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Record W2847223726 · doi:10.1002/acn3.601

Presymptomatic white matter integrity loss in familial frontotemporal dementia in the <scp>GENFI</scp> cohort: A cross‐sectional diffusion tensor imaging study

2018· article· en· W2847223726 on OpenAlexafffund
Lize C. Jiskoot, Martina Bocchetta, Jennifer M. Nicholas, David M. Cash, David L. Thomas, Marc Modat, Sébastien Ourselin, Serge A.R.B. Rombouts, Elise G.P. Dopper, Lieke Meeter, Jessica Panman, Rick van Minkelen, Emma L. van der Ende, Laura Donker Kaat, Yolande A.L. Pijnenburg, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Caroline Graff, Fabrizio Tagliavini, Giovanni B. Frisoni, Robert Laforce, Elizabeth Finger, Alexandre de Mendonça, Sandro Sorbi, Janne M. Papma, John C. van Swieten, Jonathan D. Rohrer

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversité LavalOccupational Cancer Research CentreUniversity of TorontoWestern UniversitySunnybrook Health Science Centre
FundersMedical Research CouncilStichting DioraphteMinistero della SaluteErasmus Medisch CentrumAlzheimer’s Research UKBrain Research TrustWolfson FoundationNational Institute for Health and Care ResearchAlzheimer NederlandEU Joint Programme – Neurodegenerative Disease ResearchZonMwNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome TrustCanadian Institutes of Health ResearchWellcome
KeywordsC9orf72SpleniumCorpus callosumMedicineWhite matterDiffusion MRIInternal capsuleUncinate fasciculusFractional anisotropyFrontotemporal dementiaPathologyDementiaRadiologyMagnetic resonance imagingDisease

Abstract

fetched live from OpenAlex

Abstract Objective We aimed to investigate mutation‐specific white matter ( WM ) integrity changes in presymptomatic and symptomatic mutation carriers of the C9orf72 , MAPT , and GRN mutations by use of diffusion‐weighted imaging within the Genetic Frontotemporal dementia Initiative ( GENFI ) study. Methods One hundred and forty mutation carriers (54 C9orf72 , 30 MAPT , 56 GRN ), 104 presymptomatic and 36 symptomatic, and 115 noncarriers underwent 3T diffusion tensor imaging. Linear mixed effects models were used to examine the association between diffusion parameters and years from estimated symptom onset in C9orf72 , MAPT , and GRN mutation carriers versus noncarriers. Post hoc analyses were performed on presymptomatic mutation carriers only, as well as left–right asymmetry analyses on GRN mutation carriers versus noncarriers. Results Diffusion changes in C9orf72 mutation carriers are present significantly earlier than both MAPT and GRN mutation carriers – characteristically in the posterior thalamic radiation and more posteriorly located tracts (e.g., splenium of the corpus callosum, posterior corona radiata), as early as 30 years before estimated symptom onset. MAPT mutation carriers showed early involvement of the uncinate fasciculus and cingulum, sparing the internal capsule, whereas involvement of the anterior and posterior internal capsule was found in GRN . Restricting analyses to presymptomatic mutation carriers only, similar – albeit less extensive – patterns were found: posteriorly located WM tracts (e.g., posterior thalamic radiation, splenium of the corpus callosum, posterior corona radiata) in presymptomatic C9orf72 , the uncinate fasciculus in presymptomatic MAPT , and the internal capsule (anterior and posterior limbs) in presymptomatic GRN mutation carriers. In GRN , most tracts showed significant left–right differences in one or more diffusion parameter, with the most consistent results being found in the UF , EC , RPIC , and ALIC . Interpretation This study demonstrates the presence of early and widespread WM integrity loss in presymptomatic FTD , and suggests a clear genotypic “fingerprint.” Our findings corroborate the notion of FTD as a network‐based disease, where changes in connectivity are some of the earliest detectable features, and identify diffusion tensor imaging as a potential neuroimaging biomarker for disease‐tracking and ‐staging in presymptomatic to early‐stage familial FTD .

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 score0.010
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.138
GPT teacher head0.454
Teacher spread0.316 · 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".

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Citations58
Published2018
Admission routes2
Has abstractyes

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