The objective of this genetic epidemiology study is to separate the environmental (dietary and lifestyle) and genetic contributions to familial aggregation of colorectal cancer. Specifically, this project will 1) use a matched case-control design to sample 550 pairs of population-based cases and controls (of whom half have been interviewed in an ongoing study), to ascertain their parents, siblings and spouses (7700 relatives expected); 2) develop three statistical methods that will be used to (a) explore patterns of familial aggregation with and without adjusting for environmental covariates, (b) perform segregation analysis after adjusting for environmental covariates, and (c) test gene- environmental interactions; and 3) study familial aggregation of colorectal cancer after adjusting for dietary and lifestyle covariates. Data collection will consist of face-to-face interviews of all cases and controls, and telephone interviews of their relatives. In both interviews, identical questionnaires will be used to obtain information on background, diet, medical history, anthropometric measurements and physical exercise. This information will enable us to quantify intakes of dietary fat, protein, calories, cholesterol, fiber and alcohol as well as levels of physical activity and obesity. Methods of collecting this information have been validated and used successfully in ongoing studies by our research group. This study will be important whether or not the results confirm any familial aggregation of colorectal cancer after adjusting for the dietary and lifestyle covariates. If, after the adjustment, familial aggregation of colorectal cancer is not significant, this would imply that the genetic contribution to the etiology of colorectal cancer is less important, and that the search for responsible genes or genetic markers might not be fruitful. Our expectation, however, is that familial aggregation of colorectal cancer will persist after adjusting for these environmental covariates, suggesting the importance of genetic factors in the etiology of colorectal cancer. Through segregation analysis, we will be able to differentiate between major (dominant, co-dominant and recessive) and poly genes, thereby providing some guidance in the search for the responsible "genes". Similarly, by testing gene-environment interactions, we will be able to identify those dietary habits and other lifestyle behaviors that may be particularly important risk factors in genetically predisposed individuals, thereby providing some guidance for future cancer prevention efforts. Finally, statistical methods developed in this project can be generally used for other genetic epidemiology studies with the same design.