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Record W4393187966 · doi:10.3390/genes15040416

Association of TMEM106B with Cortical APOE Gene Expression in Neurodegenerative Conditions

2024· article· en· W4393187966 on OpenAlexafffund
Cynthia Picard, Justin Miron, Judes Poirier

Bibliographic record

VenueGenes · 2024
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health Research
KeywordsApolipoprotein EEntorhinal cortexNeuroscienceHippocampal formationBiologyGenome-wide association studyHippocampusReinnervationNeurodegenerationDiseaseGeneSingle-nucleotide polymorphismMedicineInternal medicineGeneticsGenotype

Abstract

fetched live from OpenAlex

The e4 allele of the apolipoprotein E gene is the strongest genetic risk factor for sporadic Alzheimer’s disease. Nevertheless, how APOE is regulated is still elusive. In a trans-eQTL analysis, we found a genome-wide significant association between transmembrane protein 106B (TMEM106B) genetic variants and cortical APOE mRNA levels in human brains. The goal of this study is to determine whether TMEM106B is mis-regulated in Alzheimer’s disease or in other neurodegenerative conditions. Available genomic, transcriptomic and proteomic data from human brains were downloaded from the Mayo Clinic Brain Bank and the Religious Orders Study and Memory and Aging Project. An in-house mouse model of the hippocampal deafferentation/reinnervation was achieved via a stereotaxic lesioning surgery to the entorhinal cortex, and mRNA levels were measured using RNAseq technology. In human temporal cortices, the mean TMEM106B expression was significantly higher in Alzheimer’s disease compared to cognitively unimpaired individuals. In the mouse model, hippocampal Tmem106b reached maximum levels during the early phase of reinnervation. These results suggest an active response to tissue damage that is consistent with compensatory synaptic and terminal remodeling.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.192

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 head0.024
GPT teacher head0.328
Teacher spread0.304 · 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 designBench or experimental
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
Published2024
Admission routes2
Has abstractyes

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