Gene-environment interaction and the mapping of complex traits: some statistical models and their implications.
The manifestation of many complex diseases or traits is very likely the result of an inextricable interplay of the biological and the environmental. Yet the role of environmental effect has traditionally been played down, for various reasons. In this paper, some simple statistical models that incorporate gene-environment interaction (GEI) have been proposed and their behavior and implications investigated. These implications concern the conditional independence assumption in likelihood calculation of pedigree data, the fine-tuning of the sib pair method for mapping quantitative traits, apportioning of disease or trait variation due to specific causes. In addition, they concern properties of gene mapping methods that do not take GEI into account, and they bring into question the utility of commonly used measures of genetic effects such as recurrence risk ratio for relative pairs, twin concordance rates, and heritability coefficients. In the presence of GEI, all these measures are functions not only of genetic effects and gene frequency, but also of environmental effects, the distribution of environmental factors in the population, and of GEI. Above all, these measures are all measures of familial aggregation, since they can be significant even in the absence of any genetic component of the disease. Thus their use as indicators of the genetic basis of complex diseases is cast into doubt.
Guo
S W
SW
The M. McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, Medical College of Wisconsin, Milwaukee 53226-0509, USA. swguo@mcw.edu
D002874:Chromosome Mapping / Q000379:methods; D004777:Environment; D005796:Genes; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009103:Multiple Sclerosis / Q000235:genetics; D019655:Quantitative Trait, Heritable; D018433:Twin Studies as Topic