# Exogenous and Genetic Determinants of the Internal Environment

> **NIH NIH P01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $242,938

## Abstract

ABSTRACT 
The remarkable yield of novel genetic associations over the last decade resulting from the agnostic approach 
of genome-wide association studies (GWAS) had not been matched by comparable advances on the 
environmental side. The "exposome" concept introduced by Chris Wild in 2005 as a "comprehensive 
description of lifelong exposure history" of external exposures (e.g., chemical, physical, and biological agents), 
general external environment (e.g., climate, urban-rural, socioeconomic position), and internal exposures (e.g., 
metabolites, gut microflora) has been operationalized in terms of the measurement of internal chemicals at 
particular points in time, typically using mass spectrometry to characterize the "metabolome." With this 
machinery Environment-Wide Association Studies (EWAS) are now feasible, but there remain numerous 
methodological challenges before the EWAS concept can be considered a real companion to GWASs, 
including the dynamic nature of the external and internal environment, the problem of reverse causation, 
control of non-genetic host and environmental confounders, measurement error (temporal variability, 
instrument error, identification of unknown chemicals, etc.), and ways of conducting Gene-Environment-Wide 
Interaction Studies (GEWIS). An important component of the exposome is the microbiome. Evidence is 
mounting linking tumor promotion in a broad array of cancer types to the effects of bacterial microbiota. Local 
environmental conditions, affected by diet, antibiotics, pre- and probiotics, etc., could affect the structure of 
microbial communities, affecting risk of disease and response to therapy. The advent of high-throughput 
sequencing has allowed the relatively inexpensive identification and quantification of thousands of operational 
taxonomic units (OTUs) in a single biospecimen, providing a wealth of information on the complex structure of 
resident microbial communities. The microbiome raises many of the same methodological challenges as the 
exposome, such as time dependency, reverse causation, and non-genetic confounding, but also some different 
ones like ways of characterizing community effects like diversity and resilience. Although GxE and GxG are 
also relevant, equally interesting are host-microbial interactions and exposome-microbiome interactions. We 
propose an integrated approach to developing statistical methods for studying the determinants of the internal 
environment (the metabolome and the microbiome jointly) in relation to the external environment and the host 
genome and the relationship of the internal environment to disease risk. As part of this we propose to develop 
Bayesian network methods to relate all these variables and investigate mediation. We will apply our methods 
to data from, e.g., the Multi-Ethnic Cohort, the ColoCare Consortium, and a study of colorectal polyps in twins.

## Key facts

- **NIH application ID:** 9991775
- **Project number:** 5P01CA196569-05
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Duncan C. Thomas
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $242,938
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9991775

## Citation

> US National Institutes of Health, RePORTER application 9991775, Exogenous and Genetic Determinants of the Internal Environment (5P01CA196569-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9991775. Licensed CC0.

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