Search

Introduction: It is assumed that genetic factors may play a significant role in CKD development. The aim of the study was to investigate the role of rs7903146 polymorphism in the TCF7L2 gene in development and progression of non-diabetic chronic kidney disease (CKD). Material/Methods: 109 children and young adults with CKD caused by primary glomerulopathy and tubulointerstitial nephropathy, stages 3-5, and their 218 biological parents with no renal dysfunction were included in the study. We tested the transmission of alleles of rs7903146 polymorphism in the TCF7L2 gene from heterozygous parents to offspring affected with CKD using the transmission/disequilibrium test. We also analysed whether rs7903146 polymorphism had any impact on the loss of glomerular filtration rate. Results: The rs7903146 polymorphism in TCF7L2 allele transmission from heterozygous parents to their affected children was not different from a random proportion expected for no association, in the whole group of subjects, and in the subgroups, depending on CKD aetiology. Lack of association between the analysed polymorphism and the loss of glomerular filtration rate was found in the total group of patients as well as in the subgroups, regarding the cause of CKD. Conclusions: This study found no association between rs7903146 polymorphism in the TCF7L2 gene and the increased risk for development of CKD caused by primary glomerulopathy and analysed tubulointerstitial nephropathy. The progression rate of CKD of non-diabetic aetiology does not depend on this polymorphism.

Linkage Analysis by a Transmission/Disequilibrium Test of Russian Sibling Pairs with Coronary Artery DiseaseWe studied the association between coronary artery disease (CAD) and polymorphisms of theABCA1, ACE, AGT, eNOSandEFNB3genes in 85 Russian patients with angiography-proven CAD and 100 of their siblings. No gene analyzed had a z-score value of more than 2.47 for CAD or for its main clinical presentations due to sibling transmission/disequilibrium test (S-TDT). However, the DD genotype ofACEis significantly more prevalent in siblings with CAD [p= 0.025, relative risk(RR)2.8], angina (p= 0.028,RR= 3.3) and myocardial infarction (MI) (p= 0.018,RR= 5.5). An increased risk of CAD, and its main manifestations, was associated with the R1587 allele of theABCA1gene: theRRfor developing CAD was 4.88, for MI 6.18, and for angina 3.69 for siblings who were carriers of the R1587R and R1587K genotypes. Index of stenosis was significantly higher in probands with the K219K and R219K genotypes (p= 0.001). The combination of genotype K219K with R219K was more frequent among siblings with CAD (p= 0.044,RR= 2.38), arterial hypertension (p= 0.023,RR= 2.87) and angina (p= 0.027,RR= 3.3). Thus, none of the genes studied can be considered as the main gene associated with CAD. However, the insertion/deletion (I/D) polymorphism of theACEgene and the R219K and R1587K variants ofABCA1are associated with a higher likelihood of developing CAD, MI and angina among Russians who have siblings affected by CAD.

Haplotype sharing analysis was used to investigate the association of affection status with single nucleotide polymorphism (SNP) haplotypes within candidate gene 1 in one sample each from the isolated and the general population of Genetic Analysis Workshop (GAW) 12 simulated data. Gene 1 has direct influence on affection and harbors more than 70 SNPs. Haplotype sharing analysis depends heavily on previous haplotype estimation. Using GENEHUNTER haplotypes, strong evidence was found for most SNPs in the isolated population sample, thus providing evidence for an involvement of this gene, but the maximum -log(10)(p) values for the haplotype sharing statistics (HSS) test statistic did not correspond to the location of the true variant in either population. In comparison, transmission disequilibrium test (TDT) analysis showed the strongest results at the disease-causing variant in both populations, and these were outstanding in the general population. In this example, TDT analysis appears to perform better than HSS in identifying the disease-causing variant, using SNPs within a candidate gene in an outbred population. Simulations showed that the performance of HSS is hampered by closely spaced SNPs in strong linkage disequilibrium with the functional variant and by ambiguous haplotypes.

We applied a new haplotype sharing method to the simulated Genetic Analysis Workshop 12 data for both isolated and general populations without knowledge of the disease model, using affection status as phenotype and three different sample sizes. The highest peak for the mean sharing of the haplotypes was found in the isolated population for the markers D06G034 and D06G035, which flank the candidate genes located on chromosome 6, with -log(10)(p) values of 2.9 and 7.0 in the moderate and large study samples, respectively. The whole genome screen detected three further loci with -log(10)(p) values of 3.0, which turned out to be false positives. None of the true gene loci were detected in the general population even in the largest sample. The test of linkage disequilibrium based on excess haplotype sharing over the linkage equilibrium expectation revealed z-values one order of magnitude higher in the isolated than in the general population. This approach appears to be promising for mapping genes of complex diseases depending on population characteristics. (C) 2001 Wiley-Liss, Inc.

