44: Detecting and quantifying mediation of health outcomes by microbial communities

Music City Center 

Many studies of human microbiome epidemiology have focused on the effects of health outcomes and exposures on the microbiome or the effects of microbiome on health outcomes. However, there's increasing interest in understanding complex relationships where exposures alter microbiome composition, which thereby affects the health outcomes (i.e., "mediates" exposure effect on health). Such hypotheses can be tested by statistical mediation analysis, but typical methods are not appropriate for microbiome data due to zero-inflation, compositionality, and high-dimensionality. Using realistic simulated microbiome data, we compared the performance of (1) low-dimensional mediation methods, (2) high-dimensional, non-compositional mediation, and (3) specialized methods for microbiome under differing circumstances. We further compared these methods in two real-world datasets assessing the effect of diet on cardiometabolic disease. We make recommendations on best methods for total direct effect and total/component indirect effects. Notably, no one method performed the best in all tests, indicating the nuance in microbiome mediation analyses and the need for new methods.

human microbiome

mediation analysis

microbiome epidemiology

metagenomics 

Section on Statistics in Genomics and Genetics