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Record W4391753234 · doi:10.1002/alz.13650

Differential DNA methylation in the brain as potential mediator of the association between traffic‐related PM<sub>2.5</sub> and neuropathology markers of Alzheimer's disease

2024· article· en· W4391753234 on OpenAlexaff
Zhenjiang Li, Donghai Liang, Stefanie Ebelt, Marla Gearing, Michael S. Kobor, Chaini Konwar, Julie L. Maclsaac, Kristy Dever, Aliza P. Wingo, Allan I. Levey, James J. Lah, Thomas S. Wingo, Anke Hüls

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsBC Children's HospitalPacific Centre for Reproductive MedicineUniversity of British Columbia
FundersNational Institute of Environmental Health SciencesNational Institute on AgingGoizueta Business School, Emory UniversityNational Institutes of HealthEmory University
KeywordsdNaMNeuropathologyDNA methylationNeuroinflammationMediationDiseaseMedicinePrefrontal cortexGenome-wide association studyNeuroscienceBioinformaticsPsychologyInternal medicineBiologySingle-nucleotide polymorphismGeneticsCognitionGeneGenotype

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association. METHODS We assessed genome‐wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD‐related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors’ residential traffic‐related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet‐in‐the‐Middle approach, high‐dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs. RESULTS PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty‐four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation. DISCUSSION Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic‐related PM2.5 and AD. Highlights First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1‐year, 3‐year, and 5‐year traffic‐related PM2.5 exposures prior to death. Meet‐in‐the‐middle approach and high‐dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic‐related PM2.5 and Alzheimer's disease.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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

Citations28
Published2024
Admission routes1
Has abstractyes

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