Informative-Transmission Disequilibrium Test (i-TDT):Combined Linkage and Association Mapping That Includes Unaffected Offspring as Well as Affected Offspring

Authors: GUO, C - BOSTON UNIVERSTIY; LUNETTA, K - BOSTON UNIVERSITY; DESTEFANO, A - BOSTON UNIVERSITY; Ordovas, Jose; CUPPLES, L - BOSTON UNIVERSITY

Submitted to: Genetic Epidemiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/4/2006
Publication Date: 11/22/2006
Citation: Guo, C.Y., Lunetta, K.L., Destefano, A.L., Ordovas, J.M., Cupples, L.A. 2006. Informative-Transmission Disequilibrium Test (i-TDT):Combined Linkage and Association Mapping That Includes Unaffected Offspring as Well as Affected Offspring. Genetic Epidemiology. 31(2):115-33.

Interpretive Summary: Recently, family-based association studies have drawn substantial attention in statistical genetics. The transmission/disequilibrium test (TDT) was proposed to test linkage and association between a marker and a disease locus using ascertained affected individuals and his/her parental marker information to determine if a specific allele is transmitted preferentially [Spielman et al., 1993]. The composite null hypothesis of the TDT is no linkage or no association, which means that when there is no association in the presence of linkage, or no linkage in the presence of association, the TDT will not reject the composite null hypothesis to yield a significant result. When testing for linkage, transmissions from heterozygous parents to all of their affected offspring within the same family can be considered in the TDT analysis. However, when related affected offspring are used in the analysis, the TDT does not provide a valid test for association. One remedy is to select a single affected offspring from each nuclear family, creating a major disadvantage in loss of power. Martin et al. [1997] presented a statistic, which focuses on the set of transmissions from a parent to his/her affected offspring, rather than focusing on the individual transmissions to each offspring. They explored one case in which all nuclear families have two affected offspring. Let S11 (S22) be the number of heterozygous parents who transmitted the B1 (B2) allele to both affected offspring. The TDTsp is valid for the composite null hypothesis of no linkage or no association and is more powerful than the TDT that uses one randomly selected offspring from each family. Discordant sibship methods, which use genotype information from both affected and unaffected offspring without parental data, were developed subsequently for situations where parental information is not available due to late onset disease [Curtis, 1997; Boehnke and Langefeld,1998; Spielman and Ewens, 1998; Horvath and Laird, 1998]. Later, the family-based association test (FBAT) of Rabinowitz and Laird [2000] was introduced to deal with a broad class of FBAT that adjust for admixture for either dichotomous or measured phenotypes. Genotypes of unaffected siblings are used to infer parental genotypes when parental genotypes are incomplete, but their genotypes are not incorporated in its score statistic. The null hypothesis of FBAT is "no linkage and no association", when there is more than one offspring in the family, or when there are several nuclear families within a pedigree. The FBAT does not provide a valid test for association under the two circumstances, since its type-I error is inflated over the nominal level when there is no association in the presence of linkage. Unless the study sample contains only independent trios, the FBAT will not be valid for testing association. Therefore, Lake et al. [2000] proposed the usage of an empirical variance in the score statistic to provide a valid test for association (FBAT with -e option), and the null hypothesis of FBAT becomes "no association in the presence of linkage" under such scenarios. Later, Lunetta et al. [2000] proposed the TDTau, which utilizes both affected and unaffected offspring and was incorporated into the score statistic (FBAT-o: FBAT with "-o" option) to provide a valid test for linkage. Like the FBAT, the TDTau can be a valid test for association if each nuclear family contains exactly one affected or one unaffected offspring. However, if there are more than one affected or unaffected offspring within the same nuclear family, this test is valid for linkage but not for association. When the empirical variance is used (FBAT-o-e: FBAT with both -o and -e options, see the FBAT manual for details), it is a valid test for association in the presence of linkage. Recently, Lewinger and Bull [2006] proposed a new test for linkage in the p

Technical Abstract: To date, there is no test valid for the composite null hypothesis of no linkage or no association that utilizes transmission information from heterozygous parents to their unaffected offspring as well as the affected offspring from ascertained nuclear families. Since the unaffected siblings also provide information about linkage and association, we introduce a new strategy called the informative-transmission disequilibrium test (i-TDT), which uses transmission information from heterozygous parents to all of the affected and unaffected offspring in ascertained nuclear families and provides a valid chi-square test for both linkage and association. The i-TDT can be used invarious study designs and can accommodate all types of independent nuclear families with at least one affected offspring. We show that the transmission/disequilibrium test (TDT) (Spielman et al. [1993] Am. J. Hum. Genet. 52:506-516) is a special case of the i-TDT, if the study sample contains only case-parent trios. If the sample contains only affected and unaffected offspring without parental genotypes, the i-TDT is equivalent to the sibship disequilibrium test (SDT) (Horvath and Laird [1998] Am. J. Hum. Genet. 63:1886-1897. In addition, the test statistic of i-TDT is simple, explicit and can be implemented easily without intensive computing. Through computer simulations, we demonstrate that power of the i-TDT can be higher in many circumstances compared to a method that uses affected offspring only. Applying the i-TDT to the Framingham Heart Study data, we found that the apolipoprotein E (APOE) gene is significantly linked and associated with cross-sectional measures and longitudinal changes in total cholesterol.