# Novel methods for longitudinal study of synergistic gene-environment interactions in complex diseases

> **NIH NIH R21** · MICHIGAN STATE UNIVERSITY · 2020 · $228,896

## Abstract

Project Summary/Abstract
The etiology of many complex human diseases/disorders is multi-factorial involving the contribution of genetics,
environmental exposures as well as complicated interactions between them. As living organisms, people are
exposed to multiple environmental risk factors, such as chemical contaminants and non-chemical stressors
(e.g., nutrients intake, hormone level and stress) on a daily basis. There is clear evidence that disease risk can
be modified by simultaneous and sequential exposure to multiple environmental factors, larger than what
would be expected from simple addition of the effects of the factors acting alone. Thus, the “single
environmental exposure” approach cannot capture the combined environmental effect and their synergistic
interactions with our genetic system. Built upon our previous methodology development on G×E interactions,
the long-term goal of the research is to understand and gain novel insights into how environmental mixtures
jointly moderate genetic influences on disease risk with longitudinal genetic data. Our objective is to develop
powerful statistical methods to understand how genes interact with multiple environmental exposures as a
whole to affect disease risk and to further dissect the dynamics of G×E effects. Specifically, we try to address:
1) Which genetic variants are sensitive to multiple environmental exposures to affect disease risk? 2) Which
mixtures of environmental exposures are responsible for the risk? and 3) What is the dynamics of the
synergistic G×E effects over time? Non- and semi-parametric methods will be developed to model and test
synergistic G×E effect with longitudinal data. We will apply the methods to a longitudinal study of G×E
interactions on eating disorder (ED) and explore the mechanism of gene by hormone interaction on woman’s
eating behavior. We will provide efficient estimation and testing procedures with asymptotic evaluations. User
friendly computational tools will be made available for public use. The success will provide important tools to
facilitate the process of disease gene identification, and advance the discovery of novel genes and
environmental risk factors to facilitate identification of drug targets and better prevention strategies to enhance
public health. In addition, novel genetic and environmental interaction findings based on the ED GWAS data
will likely provide new insights into the etiology of eating disorder in women.

## Key facts

- **NIH application ID:** 9920183
- **Project number:** 5R21HG010073-02
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** Yuehua Cui
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $228,896
- **Award type:** 5
- **Project period:** 2019-05-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9920183

## Citation

> US National Institutes of Health, RePORTER application 9920183, Novel methods for longitudinal study of synergistic gene-environment interactions in complex diseases (5R21HG010073-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9920183. Licensed CC0.

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