We applied a new haplotype sharing method to the simulated Genetic Analysis Workshop 12 data for both isolated and general populations without knowledge of the disease model, using affection status as phenotype and three different sample sizes. The highest peak for the mean sharing of the haplotypes was found in the isolated population for the markers D06G034 and D06G035, which flank the candidate genes located on chromosome 6, with -log(10)(p) values of 2.9 and 7.0 in the moderate and large study samples, respectively. The whole genome screen detected three further loci with -log(10)(p) values of 3.0, which turned out to be false positives. None of the true gene loci were detected in the general population even in the largest sample. The test of linkage disequilibrium based on excess haplotype sharing over the linkage equilibrium expectation revealed z-values one order of magnitude higher in the isolated than in the general population. This approach appears to be promising for mapping genes of complex diseases depending on population characteristics. (C) 2001 Wiley-Liss, Inc.

The transmission/disequilibrium test (TDT) is a popular, simple, and powerful test of linkage, which can be used to analyze data consisting of transmissions to the affected members of families with any kind pedigree structure, including affected sib pairs (ASPs). Although it is based on the preferential transmission of a particular marker allele across families, it is not a valid test of association for ASPs. Martin et al. devised a similar statistic for ASPs, Tsp, which is also based on preferential transmission of a marker allele but which is a valid test of both linkage and association for ASPs. It is, however, less powerful than the TDT as a test of linkage for ASPs. What I show is that the differences between the TDT and Tsp are due to the fact that, although both statistics are based on preferential transmission of a marker allele, the TDT also exploits excess sharing in identity-by-descent transmissions to ASPs. Furthermore, I show that both of these statistics are members of a family of “TDT-like” statistics for ASPs. The statistics in this family are based on preferential transmission but also, to varying extents, exploit excess sharing. From this family of statistics, we see that, although the TDT exploits excess sharing to some extent, it is possible to do so to a greater extent—and thus produce a more powerful test of linkage, for ASPs, than is provided by the TDT. Power simulations conducted under a number of disease models are used to verify that the most powerful member of this family of TDT-like statistics is more powerful than the TDT for ASPs.

Family-based association methods have recently been introduced that allow testing for linkage in the presence of linkage disequilibrium between a marker and a disease even if there is only incomplete parental-marker information. No such tests are currently available for X-linked markers. This report fills this methodological gap by presenting the X-linked sibling transmission/disequilibrium test (XS-TDT) and the X-linked reconstruction-combination transmission/disequilibrium test (XRC-TDT). As do their autosomal counterparts (S-TDT and RC-TDT), these tests make no assumption about the mode of inheritance of the disease and the ascertainment of the sample. They protect against spurious association due to population stratification. The two tests were compared by simulations, which show that (1) the X-linked RC-TDT is, in general, considerably more powerful than the X-linked S-TDT and (2) the lack of parental-genotype information can be offset by the typing of a sufficient number of sibling controls. A freely available SAS implementation of these tests allows the calculation of exact P values.

SummaryA new transmission/disequilibrium-test statistic is proposed for situations in which transmission is uncertain. Such situations arise when transmission of a multilocus marker haplotype is considered, since haplotype phase is often unknown in a substantial number of instances. Even for single-locus markers, transmission is uncertain if one or both parents are missing. In both these situations, uncertainty may be reduced by the typing of further siblings, whose disease status may be unaffected or unknown. The proposed test is a score test based on a partial score function that omits the terms most influenced by hidden population stratification.

SummaryA generalization of the transmission/disequilibrium test to detect association between polymorphic markers and discrete or quantitative traits is discussed, with particular emphasis on marker haplotypes formed by several adjacent loci. Furthermore, strategies for testing haplotype association, using methods from spatial statistics, are developed. This approach compares the “similarity” of transmitted and untransmitted haplotypes, with the aim of determining the regions where there is greater similarity within the transmitted set. This arises from the fact that, although the original haplotypes carrying the mutation will be broken down by recombination, there may be a subset of markers near the mutation that are common to many of the recombinant haplotypes. Thus, by examination of each marker in turn and by measurement of the average size of the region shared identically by state in the transmitted and untransmitted haplotypes, it may be possible to detect regions of linkage disequilibrium that encompass the susceptibility gene.

