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Gene-environment interaction and the mapping of complex traits: some statistical models and their implications
1The M. McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College of Wisconsin, Milwaukee 53226-0509, USA. swguo@mcw.edu
Human Heredity
|July 6, 2000
Summary
Complex diseases arise from gene-environment interactions (GEI). Traditional genetic measures may be misleading when GEI is present, questioning their utility in complex disease research.
Area of Science:
- Genetics
- Environmental Health
- Biostatistics
Background:
- Complex diseases result from gene-environment interplay.
- Environmental factors' role is often underestimated.
- Gene-environment interaction (GEI) models are crucial for understanding disease.
Purpose of the Study:
- To propose and investigate simple statistical models for GEI.
- To explore the implications of GEI on genetic analysis methods.
- To re-evaluate commonly used measures of genetic effects.
Main Methods:
- Development of statistical models incorporating GEI.
- Analysis of GEI's impact on pedigree data and quantitative trait mapping.
- Assessment of traditional genetic measures under GEI.
Main Results:
- GEI affects likelihood calculations and trait mapping.
- Common genetic measures (heritability, twin concordance) are influenced by environmental factors and GEI.
- These measures may indicate familial aggregation without a genetic basis.
Conclusions:
- GEI significantly impacts the interpretation of genetic studies.
- Traditional measures of genetic effects are unreliable in the presence of GEI.
- Rethinking genetic analysis is necessary for complex diseases.