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Activity Number: 168 - Causal Inference
Type: Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #330423 Presentation
Title: Nonparametric Mediation Analysis for Investigating the ROle of Microbiome Health
Author(s): Kyle Carter* and Meng Lu and Lingling An
Companies: University of Arizona and University of Arizona and University of Arizona
Keywords: Metagenomics; Mediation Analysis; Integrative Analysis; High Dimensional; Information Theory

The human body maintains a close symbiotic relationship with the trillions of microorganisms that live upon and within it. Host gene expression in cooperation with the microbiome has been discovered to play a critical role in disease progression and response. In particular, changes in host gene expression may have a marked impact on the species diversity and abundance. Integration of gene expression and microbiome data can be achieved through mediation modeling. Structural equation modeling has been a popular causal framework, however it maintains strong assumptions about the distribution and association of parameters. We propose a nonparametric approach for selecting significant mediating species for models with high dimensional exposures and mediators. Simulation studies show improved performance compared to traditional mediation methods.

Authors who are presenting talks have a * after their name.

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