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Record W4411122577 · doi:10.1101/2025.06.03.657357

Non-invasive measures of DNA methylation capture molecular aging in wild capuchin monkeys

2025· preprint· en· W4411122577 on OpenAlexafffund
Baptiste Sadoughi, Raquel Hernandez-Rojas, Hussam Aldin Hamou, Rafael López, Manuel W. Mah, Elizabeth Slikas, Joseph D. Orkin, James P. Higham, Katharine M. Jack, Fernando A. Campos, Noah Snyder‐Mackler, Amanda Melin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsAlberta Children's HospitalUniversité de MontréalUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsdNaMBiologyDNA methylationEpigeneticsEvolutionary biologyPopulationSenescenceZoologyGeneticsGeneMedicineGene expression

Abstract

fetched live from OpenAlex

Elucidating the socio-ecological factors that shape patterns of epigenetic modification in long-lived vertebrates is of broad interest to evolutionary biologists, geroscientists, and ecologists. However, aging research in wild populations is limited due to inability to measure cellular hallmarks of aging noninvasively. Here, we demonstrate that cellular DNA methylation (DNAm) profiles from fecal samples provide an accurate and reliable molecular clock in wild capuchin monkeys. Analysis of blood, feces, and urine samples from a closely related species shows that DNAm differentiates between species and different types of biological samples. We further find age-associated differences in DNAm relevant to cellular damage, inflammation, and senescence, consistent with hallmarks conserved across humans and other mammalian species, speaking to the comparative potential. By demonstrating that DNAm can be studied non-invasively in wild animals, our research opens new avenues in the study of modifiers of the pace of aging, and increases potential for cross-population and species comparisons.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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