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Record W2002840337 · doi:10.1038/srep04954

Human leukocyte telomere length is associated with DNA methylation levels in multiple subtelomeric and imprinted loci

2014· article· en· W2002840337 on OpenAlexafffund
Jessica L. Buxton, Matthew Suderman, Jane J. Pappas, Nada Borghol, Wendy L. McArdle, Alexandra I. F. Blakemore, Clyde Hertzman, Christopher Power, Moshe Szyf, Marcus Pembrey

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersFP7 HealthBiotechnology and Biological Sciences Research CouncilNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchImperial College LondonMedical Research CouncilWellcome Trust
KeywordsCpG siteDNA methylationTelomereSubtelomereMethylationBiologyPromoterMolecular biologyGeneGeneticsDNAGene expression

Abstract

fetched live from OpenAlex

In humans, leukocyte telomere length (LTL) is positively correlated with lifespan, and shorter LTL is associated with increased risk of age-related disease. In this study we tested for association between telomere length and methylated cytosine levels. Measurements of mean telomere length and DNA methylation at >450,000 CpG sites were obtained for both blood (N = 24) and EBV-transformed cell-line (N = 36) DNA samples from men aged 44-45 years. We identified 65 gene promoters enriched for CpG sites at which methylation levels are associated with leukocyte telomere length, and 36 gene promoters enriched for CpG sites at which methylation levels are associated with telomere length in DNA from EBV-transformed cell-lines. We observed significant enrichment of positively associated methylated CpG sites in subtelomeric loci (within 4 Mb of the telomere) (P < 0.01), and also at loci in imprinted regions (P < 0.001). Our results pave the way for further investigations to help elucidate the relationships between telomere length, DNA methylation and gene expression in health and 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.568

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 head0.019
GPT teacher head0.256
Teacher spread0.236 · 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

Citations111
Published2014
Admission routes2
Has abstractyes

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