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Epigenetic Regulation

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

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Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable

Mohammad W Hattab¹, Andrey A Shabalin¹, Shaunna L Clark¹

¹Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA.

|February 1, 2017

Summary

Surrogate variable analysis (SVA) may not fully correct cell-type heterogeneity in DNA methylation studies. A reference-based method is more reliable for controlling confounding effects and avoiding false positives.

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Area of Science:

Epigenetics
Genomics
Biostatistics

Background:

Cell-type heterogeneity is a significant confounder in DNA methylation association studies.
Surrogate variable analysis (SVA) has been proposed to address this, particularly when cell-type proportions are unknown.

Purpose of the Study:

To empirically validate the effectiveness of SVA for controlling cell-type heterogeneity in DNA methylation studies.
To compare SVA performance against a reference-based correction method using large-scale empirical data.

Main Methods:

Replication of findings from a simulation study using two large-scale empirical DNA methylation datasets.
Application and evaluation of Surrogate Variable Analysis (SVA).
Application and evaluation of a reference-based correction method.

Main Results:

In empirical data, SVA showed unstable performance and did not fully correct for cell-type effects.
SVA carried a risk of removing true biological signals, potentially leading to missed associations.
The reference-based correction method demonstrated robust performance without the limitations observed with SVA.

Conclusions:

SVA may not be a fully reliable method for controlling cell-type heterogeneity in DNA methylation studies.
Reference-based correction is a more dependable approach, despite the potential need to generate reference methylomes.
Investing in reference methylomes is recommended to prevent false-positive findings in DNA methylation research.