A general test of association for quantitative traits in nuclear families

High-resolution mapping is an important step in the identification of compl ex disease genes. In outbred populations, linkage disequilibrium is expecte d to operate over short distances and could provide a powerful fine-mapping tool. Here we build on recently developed methods for linkage-disequilibri um mapping of quantitative traits to construct a general approach that can accommodate nuclear families of any size, with or without parental informat ion. Variance components are used to construct a test that utilizes informa tion from all available offspring but that is not biased in the presence of linkage or familiality. A permutation test is described for situations in which maximum-likelihood estimates of the variance components are biased. S imulation studies are used to investigate power and error rates of this app roach and to highlight situations in which violations of multivariate norma lity assumptions warrant the permutation test: The relationship between pow er and the level of linkage disequilibrium for this test suggests that the method is well suited to the analysis of dense maps. The relationship betwe en power and family structure is investigated, and these results are applic able to study design in complex disease, especially for late-onset conditio ns for which parents are usually not available. When parental genotypes are available, power does not depend greatly on the number of offspring in eac h family. Power decreases when parental genotypes are not available, but th e loss in power is negligible when four or more offspring per family are ge notyped. Finally, it is shown that, when siblings are available, the total number of genotypes required in order to achieve comparable power is smalle r if parents are not genotyped.