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Record W2741099473 · doi:10.3389/fnagi.2017.00249

DNA Methylation of Synaptic Genes in the Prefrontal Cortex Is Associated with Aging and Age-Related Cognitive Impairment

2017· article· en· W2741099473 on OpenAlexaff
Lara Ianov, Alberto Riva, Ashok Kumar, Thomas C. Foster

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsInstitute of Genetics
FundersNational Institute on Aging
KeywordsDNA methylationEpigeneticsPrefrontal cortexBiologyCpG siteMethylationGeneGeneticsNeuroscienceGene expressionCognition

Abstract

fetched live from OpenAlex

The current study investigates DNA methylation as a possible epigenetic regulator of transcription associated with aging and cognitive function. Young and aged male Fischer 344 rats were behaviorally characterized on a set shifting task, and whole genome bisulfite sequencing was employed to profile the DNA methylome of the medial prefrontal cortex (mPFC). DNA methylation was also compared to RNA expression in the mPFC from the same animals. Variability in methylation was mainly observed for CpG sites as opposed to CHG and CHH sites. Gene bodies, specifically introns, contain the highest levels of methylation. During aging, hypermethylation was observed for genes linked to synaptic function and GTPase activity. Furthermore, impaired cognitive flexibility during aging was associated with hypermethylation of genes linked to the postsynaptic density, dendrites, the axon terminus, and Ca2+ channels. Finally, comparison with RNA expression confirmed that hypermethylation was correlated with decreased expression of synaptic genes. The results indicate that DNA methylation over the lifespan contributes to synaptic modification observed in brain aging and age-related cognitive impairment.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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

Citations62
Published2017
Admission routes1
Has abstractyes

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