Journal
GENOME BIOLOGY
Volume 24, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13059-023-02855-7
Keywords
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Microarray technology is employed to analyze genome-wide DNA methylation and its association with complex traits or diseases. Results can be used to predict outcomes using methylation profile scores (MPS) in independent datasets. However, there are key differences between MPS and polygenic (risk) scores (PGS), especially in terms of assumptions made in genetic modeling that may not apply to epigenetic data.
Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites ( probes ) and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.
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