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Record W4323811581 · doi:10.1002/hbm.26220

Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia

2023· article· en· W4323811581 on OpenAlexafffund
Aurélie Bussy, Jake Levy, Tristin Best, Raihaan Patel, Lani Cupo, Tim Van Langenhove, Jørgen E. Nielsen, Yolande A.L. Pijnenburg, Maria Landqvist Waldö, Anne M. Remes, Matthias L. Schroeter, Isabel Santana, Florence Pasquier, Markus Otto, Adrian Danek, Johannes Levin, Isabelle Le Ber, Rik Vandenberghe, Matthis Synofzik, Fermín Moreno, Alexandre de Mendonça, Raquel Sánchez‐Valle, Robert Laforce, Tobias Langheinrich, Alexander Gerhard, Caroline Graff, Christopher Butler, Sandro Sorbi, Lize C. Jiskoot, Harro Seelaar, John C. van Swieten, Elizabeth Finger, Maria Carmela Tartaglia, Mario Masellis, Pietro Tiraboschi, Daniela Galimberti, Barbara Borroni, James B. Rowe, Martina Bocchetta, Jonathan D. Rohrer, Gabriel A. Devenyi, M. Mallar Chakravarty, Simon Ducharme

Bibliographic record

VenueHuman Brain Mapping · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreOccupational Cancer Research CentreWestern UniversityUniversité LavalUniversity of TorontoMontreal Neurological Institute and HospitalMcGill UniversityDouglas Mental Health University Institute
FundersNIHR Cambridge Biomedical Research CentreMedical Research CouncilFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaAlzheimer's SocietyAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftUK Dementia Research InstituteMinistero della SaluteDepartment of Health and Social CareEU Joint Programme – Neurodegenerative Disease ResearchAlzheimer SocietyNational Institute for Health and Care ResearchNovo Nordisk FondenCanadian Institutes of Health ResearchWeston Brain Institute
KeywordsFrontotemporal dementiaAtrophyNeuroscienceDementiaPsychologyPsychiatryMedicinePathologyDisease

Abstract

fetched live from OpenAlex

Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.314
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2023
Admission routes2
Has abstractyes

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