Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK.
Genome Biol. 2023 Feb 16;24(1):28. doi: 10.1186/s13059-023-02855-7.
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.
微阵列技术已被用于测量数千个人的全基因组 DNA 甲基化。这些研究通常测试个体 DNA 甲基化位点（“探针”）与复杂特征或疾病之间的关联。研究结果可用于生成甲基化谱评分（MPS），以预测独立数据集的结果。尽管 MPS 与多基因（风险）评分（PGS）之间有许多相似之处，但它们之间存在关键差异。在这里，我们回顾了基于 DNA 甲基化的特征预测的动机、方法和应用，重点关注常见疾病。我们将 MPS 与 PGS 进行对比，突出了遗传建模中做出的假设在表观遗传学数据中可能不成立的地方。
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