Issues concerning association studies for fine mapping a susceptibility gene for a complex disease

The usefulness of association studies for fine mapping loci with common sus ceptibility alleles for complex genetic diseases in outbred populations is unclear. We investigate this issue for a battery of tightly linked anonymou s genetic markers spanning a candidate region centered around a disease loc us, and study the joint behavior of chi-square statistics used to discover and to localize the disease locus. We used simulation methods based on a co alescent process with mutation, recombination, and genetic drift to examine the spatial distribution of markers with large noncentrality parameters in a case-control study design. Simulations with a disease allele at intermed iate frequency, presumably representing an old mutation, tend to exhibit th e largest noncentrality parameter values st markers near the disease lotus. In contrast, simulations with a disease allele at low frequency, presumabl y representing a young mutation, often exhibit the largest noncentrality pa rameter values at markers scattered over the candidate region. In the forme r cases, sample sizes or marker densities sufficient to detect association are likely to lead to useful localization, whereas, in the latter case, loc alization of the disease locus within the. candidate region is much less li kely. regardless of the sample size or density of the map. The effects of i ncreasing sample size or marker density are also investigated. Based upon a single marker analysis, we find that a simple strategy of choosing the mar ker with the smallest associated P value to begin a laboratory search for t he disease locus performs adequately for a common disease allele. We also i nvestigated a strategy of pooling nearby sites to form multiple allele mark ers. Using multiple degree of freedom chi-square tests for two or three nea rby sites, we found no clear advantage of this form of pooling over a singl e marker analysis.