SummaryThe transmission/disequilibrium (TD) test (TDT), proposed, by Spielman et al., for binary traits is a powerful method for detection of linkage between a marker locus and a disease locus, in the presence of allelic association. As a test for linkage disequilibrium, the TDT makes the assumption that any allelic association present is due to linkage. Allison proposed a series of TD-type tests for quantitative traits and calculated their power, assuming that the marker locus is the disease locus. All these tests assume that the observations are independent, and therefore they are applicable, as a test for linkage, only for nuclear-family data. In this report, we propose a regression-based TD-type test for linkage between a marker locus and a quantitative trait locus, using information on the parent-to-offspring transmission status of the associated allele at the marker locus. This method does not require independence of observations, thus allowing for analysis of pedigree data as well, and allows adjustment for covariates. We investigate the statistical power and validity of the test by simulating markers at various recombination fractions from the disease locus.

SummaryThe transmission/disequilibrium test (TDT) developed by Spielman et al. can be a powerful family-based test of linkage and, in some cases, a test of association as well as linkage. It has recently been extended in several ways; these include allowance for implementation with quantitative traits, allowance for multiple alleles, and, in the case of dichotomous traits, allowance for testing in the absence of parental data. In this article, these three extensions are combined, and two procedures are developed that offer valid joint tests of linkage and (in the case of certain sibling configurations) association with quantitative traits, with use of data from siblings only, and that can accommodate biallelic or multiallelic loci. The first procedure uses a mixed-effects (i.e., random and fixed effects) analysis of variance in which sibship is the random factor, marker genotype is the fixed factor, and the continuous phenotype is the dependent variable. Covariates can easily be accommodated, and the procedure can be implemented in commonly available statistical software. The second procedure is a permutation-based procedure. Selected power studies are conducted to illustrate the relative power of each test under a variety of circumstances.

Summary Linkage disequilibrium has been used to help in the identification of genes predisposing to certain qualitative diseases. Although several linkage-disequilibrium tests have been developed for localization of genes influencing quantitative traits, these tests have not been thoroughly compared with one another. In this report we compare, under a variety of conditions, several different linkage-disequilibrium tests for identification of loci affecting quantitative traits. These tests use either single individuals or parent-child trios. When we compared tests with equal samples, we found that the truncated measured allele (TMA) test was the most powerful. The trait allele frequencies, the stringency of sample ascertainment, the number of marker alleles, and the linked genetic variance affected the power, but the presence of polygenes did not. When there were more than two trait alleles at a locus in the population, power to detect disequilibrium was greatly diminished. The presence of unlinked disequilibrium ( D ′ * ) increased the false-positive error rates of disequilibrium tests involving single individuals but did not affect the error rates of tests using family trios. The increase in error rates was affected by the stringency of selection, the trait allele frequency, and the linked genetic variance but not by polygenic factors. In an equilibrium population, the TMA test is most powerful, but, when adjusted for the presence of admixture, Allison test 3 becomes the most powerful whenever D ′* >.15.

SummaryThe human leukocyte antigen (HLA) complex, encompassing 3.5 Mb of DNA from the centromeric HLA-DPB2 locus to the telomeric HLA-F locus on chromosome 6p21, encodes a major part of the genetic predisposition to develop type 1 diabetes, designated “IDDM1.” A primary role for allelic variation of the class II HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci has been established. However, studies of animals and humans have indicated that other, unmapped, major histocompatibility complex (MHC)–linked genes are participating in IDDM1. The strong linkage disequilibrium between genes in this complex makes mapping a difficult task. In the present paper, we report on the approach we have devised to circumvent the confounding effects of disequilibrium between class II alleles and alleles at other MHC loci. We have scanned 12 Mb of the MHC and flanking chromosome regions with microsatellite polymorphisms and analyzed the transmission of these marker alleles to diabetic probands from parents who were homozygous for the alleles of the HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes. Our analysis, using three independent family sets, suggests the presence of an additional type I diabetes gene (or genes). This approach is useful for the analysis of other loci linked to common diseases, to verify if a candidate polymorphism can explain all of the association of a region or if the association is due to two or more loci in linkage disequilibrium with each other.

SummaryThe sibship disequilibrium test (SDT) is designed to detect both linkage in the presence of association and association in the presence of linkage (linkage disequilibrium). The test does not require parental data but requires discordant sibships with at least one affected and one unaffected sibling. The SDT has many desirable properties: it uses all the siblings in the sibship; it remains valid if there are misclassifications of the affectation status; it does not detect spurious associations due to population stratification; asymptotically it has a χ2 distribution under the null hypothesis; and exact P values can be easily computed for a biallelic marker. We show how to extend the SDT to markers with multiple alleles and how to combine families with parents and data from discordant sibships. We discuss the power of the test by presenting sample-size calculations involving a complex disease model, and we present formulas for the asymptotic relative efficiency (which is approximately the ratio of sample sizes) between SDT and the transmission/disequilibrium test (TDT) for special family structures. For sib pairs, we compare the SDT to a test proposed both by Curtis and, independently, by Spielman and Ewens. We show that, for discordant sib pairs, the SDT has good power for testing linkage disequilibrium relative both to Curtis's tests and to the TDT using trios comprising an affected sib and its parents. With additional sibs, we show that the SDT can be more powerful than the TDT for testing linkage disequilibrium, especially for disease prevalence >.3.

