title: Integrative modeling of multi-platform genomic data under the framework of mediation analysis.
abstract: Given the availability of genomic data, there have been emerging interests in integrating multi-platform data. Here, we propose to model genetics (single nucleotide polymorphism (SNP)), epigenetics (DNA methylation), and gene expression data as a biological process to delineate phenotypic traits under the framework of causal mediation modeling. We propose a regression model for the joint effect of SNPs, methylation, gene expression, and their nonlinear interactions on the outcome and develop a variance component score test for any arbitrary set of regression coefficients. The test statistic under the null follows a mixture of chi-square distributions, which can be approximated using a characteristic function inversion method or a perturbation procedure. We construct tests for candidate models determined by different combinations of SNPs, DNA methylation, gene expression, and interactions and further propose an omnibus test to accommodate different models. We then study three path-specific effects: the direct effect of SNPs on the outcome, the effect mediated through expression, and the effect through methylation. We characterize correspondences between the three path-specific effects and coefficients in the regression model, which are influenced by causal relations among SNPs, DNA methylation, and gene expression. We illustrate the utility of our method in two genomic studies and numerical simulation studies.
authors.affiliation: Department of Epidemiology, Brown University, 121 S. Main St., Box G-S121-2, Providence, RI, 02912, U.S.A.
authors.forename: Yen-Tsung
authors.initials: YT
authors.lastname: Huang
mesh_terms: D001249:Asthma / Q000235:genetics*; D003198:Computer Simulation; D019175:DNA Methylation; D057890:Epigenomics / Q000379:methods / Q000706:statistics & numerical data*; D051383:GRB10 Adaptor Protein / Q000235:genetics*; D015870:Gene Expression; D015894:Genome, Human; D055106:Genome-Wide Association Study; D005909:Glioblastoma / Q000235:genetics* / Q000401:mortality; D006801:Humans; D008565:Membrane Proteins / Q000235:genetics*; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012044:Regression Analysis; D016019:Survival Analysis
chemical_list: C096358:GRB10 protein, human; D008565:Membrane Proteins; C464399:ORMDL3 protein, human; D051383:GRB10 Adaptor Protein
keywords: SNP-set analysis; causal inference; epigenetics; genetic association studies; path-specific effect; variance component test