A1140
Title: A joint approach to screen high dimensional mediators in epigenetic data with repeated outcomes
Authors: Yu Jiang - University of Memphis (United States) [presenting]
Lu Xie - University of Memphis (United States)
Hongmei Zhang - University of Memphis (United States)
Meredith Ray - University of Memphis (United States)
Cen Wu - Kansas State University (United States)
Abstract: There has been a growing demand for mediation analyses for high-dimensional data, specifically for high-dimensional epigenetic data, where the number of potential mediators is more than half a million. While existing statistical approaches conduct mediation analyses for single or multiple mediator models, none of these methods deals with high dimensional mediators while controlling for both Type I and Type II errors for repeated outcomes, which are often observed in longitudinal studies. There is no software or packages to perform an efficient screening. A novel screening method, screening, was developed to perform a screening process for high-dimensional mediators with a repeated outcome. Simulation studies were used to evaluate the performance of the proposed joint screening method. For both continuous and binary outcomes, the proposed joint screening method showed comparable sensitivity and specificity when the number of mediators in the model was relatively small and higher sensitivity when the number was larger compared to traditional FDR and Bonferroni methods. This proposed method was applied to real data to examine the mediation effects of DNA methylation in the association between maternal smoking and childhood asthma. It is a powerful tool for a better understanding the epigenetic effects of mediating risk factors on disease outcomes.
