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Record W1974930628 · doi:10.1016/j.jalz.2011.09.081

P4‐336: Dissecting pathogenic ApoE pathways with the ADNI dataset: The case for reelin

2011· article· en· W1974930628 on OpenAlexaboutno aff
Christopher C. Hemond, Kwangsik Ngo, Li Shen, Shannon L. Risacher, Sungeun Kim, Andrew J. Saykin, Michael D. Greicius

Bibliographic record

VenueAlzheimer s & Dementia · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsnot available
Fundersnot available
KeywordsReelinApolipoprotein EEntorhinal cortexNeuroscienceSingle-nucleotide polymorphismHippocampusAlzheimer's diseaseWhite matterPsychologyBiologyMedicineReceptorInternal medicineDiseaseGeneticsMagnetic resonance imagingGene

Abstract

fetched live from OpenAlex

Reelin is a secreted glycoprotein that plays important roles in neuronal migration, neuroplasticity, and memory. It is highly expressed in the entorhinal cortex (EC), the epicenter for Alzheimer's disease (AD) pathology. It is believed to interact with ApoE in one or more molecular pathways. In model systems, reelin competes with ApoE for binding on two lipoprotein receptors. Activation of these receptors affects downstream kinases involved in processes critical to synaptic plasticity such as NMDA receptor expression. ApoE4 may limit reelin's effect via sequestration and impaired recycling of these receptors. To test our hypothesis that reelin interacts with ApoE in AD pathogenesis, we examined associations between reelin SNPs, presence or absence of the ApoE e4 allele, clinical status, and imaging outcomes from the ADNI dataset. Analyzing previous literature, we chose thirteen reelin SNPs associated with neuropsychiatric disease or cognitive dysfunction. These SNPs were then imputed (N = 7) or directly genotyped (N = 6) from the ADNI dataset (subject N = 752 Caucasian subjects); Structural MRI data from ADNI was used for region-of-interest analyses (cortical thickness in EC and volume in hippocampus (HC)). A whole-brain, surface-based analysis of cortical thickness was performed in SurfStat (http://www.math.mcgill.ca/keith/surfstat). The association analysis of reelin SNPs with EC thickness and HC volume was conducted in Plink v1.07 (http://pngu.mgh.harvard.edu/∼purcell/plink) on a SNP-by-SNP basis. We modeled both independent effects of reelin SNPs and interactions with ApoE e4 status and clinical status (control, AD, or MCI). Multiple comparisons were corrected by permutation for candidate gene analyses and random field theory for surface-based analyses. Reelin SNPs were not differentially prevalent across diagnostic groups in a case-control analysis. The “G” allele of SNP rs600755, located in the splice junction of exon 6, was independently associated with significant thinning of the EC across all subjects. A 3-way interaction between this SNP, ApoE status, and disease state was marginally significant (p = 0.051). Post-hoc analysis demonstrated a significant SNP by ApoE status interaction in the AD group. Finally, a whole-brain, surface-based analysis of cortical thickness showed marked medial temporal cortical thinning associated with the presence of the “G” allele.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.004

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 head0.033
GPT teacher head0.239
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations0
Published2011
Admission routes1
Has abstractyes

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