Family data teamed with the transmission/disequilibrium test (TDT), which simultaneously evaluates

Family data teamed with the transmission/disequilibrium test (TDT), which simultaneously evaluates linkage and association, is a powerful means of detecting disease-liability alleles. is developed for two cases: when haplotype transmission is certain and when it is not. Simulations show the ET-TDT can be more powerful than other proposed methods under reasonable conditions. More importantly, our results show that, when multiple polymorphisms are found within the gene, the ET-TDT can be useful for determining which polymorphisms affect liability. Introduction Linkage and association between disease status and marker alleles can help pinpoint a liability locus that affects a complex disease or phenotype. To circumvent spurious associations arising from population heterogeneity, Falk and Rubinstein (1987) proposed using the alleles transmitted from parents to their affected offspring as case observations and using untransmitted Cdx1 alleles as control observations. From their insight evolved the transmission/disequilibrium test (TDT) (Spielman et al. 1993). For families containing affected offspring, such as affected sib pairs with parents, the TDT uses the 483-63-6 supplier distribution of marker alleles within and among families to test for linkage and association while controlling for population heterogeneity (Ewens and Spielman 1995). The power of the TDT in this setting has been amply demonstrated by the original analysis of insulin-dependent diabetes mellitus and a 5 flanking polymorphism of the insulin locus (Spielman et al. 1993) and by subsequent power analyses (e.g., Risch and Merikangas 1996; Knapp 1999). For these reasons, the TDT and allied tests have become a favorite tool for analysis of genetic linkage and of association in 483-63-6 supplier complex diseases. A stringent requirement of the original TDT is the definitive transmission of alleles from parents to offspring. Therefore, for a single marker, at least one parent must be heterozygous. Even then, transmissions may not be obvious when parents and offspring are all heterozygous for the same biallelic marker. To increase definitive transmissions, several authors have proposed TDT tests using haplotypes (e.g., Lazzeroni and Lange 1998; Merriman et al. 1998; Clayton and Jones 1999; Clayton 1999; Rabinowitz and Laird 2000; Zhao et al. 2000). In all but the most extreme case of absolute association, transmissions from parents to offspring are more informative for 483-63-6 supplier haplotypes than for single markers. One trade-off, however, is the increase in the degrees of freedom of the test: in general, for realized haplotypes, the tests follow a 2 distribution, having … In this particular example (fig. 1), assuming the causal mutation is not measured, 11 distinct haplotypes are observed in the sample: the MRCA of all the haplotypes (founder) and the 10 new haplotypes created by the 11 depicted mutations. 483-63-6 supplier Label the founder as A, and, working from the root of the tree onward, label each new haplotype in the order of occurrence of marker mutations to obtain haplotypes BCL; notice that B is not observed in the extant population. With this one exception, each observed haplotype can be connected to another that differs by a single mutation. Three of the haplotypes (A, H, and J) have the disease mutation embedded in their history, but the remaining seven do not. If there were no other disease mutations in this chromosomal region, these seven haplotypes would share a common probability of being associated with a disease outcome, and the three haplotypes bearing the disease mutation would share a different common probability. Notice the scenario would become more complex if the third marker mutation from the founder were not measured: in this case, D merges with A, and some of these haplotypes do not have the disease mutation; hence, on average, the relative risk of this haplotype is lower than that of the other two mutation-bearing haplotypes (H and J). If the time at which the mutational events occurred is ignored, the remaining information contained in the rooted tree (fig. 1) emerges as an unrooted tree called 483-63-6 supplier a cladogram (fig. 2), with edges representing mutations that result in new haplotypes. Such a cladogram can be reconstructed from a sample of haplotypes, using the method of maximum parsimony, as implemented in the computer program PAUP (Swofford 1998). The parsimony algorithm.