Methods for Large-scale Single Mediator Hypothesis Testing: Possible Choices and Comparisons

Abstract

Mediation hypothesis testing for a large number of mediators is challenging due to the composite structure of the null hypothesis, H 0 : αβ = 0 (α: effect of the exposure on the mediator after adjusting for confounders; β: effect of the mediator on the outcome after adjusting for exposure and confounders). In this paper, we reviewed three classes of methods for multiple mediation hypothesis testing. In addition to these existing methods, we developed the Sobel-comp method, which uses a corrected mixture reference distribution for Sobel's test statistic. We performed extensive simulation studies to compare all six methods in terms of the false positive rates under the null hypothesis and the true positive rates under the alternative hypothesis. We found that the class of methods which uses a mixture reference distribution could best maintain the false positive rates at the nominal level under the null hypothesis and had the greatest true positive rates under the alternative hypothesis. We applied all methods to study the mediation mechanism of DNA methylation sites in the pathway from adult socioeconomic status to glycated hemoglobin level using data from the Multi-Ethnic Study of Atherosclerosis (MESA). We also provide guidelines for choosing the optimal mediation hypothesis testing method in practice. (word count: 196)

Methods for Mediation Analysis with High-Dimensional DNA Methylation Data: Possible Choices and Comparison

“…As an example of such an analysis, our previous work 15,16 examined the association between low SES and glycated hemoglobin (HbA1c) in the Multi-Ethnic Study of Atherosclerosis (MESA), a United States population-based longitudinal study 17 . Indicators of SES, such as education level, are strong predictors of type II diabetes 18 , while HbA1c is an important risk factor of cardiovascular disease and a critical biomarker in type II diabetes diagnosis [19][20][21] .…”