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Record W2789244140 · doi:10.1177/0891988718764330

Loss-of-Function PCSK9 Mutations Are Not Associated With Alzheimer Disease

2018· article· en· W2789244140 on OpenAlexafffundabout
Martine Paquette, Yascara Grisel Luna Saavedra, Judes Poirier, Louise Théroux, Doris Dea, Alexis Baass, Robert Dufour

Bibliographic record

VenueJournal of Geriatric Psychiatry and Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversité de MontréalMontreal Clinical Research Institute
FundersNational Institute on AgingCanadian Institutes of Health ResearchInstitut de Recherche Clinique De Montréal
KeywordsPCSK9MedicineDiseaseApolipoprotein EAlzheimer's diseaseGenotypeMutationRisk factorInternal medicineDementiaPopulationNeurocognitiveGeneticsLDL receptorCholesterolBiologyLipoproteinPsychiatryGeneCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Hypercholesterolemia is a major risk factor for the late-onset form of Alzheimer disease (AD). Loss-of-function (LOF) mutations of PCSK9 and PCSK9 inhibitors lower low-density lipoprotein cholesterol (LDL-C) and have been associated with a reduced risk of cardiovascular disease. The aim of this study was to examine the effect of PCSK9 LOF variants on risk and age of onset of AD. METHODS: A total of 878 participants (410 controls and 468 AD cases) from the Quebec Founder Population were included in the study. RESULTS: Fifty-four (6.2%) participants carried the R46L mutation, whereas 226 (26.2%) participants carried the InsLEU mutation. There was no protective or no deleterious effect of carrying PCSK9 LOF mutations on AD prevalence nor on age of onset, even when stratified by apolipoprotein E epsilon 4 genotype or by gender. CONCLUSION: Our data indicate that carrying PCSK9 LOF mutations has a neutral effect on neurocognitive health and the prevalence of 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 score0.017
Threshold uncertainty score0.308

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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

Citations26
Published2018
Admission routes3
Has abstractyes

Explore more

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