MétaCan
Menu
Back to cohort
Record W2606551040 · doi:10.1016/j.dadm.2017.04.004

Single‐nucleotide polymorphisms are associated with cognitive decline at Alzheimer's disease conversion within mild cognitive impairment patients

2017· article· en· W2606551040 on OpenAlexafffund
Eunjee Lee, Kelly S. Giovanello, Andrew J. Saykin, Fengchang Xie, Dehan Kong, Yue Wang, Liuqing Yang, Joseph G. Ibrahim, P. Murali Doraiswamy, Hongtu Zhu

Bibliographic record

VenueAlzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institute of Mental HealthNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchUniversity of California, San DiegoNational Institutes of HealthTakeda Pharmaceutical CompanyIXICOServierEisaiNorthern California Institute for Research and EducationPfizerBiogenBioClinicaMedpaceF. Hoffmann-La RocheSynarcUniversity of Southern CaliforniaGenentechCancer Prevention and Research Institute of TexasNovartis Pharmaceuticals CorporationU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbFoundation for the National Institutes of HealthGE HealthcareAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsMerckAlzheimer's AssociationNational Science Foundation
KeywordsSingle-nucleotide polymorphismCognitive impairmentCognitionCognitive declineDiseaseMedicineInternal medicineAlzheimer's diseaseDementiaOncologyGeneticsPsychiatryBiologyGenotypeGene

Abstract

fetched live from OpenAlex

INTRODUCTION: The growing public threat of Alzheimer's disease (AD) has raised the urgency to quantify the degree of cognitive decline during the conversion process of mild cognitive impairment (MCI) to AD and its underlying genetic pathway. The aim of this article was to test genetic common variants associated with accelerated cognitive decline after the conversion of MCI to AD. METHODS: In 583 subjects with MCI enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI; ADNI-1, ADNI-Go, and ADNI-2), 245 MCI participants converted to AD at follow-up. We tested the interaction effects between individual single-nucleotide polymorphisms and AD diagnosis trajectory on the longitudinal Alzheimer's Disease Assessment Scale-Cognition scores. RESULTS: , which are directly or indirectly related to MCI conversion to AD. DISCUSSION: This genome-wide association study sheds light on a genetic mechanism of longitudinal cognitive changes during the transition period from MCI to 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)0.000
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.040
GPT teacher head0.331
Teacher spread0.292 · 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

Citations48
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia Diagnosis Assessment & Disease MonitoringSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207