Evidence map›Paper›PMID 38724732›Full record

ArticleNature aging2024

Quantifying the stochastic component of epigenetic aging.

Huige Tong, Varun B Dwaraka, Qingwen Chen, Qi Luo, Jessica A Lasky-Su, Ryan Smith, Andrew E Teschendorff

Abstract read
In one paragraph

Article in Nature aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

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

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  8. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
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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

7 authors.

Huige TongCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0009-0001-1787-1828
Varun B DwarakaTruDiagnostics, Lexington, KY, USA.
Qingwen ChenChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-2946-4947
Qi LuoCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Jessica A Lasky-SuChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0001-6236-4705
Ryan SmithTruDiagnostics, Lexington, KY, USA.
Andrew E TeschendorffCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. andrew@sinh.ac.cn.ORCID http://orcid.org/0000-0001-7410-6527

Funding

Integrative Metabolomics of Asthma SeverityR01HL123915 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LASKY-SU, JESSICA A · 2014 to 2023
$7.0M
Better utilization of omics data to inform precision medicine for asthma throughout the life courseR01HL169300 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI JESSICA A LASKY-SU · 2024 to 2026
$2.3M
National Natural Science Foundation of China (National Science Foundation of China) 31970632National Natural Science Foundation of China (National Science Foundation of China) 32170652National Natural Science Foundation of China (National Science Foundation of China) 32370699NHLBI NIH HHS R01 HL123915NHLBI NIH HHS R01 HL169300
6 · The paper itself

Abstract

DNA methylation clocks can accurately estimate chronological age and, to some extent, also biological age, yet the process by which age-associated DNA methylation (DNAm) changes are acquired appears to be quasi-stochastic, raising a fundamental question: how much of an epigenetic clock's predictive accuracy could be explained by a stochastic process of DNAm change? Here, using DNAm data from sorted immune cells, we build realistic simulation models, subsequently demonstrating in over 22,770 sorted and whole-blood samples from 25 independent cohorts that approximately 66-75% of the accuracy underpinning Horvath's clock could be driven by a stochastic process. This fraction increases to 90% for the more accurate Zhang's clock, but is lower (63%) for the PhenoAge clock, suggesting that biological aging is reflected by nonstochastic processes. Confirming this, we demonstrate that Horvath's age acceleration in males and PhenoAge's age acceleration in severe coronavirus disease 2019 cases and smokers are not driven by an increased rate of stochastic change but by nonstochastic processes. These results significantly deepen our understanding and interpretation of epigenetic clocks.

Indexed as

AgingCOVID-19DNA MethylationEpigenesis, GeneticStochastic ProcessesAdultAgedFemaleHumansMaleMiddle AgedSARS-CoV-2

Identifiers

PMID38724732
PMCPMC11186785

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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.