Generalized multi‐SNP mediation intersection–union test

Abstract

To elucidate the molecular mechanisms underlying genetic variants identified from genome-wide association studies (GWAS) for a variety of phenotypic traits encompassing binary, continuous, count, and survival outcomes, we propose a novel and flexible method to test for mediation that can simultaneously accommodate multiple genetic variants and different types of outcome variables. Specifically, we employ the intersection-union test approach combined with the likelihood ratio test to detect mediation effect of multiple genetic variants via some mediator (e.g., the expression of a neighboring gene) on outcome. We fit high-dimensional generalized linear mixed models under the mediation framework, separately under the null and alternative hypothesis. We leverage Laplace approximation to compute the marginal likelihood of outcome and use coordinate descent algorithm to estimate corresponding parameters. Our extensive simulations demonstrate the validity of our proposed methods and substantial, up to 97%, power gains over alternative methods. Applications to real data for the study of Chlamydia trachomatis infection further showcase advantages of our methods. We believe our proposed methods will be of value and general interest in this post-GWAS era to disentangle the potential causal mechanism from DNA to phenotype for new drug discovery and personalized medicine.

Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants

“…Recent singlecell technologies (Zhou et al, 2021;Yu et al, 2022) have further enhanced our capabilities to characterize cell-type-specific profiles as well as to potentially reveal cell-to-cell variability, which will additionally facilitate our interpretation and understanding of GWAS results (Yu et al, 2021;Li et al, 2022). In addition, chromatin interactome profiles in population samples will also be essential to understanding the variation across individuals, the genetics behind the variation (Gorkin et al, 2019), and the consequence of such variation for the inference of the molecular causal paths via causal inference or mediation analysis (Zhong et al, 2019(Zhong et al, , 2022. Such multi-sample chromatin conformation data have emerged at the bulk level encompassing many cells (Gorkin et al, 2019;Chandra et al, 2021).…”

MedDiC: high dimensional mediation analysis via difference in coefficients

“…It is based on intersection-union tests after screening and penalization-based estimation. Many novel methods with similar rationale have been developed for various high dimensional mediation problems, such as [43] for survival outcome, [8] for testing the significance of a group of mediators with potentially non-linear mediation effect, and [49, 48, 45] for the aggregated indirect effects of the individual mediators when the exposures are potentially high dimensional. [31, 30, 29] proposed Bayesian solutions for high dimensional mediator selection problems.…”