A Review of Statistical Methods for Testing Genetic Anticipation: Looking for an Answer in Lynch Syndrome

• Activity Number: 235
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Philip Boonstra*+ and Bhramar Mukherjee and Stephen Gruber
• Companies: University of Michigan and University of Michigan and University of Michigan
• Keywords: Cox proportional hazards ; Hereditary nonpolyposis colorectal cancer ; Kaplan- Meier estimate ; Random effects

Abstract

We review methods for testing for genetic anticipation (decreasing age of onset in genetic diseases) that address the issue of bias due to right truncation. Using parent-child pair data, we compare the (biased) paired t-test with a previously-developed parametric conditional maximum likelihood approach and a nonparametric approach. Focusing on genetic anticipation in Lynch syndrome (HNPCC), we analyze new data on age of onset from a clinic-based dataset and compare the results to a previously-analyzed population-based Lynch syndrome cohort. Both indicate evidence of genetic anticipation in Lynch syndrome. We then expand our review to include recently proposed statistical methods that consider the family as the sampling unit. Finally, we propose a Bayesian analysis of these models which allows for posterior predictive probabilities for individuals and model assessment.