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Gene-Environment Interactions

Gene-Environment Interactions

Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...

Background and Environment Affect Phenotype

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...

Behavioral Genetics and Its Designs

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

Polygenic Traits

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...

Polygenic Traits

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Related Experiment Video

Updated: Jun 22, 2026

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Published on: January 7, 2014

Using cases and parents to study multiplicative gene-by-environment interaction.

Emily O Kistner¹, Min Shi, Clarice R Weinberg

¹Department of Health Studies, Division of Biological Sciences, The University of Chicago, Chicago, IL 60637, USA. ekistner@uchicago.edu

American Journal of Epidemiology

|June 2, 2009

Summary

This study introduces a new method using case-parent triads to analyze gene-by-environment interactions, crucial for understanding complex diseases. It allows for more accurate risk assessment by considering both genetic and environmental factors.

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Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

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Area of Science:

Genetics
Epidemiology
Biostatistics

Background:

Case-parent triads are valuable for estimating genotype relative risks, mitigating biases from population structure and self-selection.
Complex diseases often involve interactions between genetic susceptibility and environmental cofactors.
Existing methods for gene-environment interaction often require stringent assumptions like gene-environment independence.

Purpose of the Study:

To adapt a polytomous logistic regression method for analyzing multiplicative gene-by-environment interaction using case-parent data.
To enable estimation of interaction parameters under less restrictive assumptions.
To illustrate the method's application in a real-world scenario involving genetic polymorphisms, maternal smoking, and oral clefts.

Main Methods:

Utilized a polytomous logistic regression framework adapted for case-parent triads.
Developed an expectation-maximization algorithm to accommodate incompletely genotyped triads.
Simulated data to evaluate the method's statistical power and Type I error rates.

Main Results:

The proposed method effectively analyzes multiplicative gene-by-environment interaction in case-parent studies.
The approach is robust to population stratification and self-selection biases.
Simulations demonstrated comparable power and Type I error rates to existing methods.
The method allows for estimation of interaction parameters without assuming gene-environment independence.

Conclusions:

The developed polytomous logistic regression method provides a flexible and robust approach for studying gene-by-environment interactions in case-parent studies.
This method enhances the understanding of complex disease etiology by accurately assessing joint genetic and environmental effects.
The approach is applicable to various genetic polymorphisms and environmental exposures, as demonstrated with oral clefts and maternal smoking.