohort study

Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49\ub75 years (SD 10\ub70; onset) and 58\ub75 years (11\ub73; death) in the MAPT group, 58\ub72 years (9\ub78; onset) and 65\ub73 years (10\ub79; death) in the C9orf72 group, and 61\ub73 years (8\ub78; onset) and 68\ub78 years (9\ub77; death) in the GRN group. Mean disease duration was 6\ub74 years (SD 4\ub79) in the C9orf72 group, 7\ub71 years (3\ub79) in the GRN group, and 9\ub73 years (6\ub74) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0\ub745 between individual and parental age at onset, r=0\ub763 between individual and mean family age at onset, r=0\ub758 between individual and parental age at death, and r=0\ub769 between individual and mean family age at death) than in either the C9orf72 group (r=0\ub732 individual and parental age at onset, r=0\ub736 individual and mean family age at onset, r=0\ub738 individual and parental age at death, and r=0\ub740 individual and mean family age at death) or the GRN group (r=0\ub722 individual and parental age at onset, r=0\ub718 individual and mean family age at onset, r=0\ub722 individual and parental age at death, and r=0\ub732 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35\u201362, for age at onset; 61%, 47\u201373, for age at death), and even more by family membership (66%, 56\u201375, for age at onset; 74%, 65\u201382, for age at death). In the GRN group, only 2% (0\u201310) of the variability of age at onset and 9% (3\u201321) of that of age of death was explained by the specific mutation, whereas 14% (9\u201322) of the variability of age at onset and 20% (12\u201330) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11\u201326) of the variability of age at onset and 19% (12\u201329) of that of age at death. Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Data availability: The datasets analyzed for the current study reflect collaborative efforts of two research consortia: ALLFTD and GENFI. Each consortium provides clinical data access based on established policies for data use: processes for request are available for review at allftd.org/data for ALLFTD data and by emailing [email protected]. Certain data elements from both consortia (for example raw MRI images) may be restricted due to the potential for identifiability in the context of the sensitive nature of the genetic data. The deidentified combined dataset will be available for request through the FTD Prevention Initiative in 2023 (https://www.thefpi.org/).Code availability: Custom R code is available at https://doi.org/10.5281/zenodo.6687486.Copyright © The Author(s). 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.Data collection and dissemination of the data presented in this paper were supported by the ALLFTD Consortium (U19: AG063911, funded by the National Institute on Aging and the National Institute of Neurological Diseases and Stroke) and the former ARTFL and LEFFTDS Consortia (ARTFL: U54 NS092089, funded by the National Institute of Neurological Diseases and Stroke and National Center for Advancing Translational Sciences; LEFFTDS: U01 AG045390, funded by the National Institute on Aging and the National Institute of Neurological Diseases and Stroke). The manuscript was reviewed by the ALLFTD Executive Committee for scientific content. The authors acknowledge the invaluable contributions of the study participants and families as well as the assistance of the support staffs at each of the participating sites. This work is also supported by the Association for Frontotemporal Degeneration (including the FTD Biomarkers Initiative), the Bluefield Project to Cure FTD, Larry L. Hillblom Foundation (2018-A-025-FEL (A.M.S.)), the National Institutes of Health (AG038791 (A.L.B.), AG032306 (H.J.R.), AG016976 (W.K.), AG062677 (Ron C. Peterson), AG019724 (B.L.M.), AG058233 (Suzee E. Lee), AG072122 (Walter Kukull), P30 AG062422 (B.L.M.), K12 HD001459 (N.G.), K23AG061253 (A.M.S.), AG062422 (RCP), K24AG045333 (H.J.R.)) and the Rainwater Charitable Foundation. Samples from the National Centralized Repository for Alzheimer Disease and Related Dementias (NCRAD), which receives government support under a cooperative agreement grant (U24 AG021886 (T.F.)) awarded by the National Institute on Aging (NIA), were used in this study. This work was also supported by Medical Research Council UK GENFI grant MR/M023664/1 (J.D.R.), the Bluefield Project, the National Institute for Health Research including awards to Cambridge and UCL Biomedical Research Centres and a JPND GENFI-PROX grant (2019–02248). Several authors of this publication are members of the European Reference Network for Rare Neurologic Diseases, project 739510. J.D.R. and L.L.R. are also supported by the National Institute for Health and Care Research (NIHR) UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre Clinical Research Facility and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.D.R. is also supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). M.B. is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). RC and C.G. are supported by a Frontotemporal Dementia Research Studentships in Memory of David Blechner funded through The National Brain Appeal (RCN 290173). J.B.R. is supported by NIHR Cambridge Biomedical Research Centre (BRC-1215-20014; the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care), the Wellcome Trust (220258), the Cambridge Centre for Parkinson-plus and the Medical Research Council (SUAG/092 G116768); I.L.B. is supported by ANR-PRTS PREV-DemAls, PHRC PREDICT-PGRN, and several authors of this publication are members of the European Reference Network for Rare Neurological Diseases (project 739510). J.L. is funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198). R.S.-V. was funded at the Hospital Clinic de Barcelona by Instituto de Salud Carlos III, Spain (grant code PI20/00448 to RSV) and Fundació Marató TV3, Spain (grant code 20143810 to R.S.-V.). M.M. was, in part, funded by the UK Medical Research Council, the Italian Ministry of Health and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, by Canadian Institutes of Health Research operating grants (MOP- 371851 and PJT-175242) and by funding from the Weston Brain Institute. R.L. is supported by the Canadian Institutes of Health Research and the Chaire de Recherche sur les Aphasies Primaires Progressives Fondation Famille Lemaire. C.G. is supported by the Swedish Frontotemporal Dementia Initiative Schörling Foundation, Swedish Research Council, JPND Prefrontals, 2015–02926,2018–02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Karolinska Institutet Doctoral Funding, KI Strat-Neuro, Swedish Dementia Foundation, and Stockholm County Council ALF/Region Stockholm. J.L. is supported by Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (German Research Foundation, EXC 2145 Synergy 390857198). The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer’s Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the National Institute for Health Research UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre Clinical Research Facility and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK

Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia

Copyright © The Author(s) 2022. Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains for Healthy Lives initiative. B.M. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant RGPIN #017-04265) and from the Canada Research Chairs Program. S.D. receives salary support from the Fonds de Recherche du Québec—Santé (FRQS). G.S. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds de recherche du Québec—Nature et Technologies (FRQNT). V.B. acknowledges support from the Fonds de recherche du Québec—Nature et Technologies (FRQNT). FTLDNI data collection and sharing was funded by the Frontotemporal Lobar Degeneration Neuroimaging Initiative (National Institutes of Health Grant R01 AG032306) and is coordinated through the University of California, San Francisco, Memory and Aging Center. FTLDNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California

The role of phonological and orthographic information in lexical selection

We report the performance of two patients with lexico-semantic deficits following left MCA CVA. Both patients produce similar numbers of semantic paraphasias in naming tasks, but presented one crucial difference: grapheme-to-phoneme and phoneme-to-grapheme conversion procedures were available only to one of them. We investigated the impact of this availability on the process of lexical selection during word production. The patient for whom conversion procedures were not operational produced semantic errors in transcoding tasks such as reading and writing to dictation; furthermore, when asked to name a given picture in multiple output modalities—e.g., to say the name of a picture and immediately after to write it down—he produced lexically inconsistent responses. By contrast, the patient for whom conversion procedures were available did not produce semantic errors in transcoding tasks and did not produce lexically inconsistent responses in multiple picture-naming tasks. These observations are interpreted in the context of the summation hypothesis (Hillis & Caramazza, 1991), according to which the activation of lexical entries for production would be made on the basis of semantic information and, when available, on the basis of form-specific information. The implementation of this hypothesis in models of lexical access is discussed in detail