Evidence map›Paper›PMID 33911141›Full record

ArticleScientific reports2021

Disentangling age-dependent DNA methylation: deterministic, stochastic, and nonlinear.

O Vershinina, M G Bacalini, A Zaikin, C Franceschi, M Ivanchenko

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
    Review
  4. Article
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  10. Quiescence Multiverse.Biomolecules · 2025
    Review
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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

5 authors.

O VershininaDepartment of Applied Mathematics, Mathematics of Future Technologies Center, Laboratory of Systems Medicine of Healthy Aging, Lobachevsky University, Nizhny Novgorod, Russia, 603950. olya.vershinina@itmm.unn.ru.
M G BacaliniUniversity of Bologna and IRCCS Istituto delle Scienze Neurologiche di Bologna (ISNB), 40139, Bologna, Italy.
A ZaikinDepartment of Applied Mathematics, Mathematics of Future Technologies Center, Laboratory of Systems Medicine of Healthy Aging, Lobachevsky University, Nizhny Novgorod, Russia, 603950.
C FranceschiDepartment of Applied Mathematics, Mathematics of Future Technologies Center, Laboratory of Systems Medicine of Healthy Aging, Lobachevsky University, Nizhny Novgorod, Russia, 603950.
M IvanchenkoDepartment of Applied Mathematics, Mathematics of Future Technologies Center, Laboratory of Systems Medicine of Healthy Aging, Lobachevsky University, Nizhny Novgorod, Russia, 603950.

Funding

Medical Research Council MR/R02524X/1
6 · The paper itself

Abstract

DNA methylation variability arises due to concurrent genetic and environmental influences. Each of them is a mixture of regular and noisy sources, whose relative contribution has not been satisfactorily understood yet. We conduct a systematic assessment of the age-dependent methylation by the signal-to-noise ratio and identify a wealth of "deterministic" CpG probes (about 90%), whose methylation variability likely originates due to genetic and general environmental factors. The remaining 10% of "stochastic" CpG probes are arguably governed by the biological noise or incidental environmental factors. Investigating the mathematical functional relationship between methylation levels and variability, we find that in about 90% of the age-associated differentially methylated positions, the variability changes as the square of the methylation level, whereas in the most of the remaining cases the dependence is linear. Furthermore, we demonstrate that the methylation level itself in more than 15% cases varies nonlinearly with age (according to the power law), in contrast to the previously assumed linear changes. Our findings present ample evidence of the ubiquity of strong DNA methylation regulation, resulting in the individual age-dependent and nonlinear methylation trajectories, whose divergence explains the cross-sectional variability. It may also serve a basis for constructing novel nonlinear epigenetic clocks.

Indexed as

CpG IslandsDNA MethylationEpigenesis, GeneticAdolescentAdultAgedAged, 80 and overAgingCross-Sectional StudiesFemaleHumansMaleMiddle AgedStochastic ProcessesYoung Adult

Identifiers

PMID33911141
PMCPMC8080842

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Registered trials

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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.