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Record W4210718205 · doi:10.1002/alz.055058

The association of <i>APOE</i> ‐ε4 with clinicopathological, cognitive, neuropsychiatric, and neuroimaging features in α‐synucleinopathies

2021· article· en· W4210718205 on OpenAlexaff
Usman Saeed, M. Banihashemi, Sandra E. Black, Mario Masellis

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsDementia with Lewy bodiesCerebral amyloid angiopathyDementiaApolipoprotein ELewy bodySynucleinopathiesAtrophyMedicinePathologyCognitive declineNeuroimagingPsychologyParkinson's diseaseNeuroscienceDiseaseAlpha-synuclein

Abstract

fetched live from OpenAlex

Background The ε4-allele of apolipoprotein E (APOE-ε4) presents an elevated risk not only for Alzheimer’s disease (AD), but also for Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB). Indeed, the independent influence of APOE-ε4 on the promotion and exacerbation of α-synuclein pathology has recently been suggested. However, the precise phenotypic associations of APOE-ε4 in α-synucleinopathies are variable. The primary objective of this first, comprehensive systematic review was to identify biomarkers, phenotypes, or other clinicopathological characteristics that reliably associate with APOE-ε4 in α-synucleinopathies [Parkinson’s disease (PD), DLB, PDD, and multiple system atrophy (MSA)], which may in turn uncover important pathophysiological mechanisms. Method Electronic databases were systematically searched from January 1st, 1995 through December 31st, 2020, as per the PRISMA guidelines. Studies evaluating the association of APOE-ε4 with clinicopathological, cognitive, neuropsychiatric, and neuroimaging phenotypes in clinically and/or pathologically diagnosed cases of PD, PDD, DLB, and MSA cases were reviewed. Result A total of 136 studies were eligible for inclusion (Figure). APOE-ε4 was found to be consistently associated with: 1) lower cerebrospinal fluid levels of amyloid-β 1-42 in PDD and DLB, 2) cognitive deficits in the memory domain in PD, PDD, and DLB, 3) mediotemporal cortical atrophy primarily in DLB, 3) cerebral amyloid angiopathy, shorter survival, and accelerated decline in global cognition in DLB, as well as 4) the co-occurrence of AD-type neuropathological features. Furthermore, APOE-ε4 was associated, albeit inconsistently, with: 1) the presence and severity of diffuse neocortical Lewy body pathology and, 2) elevated tracer retention on amyloid positron emission tomography in PD, PDD, and DLB, 3) greater odds of dementia in PD, and 4) other genetic and pathophysiological factors to enhance the cumulative risk for DLB. APOE-ε4 was not associated with disease risk or α-synuclein pathology in MSA. Studies also highlighted the relationship of APOE-ε4 with neuropsychiatric, epigenetic (DNA methylation), sleep, immunohistochemical, and biochemical factors in α-synucleinopathies, which will be presented. Conclusion In addition to its role in AD, APOE-ε4 influences the disease presentation and progression particularly in PDD and DLB. Guided by reliable biomarkers, further research to unravel the underlying mechanisms will assist in developing early prevention strategies targeting the APOE protein.

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)0.007
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0150.021
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.269
Teacher spread0.254 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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