@artheibault

Accounting for cellular heterogeneity is critical in epigenome-wide association studies

, and . Genome Biology (February 2014)

Abstract

Background Epigenome-wide association studies of human disease and other quantitative traits are becoming increasingly common. A series of papers reporting age-related changes in DNA methylation profiles in peripheral blood have already been published. However, blood is a heterogeneous collection of different cell types, each with a very different DNA methylation profile. Results Using a statistical method that permits estimating the relative proportion of cell types from DNA methylation profiles, we examine data from five previously published studies, and find strong evidence of cell composition change across age in blood. We also demonstrate that, in these studies, cellular composition explains much of the observed variability in DNA methylation. Furthermore, we find high levels of confounding between age-related variability and cellular composition at the CpG level. Conclusions Our findings underscore the importance of considering cell composition variability in epigenetic studies based on whole blood and other heterogeneous tissue sources. We also provide software for estimating and exploring this composition confounding for the Illumina 450k microarray.

Description

This article describes minfi, a reference-based way of correcting for cell type by estimating cell-type proportions. Kaushal et al. found minfi to be the more reliable of the reference-based methods because it could be used on the Illumina 450k array as well as the 27k array.

Links and resources

DOI:
10.1186/gb-2014-15-2-r31
URL:
BibTeX key:
jaffe2014accounting
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