Evidence map›Paper›PMID 35681206›Full record

ArticleClinical epigenetics2022

Evaluation of short-term epigenetic age fluctuation.

Shohei Komaki, Hideki Ohmomo, Tsuyoshi Hachiya, Yoichi Sutoh, Kanako Ono, Ryohei Furukawa, So Umekage, Yayoi Otsuka-Yamasaki, Shiori Minabe, Akira Takashima and 3 more

Abstract read
In one paragraph

Article in Clinical epigenetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Pregnancy is linked to faster epigenetic aging in young women.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  9. Review
  10. Article
  11. Article
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

13 authors.

Shohei KomakiDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Hideki OhmomoDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Tsuyoshi HachiyaDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Yoichi SutohDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Kanako OnoDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Ryohei FurukawaDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
So UmekageDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Yayoi Otsuka-YamasakiDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Shiori MinabeDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Akira TakashimaDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan.
Kozo TannoDivision of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan.
Makoto SasakiIwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan.
Atsushi ShimizuDivision of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1, Idaidori, Yahaba, Iwate, 028-3694, Japan. ashimizu@iwate-med.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considerable effort has been spent on lowering and maintaining the epigenetic age. However, the extent to which epigenetic age fluctuates under normal conditions is poorly understood. Therefore, we analyzed methylation data from monocytes and peripheral blood mononuclear cells collected from two Japanese men. The ranges of the Pan-tissue, Skin and blood, and DNAm PhenoAge epigenetic age during 3 months were ≥ 5.62, ≥ 3.04, and ≥ 8.23 years, and the maximum daily changes were 5.21, 3.20, and 6.53 years, respectively. These fluctuations were not suppressed by correcting for cell-type composition. Although the underlying biological mechanism remains unclear, there was a nonnegligible degree of age fluctuation which should inform personalized clinical applications.

Indexed as

DNA MethylationEpigenesis, GeneticAgingEpigenomicsHumansInfantLeukocytes, MononuclearMaleMonocytesBlood DNA methylationEpigenetic clockHealthy individualsNormal condition

Identifiers

PMID35681206
PMCPMC9185970

What OpenQuestion holds

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LicenceCC BY
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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.