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Record W4401813020 · doi:10.3233/jad-240459

Effect of Genetic Risk on the Relationship Between rs-fMRI Complexity and Tau and Amyloid PET in Alzheimer’s Disease

2024· article· en· W4401813020 on OpenAlexfundno aff
Kay Jann, Steven Cen, M. Danda Vasconcelos Santos, Leon Aksman, Dilmini Wijesinghe, Ru Zhang, Kirsten M. Lynch, John M. Ringman, Danny J.J. Wang

Bibliographic record

VenueJournal of Alzheimer s Disease · 2024
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationPfizerNovartis Pharmaceuticals CorporationUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsNational Institute on AgingAlzheimer's Association
KeywordsTauopathyFunctional magnetic resonance imagingApolipoprotein ENeuroscienceImaging geneticsAmyloid (mycology)PsychologyDiseaseAlzheimer's diseaseNeuroimagingMedicineInternal medicineNeurodegenerationPathology

Abstract

fetched live from OpenAlex

Reduced functional magnetic resonance imaging (fMRI)-complexity in Alzheimer's disease (AD) progression has been demonstrated and found to be associated with tauopathy and cognition. However, association of fMRI-complexity with amyloid and influence of genetic risk (APOEɛ4) remain unknown. Here we investigate the association between fMRI-complexity, tau-PET, and amyloid-PET as well as influence of APOE genotype using multivariate generalized linear models. We show that fMRI-complexity has a strong association with tau but not amyloid deposition and that the presence of an APOEɛ4 allele enhances this effect. Thus fMRI-complexity provides a surrogate marker of impaired brain functionality in AD progression.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.092
GPT teacher head0.325
Teacher spread0.233 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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