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Updated: May 13, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
Published on: October 8, 2017
The fate is not always written in the genes: epigenomics in epidemiologic studies
Scott M Langevin1, Karl T Kelsey
1Department of Epidemiology, Brown University, Providence, Rhode Island, USA.
Abstract:
Cost-effective, high-throughput epigenomic technologies have begun to emerge, rapidly replacing the candidate gene approach to molecular epidemiology and offering a comprehensive strategy for the study of epigenetics in human subjects. Epigenome-wide association studies (EWAS) provide new opportunities for advancing our understanding of epigenetic changes associated with complex disease states. However, such analyses are complicated by the dynamic nature of DNA methylation. In contrast to genomic studies, where genotype is essentially constant across somatic cells, EWAS present a new set of challenges, largely due to differential DNA methylation across distinct cell types, particularly for studies involving heterogeneous tissue sources, and changes in the epigenetic profile that occur over time. This review describes potential applications of EWAS from the viewpoint of the molecular epidemiologist, along with special considerations and pitfalls involved in the design of such studies.
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