Linkage disequilibrium mapping: the role of population history, size, and structure

Linkage disequilibrium mapping attempts to infer the location of a disease gene from observed associations between marker alleles and disease phenotype. This approach can be quite powerful when disease chromosomes are descended from a single founder mutation and the markers considered are tightly linked to the disease locus. The success of linkage disequilibrium map ping in fine-scale localization has led to the suggestion that genome-wide association testing might be useful in the detection of susceptibility genes for complex traits. Such studies would likely be performed in small, relatively isolated founder populations, where heterogeneity of the disease is less likely. To interpret the patterns of association observed in such populations, we need to understand the effect of population size, history, and structure on linkage disequilibrium. In this chapter, we first review measures of allelic association at a single locus. Measures of association between two loci are described, and some theoretical results are reviewed. We then consider some methods for inferring linkage between a marker and a rare disease, focusing on those that model the ancestry of the disease chromosomes. Next we discuss factors whose effect on disequilibrium are understood, and finally we describe the characteristics of some human populations that may be useful for disequilibrium mapping of complex traits.