Integration of multiview microbiome data for deciphering microbiome-metabolome-disease pathways

TL;DR

This paper introduces a novel integrative approach using structural equation modeling and external data to understand the complex microbiome-metabolome-disease pathways, validated through simulations and application to inflammatory bowel disease.

Contribution

It presents a new integrative method combining structural equation modeling with external cohort data to uncover microbiome-related disease mechanisms.

Findings

Validated the approach with simulation studies

Applied method to inflammatory bowel disease data

Demonstrated estimation consistency and asymptotic normality

Abstract

The intricate interplay between host organisms and their gut microbiota has catalyzed research into the microbiome's role in disease, shedding light on novel aspects of disease pathogenesis. However, the mechanisms through which the microbiome exerts its influence on disease remain largely unclear. In this study, we first introduce a structural equation model to delineate the pathways connecting the microbiome, metabolome, and disease processes, utilizing a target multiview microbiome data. To mitigate the challenges posed by hidden confounders, we further propose an integrative approach that incorporates data from an external microbiome cohort. This method also supports the identification of disease-specific and microbiome-associated metabolites that are missing in the target cohort. We provide theoretical underpinnings for the estimations derived from our integrative approach, demonstrating estimation consistency and asymptotic normality. The effectiveness of our methodologies is validated through comprehensive simulation studies and an empirical application to inflammatory bowel disease, highlighting their potential to unravel the complex relationships between the microbiome, metabolome, and disease.