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Genotype-environment interaction in transmission disequilibrium tests.

L J Eaves¹, P Sullivan

¹Department of Human Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond 23298, USA.

Advances in Genetics

|October 19, 2000

Summary

Transmission disequilibrium tests (TDTs) can now detect genotype-environment interactions and genomic imprinting effects. This enhanced logistic regression approach improves the detection of genetic associations with complex disorders.

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Area of Science:

Genetics
Biostatistics
Complex Disease Research

Background:

Transmission disequilibrium tests (TDTs) are used to detect associations between marker alleles and complex disorder risk.
Conventional TDTs may miss significant genetic effects influenced by genotype-environment interactions (G x E).

Purpose of the Study:

To generalize the logistic regression approach for TDTs to separately test marker main effects and G x E.
To adapt the model for detecting genomic imprinting effects on susceptibility loci.
To evaluate the model's ability to detect genetic effects and G x E with various family structures.

Main Methods:

Generalized logistic regression model applied to TDTs.
Simulations using offspring-parent trios, sibling pairs, and monozygotic twin pairs.

Related Experiment Videos

Analysis of marker allele effects, G x E, and genomic imprinting.

Main Results:

The logistic regression model successfully detects marker main effects and G x E, even when conventional TDTs fail.
The model can identify alleles influencing phenotype through sensitivity to the within-family environment using MZ twin pairs.
Genotype-environment correlation does not bias TDT outcomes despite potential spurious associations in population studies.

Conclusions:

The generalized logistic regression TDT offers a powerful tool for dissecting complex genetic architectures, including G x E and imprinting.
This method enhances the detection of genetic associations with complex disorders by accounting for environmental influences.
The approach is robust across different family structures and environmental contexts.