Modeling of Susceptibility Genes for Cancer Risk Estimation in Family Studies

• Activity Number: 122
• Type: Contributed
• Date/Time: Monday, August 1, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Chih-Chieh Wu*+ and Louise C. Strong and Sanjay Shete
• Companies: The University of Texas MD Anderson Cancer Center and The University of Texas MD Anderson Cancer Center and The University of Texas MD Anderson Cancer Center
• Keywords: statistical genetics ; family studies ; familial cancer ; genetic epidemiology

Abstract

Numerous family studies have been performed to assess the associations between cancer incidence and genetic and non-genetic risk factors and to quantitatively evaluate the cancer risk attributable to these factors. As more and more mutated genes and risk alleles have been discovered or identified over the past few decades, it becomes increasingly important to incorporate information on known susceptibility genotypes into cancer risk analyses. However, mathematical models that account for measured (known) susceptibility genes have not been explored in family studies. We have developed a method to precisely model measured susceptibility genes accounting for intra-familial correlation in hereditary mutation distribution and to simultaneously determine the combined effects of individual risk factors and their interactions. Our method accounts for measured hereditary susceptibility genotypes of the proband and each relative in a family. Our approach is structured for age-specific risk models based on Cox proportional hazards regression. We exemplified the method by analyzing various family data of Li-Fraumeni syndrome with TP53 germ-line mutations and genetic modifier of MDM2 SNP309.