Properties of case/pseudocontrol analysis for genetic association studies: Effects of recombination, ascertainment, and multiple affected offspring.
The case/pseudocontrol approach is a general framework for family-based association analysis, incorporating several previously proposed methods such as the transmission/disequilibrium test and log-linear modelling of parent-of-origin effects. In this report, I examine the properties of methods based on a case/pseudocontrol approach when applied to a linked marker rather than (or in addition to) the true disease locus or loci, and when applied to sibships that have been ascertained on, or that may simply contain, multiple affected sibs. Through simulations and analytical calculations, I show that the expected values of the observed relative risk parameters (estimating quantities such as effects due to a child's own genotype, maternal genotype, and parent-of-origin) depend crucially on the ascertainment scheme used, as well as on whether there is non-negligible recombination between the true disease locus and the locus under study. In the presence of either recombination or ascertainment on multiple affected offspring, methods based on conditioning on parental genotypes are shown to give unbiased genotype relative risk estimates at the true disease locus (or loci) but biased estimates of population genotype relative risks at a linked marker, suggesting that the resulting estimates may be misleading when used to predict the power of future studies. Methods that allow for exchangeability of parental genotypes are shown (in the presence of either recombination or ascertainment on multiple affected offspring) to produce false-positive evidence of maternal genotype effects when there are true parent-of-origin or mother-child interaction effects, even when analyzing the true locus. These results suggest that care should be taken in both the interpretation and application of parameter estimates obtained from family-based genetic association studies.
Cordell
Heather J
HJ
Department of Medical Genetics, University of Cambridge, Cambridge, UK. heather.cordell@cimr.cam.ac.uk
D000465:Algorithms; D003198:Computer Simulation; D005260:Female; D008040:Genetic Linkage; D005819:Genetic Markers; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D016014:Linear Models; D015810:Linkage Disequilibrium; D016015:Logistic Models; D008297:Male; D008957:Models, Genetic; D011995:Recombination, Genetic / Q000235:genetics*
D005819:Genetic Markers