A distance-based approach for testing the mediation effect of the human microbiome

Document Type

Article

Publication Date

6-1-2018

Abstract

Motivation Recent studies have revealed a complex interplay between environment, the human microbiome and health and disease. Mediation analysis of the human microbiome in these complex relationships could potentially provide insights into the role of the microbiome in the etiology of disease and, more importantly, lead to novel clinical interventions by modulating the microbiome. However, due to the high dimensionality, sparsity, non-normality and phylogenetic structure of microbiome data, none of the existing methods are suitable for testing such clinically important mediation effect. Results We propose a distance-based approach for testing the mediation effect of the human microbiome. In the framework, the nonlinear relationship between the human microbiome and independent/dependent variables is captured implicitly through the use of sample-wise ecological distances, and the phylogenetic tree information is conveniently incorporated by using phylogeny-based distance metrics. Multiple distance metrics are utilized to maximize the power to detect various types of mediation effect. Simulation studies demonstrate that our method has correct Type I error control, and is robust and powerful under various mediation models. Application to a real gut microbiome dataset revealed that the association between the dietary fiber intake and body mass index was mediated by the gut microbiome.

Identifier

85048035370 (Scopus)

Publication Title

Bioinformatics

External Full Text Location

https://doi.org/10.1093/bioinformatics/bty014

e-ISSN

14602059

ISSN

13674803

PubMed ID

29346509

First Page

1875

Last Page

1883

Issue

11

Volume

34

Fund Ref

Mayo Clinic

This document is currently not available here.

Share

COinS