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Epigenetic Regulation01:37

Epigenetic Regulation

Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
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Updated: Jul 15, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Gut microbiome signatures associate with DNA methylation-based biological aging.

Braden P Kunihiro1,2, Brennan Y Yamamoto1, Ruben Juarez3,4

  • 1Department of Anatomy, Biochemistry and Physiology, John A. Burns School of Medicine, Honolulu, HI, USA.

Scientific Reports
|July 13, 2026
PubMed
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Gut microbial composition is linked to biological aging pace, independent of chronological age. Specific bacteria like Bifidobacterium adolescentis may slow aging, while Succinivibrio dextrinosolvens may accelerate it.

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Area of Science:

  • Microbiology
  • Genetics
  • Computational Biology

Background:

  • The gut microbiome's role in aging is increasingly recognized, but its connection to epigenetic aging pace is not well understood.
  • Machine learning offers novel approaches to analyze complex biological data in aging research.

Purpose of the Study:

  • To investigate the association between gut microbial composition and biological aging pace, independent of chronological age.
  • To develop predictive models for epigenetic age acceleration using gut microbiome data.

Main Methods:

  • Utilized 16S rRNA gene sequencing and DNA methylation data from 123 monocyte-enriched samples.
  • Developed "EpiBiome" models to predict epigenetic age acceleration residuals and DunedinPACE.
  • Employed SHAP analysis to identify key microbial taxa associated with aging pace.

Main Results:

  • EpiBiome-Accel models significantly predicted DunedinPACE at both species (R²=0.152) and genus (R²=0.099) levels.
  • Model performance was not improved by adding chronological age, indicating age-independence.
  • Bifidobacterium adolescentis was identified as a key predictor of decelerated aging, while Succinivibrio dextrinosolvens was associated with accelerated aging.

Conclusions:

  • Specific gut microbial taxa are associated with the pace of biological aging.
  • Findings suggest potential microbial targets for future mechanistic studies on aging.
  • Gut microbiome composition may serve as a biomarker for biological aging pace, distinct from chronological age.