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Record W4407577249 · doi:10.1093/braincomms/fcaf068

Neuronal and glial dysfunction, white matter hyperintensities and cognition in ageing and Alzheimer’s disease

2024· article· en· W4407577249 on OpenAlexfundno aff
Ann J. Lee, Erica Howard, Nicole Saltiel, Jasmeet P. Hayes, Scott M. Hayes

Bibliographic record

VenueBrain Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersJanssen Alzheimer Immunotherapy Research And DevelopmentNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchGenentechNational Institutes of HealthTakeda Pharmaceutical CompanyIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationEisai CanadaDoD Alzheimer's Disease Neuroimaging InitiativePfizerBiogenBioClinicaAbbVie CanadaUniversity of Southern CaliforniaNovartis Pharmaceuticals CorporationU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbF. Hoffmann-La RocheAlzheimer's Drug Discovery FoundationMerckFujirebio EuropeBristol-Myers Squibb CanadaAlzheimer's AssociationFoundation for the National Institutes of HealthGE HealthcareAlzheimer's Disease Neuroimaging InitiativeMeso Scale Diagnostics
KeywordsHyperintensityNeuroscienceWhite matterCognitionDiseaseAlzheimer's diseaseBrain agingMedicinePsychologyPathologyMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract This cross-sectional study examined associations between multiple fluid biomarkers of neuronal and glial dysfunction (plasma neurofilament light chain, CSF growth-associated protein 43 and CSF soluble triggering receptor expressed on myeloid cells 2), total white matter hyperintensity volume and episodic memory and executive function performance in the context of Alzheimer’s disease biomarker status. A total of 563 participants (mean age = 71.9 years, standard deviation = 7.2) from the Alzheimer’s Disease Neuroimaging Initiative were classified by the amyloid-β/tau/neurodegeneration framework into no Alzheimer’s disease pathology (n = 176), suspected non-Alzheimer’s disease pathophysiology (n = 87) or Alzheimer’s disease continuum (n = 300) groups. Participants completed baseline neuropsychological assessment, plasma/CSF biomarker collection and MRI. Analyses explored the relative contributions of biomarkers to episodic memory and executive function performance and whether relationships varied by amyloid-β/tau/neurodegeneration group status. Across all participants, neurofilament light chain (β^= −0.14, P < 0.001) and growth-associated protein 43 (β^= −0.13, P < 0.001) were the strongest biomarkers associated with episodic memory performance, such that greater levels were associated with worse episodic memory. There was a group by growth-associated protein 43 interaction with episodic memory: greater growth-associated protein 43 was associated with lower episodic memory performance in participants classified as Alzheimer’s disease continuum relative to the no Alzheimer’s disease pathology group (β^= −0.26, P < 0.001). No robust associations between biomarkers and executive function performance or between soluble triggering receptor expressed on myeloid cells 2, white matter hyperintensity volume and cognition were observed. Biomarkers of neuro-axonal injury and synaptic dysfunction may independently contribute to episodic memory performance across participants with differing amyloid-β/tau/neurodegeneration profiles. Growth-associated protein 43 may predict worse episodic memory performance in participants with greater Alzheimer’s disease pathology. These biomarkers of neuronal dysfunction may serve as domain-specific cognitive correlates in the context of Alzheimer’s disease biomarker status.

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 score0.070
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.324
Teacher spread0.286 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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