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Differences in the epigenome can be used to study genetic variation and disease risk in populations.
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New, Robust Approach for Understanding Population Epigenetic Variation

CoRSIVs help precisely link genetic traits to disease risk in populations

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Swathi Kodaikal, MSc
Photo portrait of swathi kodaikal

Swathi Kodaikal, MSc, holds a master’s degree in biotechnology and has worked in places where actual science and research happen. Blending her love for writing with science, Swathi enjoys demystifying complex research findings for readers from all walks of life. On the days she doesn’t write, she learns and performs Kathak, sings, makes plans to travel, and obsesses over cleanliness.

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Published:Jan 26, 2023
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Researchers at Baylor College of Medicine may have discovered a new way to accurately investigate epigenetic causes of disease. “Epigenetic differences between people can affect their risk of disease,” said Robert A. Waterland, PhD, professor of pediatrics-nutrition at Baylor’s USDA/ARS Children’s Nutrition Research Center and the co-corresponding author of a recent paper in Genome Biology. This study describes a powerful approach to studying epigenetics using previously unreported regions of interindividual variation.

The epigenome is a system of molecular modifications involving DNA methylation that turns different genes on and off, according to cell type. To understand genetic differences in populations, epigeneticists probe patterns of DNA methylation that occur at specific locations called CpG sites.

What is a QTL? What is mQTL used for?
Quantitative trait locus (QTL) is a region of DNA associated with a specific trait (like hair color, height, or eye color) that varies within a population. mQTL is a methylated QTL. QTLs are used in a statistical method that links phenotypic data (trait measurements) and genotypic data (usually molecular markers) to explain the genetic basis of variation in complex traits.

Analyzing methylation quantitative trait loci (mQTL) statistically explains how methylation at specific CpG sites may be correlated to genetic variants (or a disease).

In this study, Waterland and his team analyzed DNA methylation at 10,000 new regions, called correlated regions of systemic interindividual variation, or CoRSIVs, in samples from multiple tissues of nearly 200 individuals. Like CpG sites, CoRSIVs are regions where DNA methylation differs substantially among people but is consistent across the different tissues of each person.

“Compared to the most powerful previous study including 33,000 people, our much smaller study focused on CoRSIVs discovered 72 times more mQTL,” said Chathura J. Gunasekara, PhD, a data analyst in the Waterland lab and first author of the paper, in a recent press release. This is because 95 percent of the CpG sites on commercial methylation arrays do not target sites of interindividual methylation differences. So, studies relying on these arrays may not successfully capture population-level epigenetic variation underlying disease risk.

CoRSIVs have already been linked to conditions like thyroid function, cognition, cleft palate, schizophrenia, childhood obesity, and autism spectrum disorder. “We hope that the new tool we’ve developed will accelerate progress in understanding epigenetic causality of disease,” said Waterland.