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Record W4410811380 · doi:10.1038/s42003-025-08177-7

White matter dysfunction in Alzheimer’s disease is associated with disease-related transcriptomic signatures

2025· article· en· W4410811380 on OpenAlexafffund
Yilu Li, Guanyu Zhou, Jinzhong Peng, Lin Liu, Fanyu Zhang, Yasser Iturria‐Medina, Dezhong Yao, Bharat B. Biswal, Pan Wang

Bibliographic record

VenueCommunications Biology · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchAvid RadiopharmaceuticalsNational Institutes of HealthH. Lundbeck A/SServierEisaiGenentechIXICONational Natural Science Foundation of ChinaNorthern California Institute for Research and EducationPfizerNovartis Pharmaceuticals CorporationNational Center for Advancing Translational SciencesUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseMeso Scale DiagnosticsNational Institute on AgingAlzheimer's Association
KeywordsDiseaseWhite matterTranscriptomeMedicineNeurosciencePsychologyBiologyPathologyGeneticsMagnetic resonance imagingGeneGene expression

Abstract

fetched live from OpenAlex

While anatomical white matter (WM) alterations in Alzheimer's disease (AD) are well-established, functional WM dysregulation remains rarely investigated. The current study examines WM functional connectivity and network properties alterations in AD and mild cognitive impairment (MCI) and further describes their spatially correlated genes. AD and MCI shared decreased functional connectivity, clustering coefficient, and local efficiency within WM regions involved in impaired sensory-motor, visual-spatial, language, or memory functions. AD-specific dysfunction (i.e., AD vs. MCI and cognitively unimpaired participants) was predominantly located in WM, including anterior and posterior limb of internal capsule, corona radiata, and left tapetum. This WM dysfunction spatially correlates with specific genes, which are enriched in multiple biological processes related to synaptic function and development, and are mostly active in neurons and astrocytes. These findings may contribute to understanding molecular, cellular, and functional signatures associated with WM damage in AD.

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)0.000
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 score0.295
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.326
Teacher spread0.295 · 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

Citations8
Published2025
Admission routes2
Has abstractyes

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