DNA methylation plays an important role in normal human development and disease. In epigenome-wide association studies (EWAS), a univariate test for association between a phenotype and each cytosine-phosphate-guanine (CpG) site has been widely used. Given the number of CpG sites tested in EWAS, a stringent significance cutoff is required to adjust for multiple testing; in addition, multiple nearby CpG sites may be associated with the phenotype, which is ignored by a univariate test. These two factors may contribute to the power loss of a univariate test. As an alternative, we propose applying an adaptive gene-based test that is powerful in genome-wide association studies (GWAS), called aSPUw, to EWAS for simultaneous testing on multiple CpG sites within or near a gene. We show its application to the GAW20 methylation data set.
Bibliographical noteFunding Information:
Publication of this article was supported by NIH R01 GM031575. This research was supported by (NIH) grants R01GM113250, R01HL105397, and R01HL116720 and by the Minnesota Supercomputing Institute. CW is supported by a University of Minnesota Doctoral Dissertation Fellowship.
© 2018 The Author(s).