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Record W7119068244 · doi:10.1002/alz70856_105626

Association between white matter T1w/T2w ratio and cognitive function in FTD genetic mutation carriers

2025· article· en· W7119068244 on OpenAlexaff
Hyun-Woo Lee, Ian R. Mackenzie, Mirza Faisal Beg, Karteek Popuri, Dana Wittenberg, Winston Huang, Ging‐Yuek Robin Hsiung

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsSimon Fraser UniversityMemorial University of NewfoundlandUniversity of British Columbia
Fundersnot available
KeywordsWhite matterCognitionFrontotemporal dementiaNeuropsychologyAssociation (psychology)DementiaEffects of sleep deprivation on cognitive performanceMyelinMutation

Abstract

fetched live from OpenAlex

Abstract Background Frontotemporal dementia (FTD) presents with heterogeneous, progressive deficits in behavior, language, and cognition. These changes have been associated with white matter (WM) alterations on MRI, including white matter signal abnormalities and diffusion‐based metrics. Recent pathological findings suggest that white matter changes in FTD, particularly in individuals with mutations in the progranulin gene ( GRN ), may be partly attributable to myelin deficits. The ratio of T1‐weighed and T2‐weighted images on MRI (T1w/T2w) has been demonstrated as an indicator of myelin content in the brain. We hypothesized that GRN mutation carriers would exhibit a reduced T1w/T2w ratio compared to those with mutations in the chromosome 9 open reading frame 72 (C9orf7 2) or noncarriers. Additionally, we hypothesized a correlation between the T1w/T2w ratio and FTD‐related cognitive functions. Method GRN , C9orf72 , and noncarrier family controls ( N = 80) were recruited through the University of British Columbia Familial FTD Study. Neuropsychological domains, including attention, language, visuospatial skills, working memory, verbal memory, and non‐verbal memory, were examined using neuropsychological test batteries. All cognitive domain scores were transformed into z‐scores. For each participant, T1w and T2w MRI were acquired using a 1.5T scanner. T1w and T2w images were spatially coregistered, followed by intensity standardization. Average T1w/T2w was calculated within the WM region‐of‐interest defined by the JHU WM Tractography Atlas. This was a cross‐sectional analysis using baseline images. General linear models were used to: 1) Conduct a group comparison between genetic variants; and 2) Find an association between T1w/T2w and the neuropsychological domains. Both models were adjusted for age, sex, white matter signal abnormalities, and symptomatic status. Result T1w/T2w was significantly lower in GRN carriers, especially in the frontal lobar WM. There was no significant difference between C9orf72 and noncarriers. Lower T1w/T2w in the frontal lobe correlated with poorer working memory, language, and visuospatial scores. Conclusion WM changes observed in GRN carriers may be associated with deficits in the maintenance of cerebral myelin. Furthermore, the association between cognitive changes and reduced T1w/T2w levels, particularly in the frontal lobar regions, suggests that further studies are warranted to understand the role of GRN in myelin health and the manifestation of FTD‐related symptoms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.289
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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