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Related Concept Videos

Phase II Reactions: Methylation Reactions01:17

Phase II Reactions: Methylation Reactions

180
Methylation is a phase II biotransformation process involving the attachment of a methyl group to a substrate. Enzymes known as methyltransferases orchestrate this reaction.
The mechanism of methylation unfolds in two stages. The first stage sees a methyltransferase enzyme facilitating the transfer of a methyl group from S-adenosylmethionine (SAM) to the substrate, forming S-adenosylhomocysteine (SAH). The second stage involves further metabolism of SAH into homocysteine, which can be recycled...
180

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methscore: a comprehensive R function for DNA methylation-based health predictors.

Zongli Xu1, Liang Niu2, Jacob K Kresovich3

  • 1Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States.

Bioinformatics (Oxford, England)
|May 3, 2024
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Summary

This study integrates 158 DNA methylation predictors into an R function for easier use in epigenetics research. The new method improves the precision and comparability of biological age and other trait estimations across studies.

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Area of Science:

  • Epigenetics
  • Genomic Medicine
  • Computational Biology

Background:

  • DNA methylation predictors are valuable for epidemiology and personalized medicine.
  • Generating predictors from original sources is complex and time-consuming.
  • Array and batch effects hinder predictor comparability across studies.

Purpose of the Study:

  • To integrate 158 published DNA methylation predictors into a single R function.
  • To provide a method (ref-RCP) to mitigate batch and array differences.
  • To improve the precision and comparability of epigenetic predictor estimations.

Main Methods:

  • Integrated 158 published DNA methylation predictors into an R function.
  • Utilized classical and principal component-based methods for predictor generation.
  • Developed a modified RCP method (ref-RCP) for normalizing DNA methylation data.

Main Results:

  • The R function produces 158 predictors for chronological age, biological age, exposures, lifestyle, and serum proteins.
  • The ref-RCP method normalizes input DNA methylation data to reference data.
  • Evaluations demonstrated improved estimate precision and cross-study comparability.

Conclusions:

  • The integrated R function simplifies the use of DNA methylation predictors.
  • The ref-RCP method enhances the reliability of epigenetic estimations.
  • The ENmix package offers a valuable tool for epigenetics research and personalized medicine.