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Record W4390194905 · doi:10.1002/alz.079202

The moderating effect of <i>APOE</i> E4 on the association of plasma biomarkers with markers of cognition and brain health in Alzheimer’s disease

2023· article· en· W4390194905 on OpenAlexaffabout
Erlan Sanchez, Tim Wilkinson, Gillian Coughlan, Andrée‐Ann Baril, Malcolm A. Binns, Robert Bartha, Sean Symons, Robert A. Hegele, Paula McLaughlin, Donna Kwan, Sandra E. Black, Morris Freedman, Hlin Kvartsberg, Henrik Zetterberg, Douglas P. Munoz, Mario Masellis

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsQueen's UniversityNova Scotia Health AuthoritySunnybrook Health Science CentreRobarts Clinical TrialsWestern UniversityBaycrest HospitalMcGill UniversityDouglas Mental Health University InstituteUniversity of TorontoHealth Sciences CentreSunnybrook Hospital
Fundersnot available
KeywordsApolipoprotein ENeuropsychologyInternal medicinePsychologyCognitionNeuropsychological assessmentMedicineHyperintensityAlzheimer's Disease Neuroimaging InitiativeOncologyNeurodegenerationDiseaseAlzheimer's diseaseAudiologyNeuroscienceMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract Background Due to low success rates in clinical trials for Alzheimer’s disease (AD), there is a need to apply precision medicine approaches, such as stratifying based on APOE genotype, in order to assess its effects on outcome measures. Herein, we aim to better understand how plasma biomarkers of AD and neurodegenerative pathology are associated with cognition and neurodegeneration in APOE E4 carriers compared to non‐carriers. Method Patients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) diagnosed with AD were included (n = 126, age = 71.0±8.2, 55%M). Plasma concentrations of Aβ40 and Aβ42 (Aβ42/40 ratio), glial fibrillary acidic protein (GFAP), neurofilament light (NfL) and phosphorylated‐tau181 (p‐tau181) were measured using Simoa assays. Composite cognitive domain scores (attention & working memory, executive function, language, memory, and visuospatial function) were computed from a comprehensive neuropsychological assessment. Volumes of regional grey matter, ventricular cerebrospinal fluid, white matter hyperintensities, perivascular spaces, lacunes and strokes were extracted from 3T structural MRI sequences using the SABRE pipeline. Linear regression models with an interaction term, controlling for age, sex and education were used to test the moderating effect of the APOE E4 allele on the association of plasma biomarkers with cognitive and MRI variables. When interaction effects were significant, post‐hoc models stratified by APOE E4 carrier status and controlling for age, sex and education were assessed. Result The APOE E4 allele moderated the association of GFAP, NfL and p‐tau181 with memory. Further stratification revealed that higher levels of GFAP, NfL and p‐tau181 were all associated with worse memory only in APOE E4 carriers. APOE E4 was also found to moderate the association of GFAP and p‐tau181 with many imaging markers. Further stratification revealed that higher levels of GFAP were associated with increased white matter hyperintensities, ventricular expansion and grey matter atrophy (temporal lobe, occipital lobe, hippocampus, basal ganglia and thalamus) only in APOE E4 carriers. Higher levels of p‐tau181 were also associated with increased temporal, parietal, and hippocampal atrophy only in APOE E4 carriers. Conclusion Plasma biomarkers, especially GFAP and p‐tau181, appear to be significantly more predictive of memory deficits and brain neurodegeneration in APOE E4 carriers compared to non‐carriers 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 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)0.005
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.019
GPT teacher head0.303
Teacher spread0.284 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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