A Model for Fine Mapping in Family Based Association Studies

Genome wide association studies for complex diseases are typically followed by more focused characterization of the identified genetic region. We propose a latent class model to evaluate a candidate region with several measured markers using observations on families. The main goal is to estimate linkage disequilibrium (LD) between the observed markers and the putative true but unobserved disease locus in the region. Based on this model, we estimate the joint distribution of alleles at the observed markers and the unobserved true disease locus, and a penetrance parameter measuring the impact of the disease allele on disease risk. A family specific random effect allows for varying baseline disease prevalences for different families. We present a likelihood framework for our model and assess its properties in simulations. We apply the model to an Alzheimer data set and confirm previous findings in the ApoE region.