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Abstract:
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With development of genetic and genomic technologies, it is of increasing interest in biomedical studies to explore the genetic and epigenetic mechanisms that mediate a disease causing process. Epigenetic studies for complex diseases have shown that the effect of many risk factors are likely to be mediated in a collaborative fashion through multiple probes in a genomic region, such as CpG islands or shores. We propose a Wald-type test for the overall natural indirect effect targeting the multiple mediator problem. Kernel machine based approach is employed to account for potential interactions and nonlinearity among mediators. Under certain regularity conditions, we develop a simple variance estimator when comparing coefficients from different models. The proposed test is evaluated on data simulated from various underlying mediation pathway structures and demonstrates substantial gain in power when the effects are nonlinear. We also apply the proposed test on the Normal Aging Study to investigate the effect of smoking on lung function measures that mediated by the DNA methylation level on regions over the whole genome.
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