Detection of parent-of-origin effects in complete and incomplete nuclear families with multiple affected children using multiple tightly linked markers

For a diallelic marker locus, the parental-asymmetry test (PAT) based on case-parents trios and its extensions to accommodate incomplete unclear families (1-PAT and C-PAT) are simple and powerful approaches to test for parent-of-origin effects. However, haplotype analysis is generally regarded as advantageous over single-marker analysis in genetic study of common complex diseases. This is mainly due to the fact that complex diseases are often associated with multiple markers. As such, HAP-PAT was constructed to test for parent-of-origin effects in the framework of haplotype analysis. However, its applicability is limited due to the need for complete parental information. In this paper, for nuclear families with only one parent and multiple affected children, we develop HAP-1-PAT to test for parent-of-origin effects using multiple tightly linked markers. We further propose HAP-C-PAT to combine data from families with both parents and those with only one parent. We carry out a simulation study to evaluate the validity and power of the test statistics in various settings, including incomplete family rates, marker/disease-locus linkage disequilibrium patterns, and population models. We perform analysis for all possible combinations of the markers being considered. A permutation-based Monte Carlo procedure is devised to determine the significance of the tests; the corrected global p values taking into account of multiple testing are used for inferences. The results show that HAP-1-PAT and HAP-C-PAT would work well even under the population stratification demographic model and assortative mating demographic model. Furthermore, for the disease models considered, there are significant gains in power from haplotype analysis compared to single-marker analysis, and from combined analysis using HAP-C-PAT compared to analysis using HAP-PAT for the complete family data only.