Evidence map›Paper›PMID 31138013›Full record

ArticleEpigenetics2019

Human epigenetic ageing is logarithmic with time across the entire lifespan.

Sagi Snir, Colin Farrell, Matteo Pellegrini

Open access · greenAbstract read
In one paragraph

Article in Epigenetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Pooled it
  2. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
    Review
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  10. GABAAnnals of medicine · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Sagi Snira Department of Evolutionary Biology, University of Haifa , Haifa , Israel.
Colin Farrellb Department of Molecular, Cell and Developmental Biology, University of California , Los Angeles , CA , USA.
Matteo Pellegrinib Department of Molecular, Cell and Developmental Biology, University of California , Los Angeles , CA , USA.
University of California, Los Angeles · USUniversity of Haifa · IL

Funding

Biomedical Big Data Training GrantT32LM012424 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PELLEGRINI, MATTEO · 2016 to 2019
$1.0M
NLM NIH HHS T32 LM012424
6 · The paper itself

Abstract

Epigenetic changes during ageing have been characterized by multiple epigenetic clocks that allow the prediction of chronological age based on methylation status. Despite their accuracy and utility, epigenetic age biomarkers leave many questions about epigenetic ageing unanswered. Specifically, they do not permit the unbiased characterization of non-linear epigenetic ageing trends across entire life spans, a critical question underlying this field of research. Here we provide an integrated framework to address this question. Our model, inspired from evolutionary models, is able to account for acceleration/deceleration in epigenetic changes by fitting an individual's model age, the epigenetic age, which is related to chronological age in a non-linear fashion. Application of this model to DNA methylation data measured across broad age ranges, from before birth to old age, and from two tissue types, suggests a universal logarithmic trend characterizes epigenetic ageing across entire lifespans.

Indexed as

DNA MethylationAdultAgedAged, 80 and overAgingCpG IslandsEpigenesis, GeneticEpigenomicsGenome-Wide Association StudyHumansLongevityMiddle AgedModels, GeneticYoung AdultAgingDNA methylation

Identifiers

PMID31138013
PMCPMC6691990
OpenAlexW2952093052

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.