LOCATION:   1252 Howe Hall
                                     
SPEAKER:   Christine Spinka, Texas A & M, College Station, Texas

 

TITLE: Gene Environment Interactions in Genetic Epidemiology

ABSTRACT:

In developed countries, complex diseases are extremely important as they are one of the leading causes of mortality. Complex diseases are frequently characterized by the presence of both genetic and environmental factors. Interactions between these factors are often as important as the genetic information itself in determining the probability of disease in patients. Unfortunately, many important human diseases develop late in life, requiring the use of retrospective sampling designs. In many cases these studies are performed using the case-control study design, and the probability of disease is modeled using logistic regression. However, many covariates of interest, such as weight or age, are continuous and little is known about their distributions. In this talk, we discuss a new method for estimating the gene-environment interaction parameters in a logistic regression for the case-control study design. We assume that in the underlying population, the distributions of the genetic factors and the environmental covariates are independent. Additionally, the method we propose is semiparametric, utilizing the profile likelihood. Thus, we do not require any assumptions about the distribution of the environmental covariates. Furthermore, the methodology we develop is also general enough to be used on many different types of genetic information, including haplotypes, and can accommodate missing genotype data. These methods are illustrated using simulations and are applied to a real data set exploring the interaction between genotype and environment in disease risk. COFFEE: 10:30 a.m., 104 Snedecor Hall