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Gene-Environment Interactions

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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...

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Related Experiment Video

Updated: May 23, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

Adjusting for spurious gene-by-environment interaction using case-parent triads.

Ji-Hyung Shin¹, Claire Infante-Rivard, Jinko Graham

¹Simon Fraser University.

Statistical Applications in Genetics and Molecular Biology

|April 14, 2012

Summary

This summary is machine-generated.

Population stratification can cause false gene-by-environment interactions in genetic studies. This study introduces a new method using case-parent trios and genetic markers to correct for spurious interactions without needing sibling data.

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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

Genetics
Epidemiology
Biostatistics

Background:

The case-parent trio design is used to study genetic effects and gene-environment interactions.
Population stratification can lead to spurious gene-by-environment interactions at non-causal loci.

Purpose of the Study:

To explore the source of spurious interactions in case-parent trio studies.
To propose an alternative method to mitigate spurious interactions without requiring unaffected sibling data.

Main Methods:

Utilizing case-parent trios with genetic data from affected children and parents.
Adjusting risk models with ancestry informative markers or random markers from affected children.
Developing a data generation approach implemented in an R package.

Main Results:

Identified population stratification as a source of spurious gene-by-environment interactions.
Developed a robust method to correct for spurious interactions in case-parent trios.
Demonstrated the approach does not require data from unaffected siblings.

Conclusions:

The proposed method effectively mitigates spurious gene-by-environment interactions in case-parent trio studies.
This approach offers a valuable alternative for genetic association studies, enhancing accuracy and reducing data requirements.