SummaryPopulation-based tests of association have used data from either case-control studies or studies based on trios (affected child and parents). Case-control studies are more prone to false-positive results caused by inappropriate controls, which can occur if, for example, there is population admixture or stratification. An advantage of family-based tests is that cases and controls are well matched, but parental data may not always be available, especially for late-onset diseases. Three recent family-based tests of association and linkage utilize unaffected siblings as surrogates for untyped parents. In this paper, we propose an extension of one of these tests. We describe and compare the four tests in the context of a complex disease for both biallelic and multiallelic markers, as well as for sibships of different sizes. We also examine the consequences of having some parental data in the sample.

Summary Linkage analysis with genetic markers has been successful in the localization of genes for many monogenic human diseases. In studies of complex diseases, however, tests that rely on linkage disequilibrium (the simultaneous presence of linkage and association) are often more powerful than those that rely on linkage alone. This advantage is illustrated by the transmission/disequilibrium test (TDT). The TDT requires data (marker genotypes) for affected individuals and their parents; for some diseases, however, data from parents may be difficult or impossible to obtain. In this article, we describe a method, called the "sib TDT" (or "S-TDT"), that overcomes this problem by use of marker data from unaffected sibs instead of from parents, thus allowing application of the principle of the TDT to sibships without parental data. In a single collection of families, there might be some that can be analyzed only by the TDT and others that are suitable for analysis by the S-TDT. We show how all the data may be used jointly in one overall TDT - type procedure that tests for linkage in the presence of association. These extensions of the TDT will be valuable for the study of diseases of late onset, such as non–insulin-dependent diabetes, cardiovascular diseases, and other diseases associated with aging.

This work was supported in part by the Special Trustees of Guy's Hospital. We would like to thank Robert Curnow and David Balding for their helpful comments on an earlier draft of this article.

The most simple and commonly used approach for genetic associations is the case-control study design of unrelated people. This design is susceptible to population stratification. This problem is obviated in family-based studies, but it is usually difficult to accumulate large enough samples of well-characterized families. We addressed empirically whether the two designs give similar estimates of association in 93 investigations where both unrelated case-control and family-based designs had been employed. Estimated odds ratios differed beyond chance between the two designs in only four instances (4%). The summary relative odds ratio (ROR) (the ratio of odds ratios obtained from unrelated case-control and family-based studies) was close to unity (0.96 [95% confidence interval, 0.91-1.01]). There was no heterogeneity in the ROR across studies (amount of heterogeneity beyond chance I(2) = 0%). Differences on whether results were nominally statistically significant (p < 0.05) or not with the two designs were common (opposite classification rates 14% and 17%); this reflected largely differences in power. Conclusions were largely similar in diverse subgroup analyses. Unrelated case-control and family-based designs give overall similar estimates of association. We cannot rule out rare large biases or common small biases. PLoS Genet

Times Cited: 66; International audience; Although genotyping errors affect most data and can markedly influence the biological conclusions of a study, they are too often neglected. Errors have various causes, but their occurrence and effect can be limited by considering these causes in the production and analysis of the data. Procedures that have been developed for dealing with errors in linkage studies, forensic analyses and non-invasive genotyping should be applied more broadly to any genetic study. We propose a protocol for estimating error rates and recommend that these measures be systemically reported to attest the reliability of published genotyping studies.

We have previously described linkage/association between reelin gene polymorphisms and autistic disorder. APOE also participates in the Reelin signaling pathway, by competitively antagonizing Reelin binding to APOE receptor 2 and to very-low-density lipoprotein receptors. The APOE2 protein variant displays the lowest receptor binding affinity compared with APOE3 and APOE4. In this study, we assess linkage/association between primary autism and APOE alleles in 223 complete trios, from 119 simplex Italian families and 44 simplex and 29 multiplex Caucasian-American families. Statistically significant disequilibrium favors the transmission of epsilon2 alleles to autistic offspring, over epsilon3 and epsilon4 (allele-wise transmission/disequilibrium test [TDT], chi2 = 6.16, 2 degrees of freedom [d.f.], P

We applied a new haplotype sharing method to the simulated Genetic Analysis Workshop 12 data for both isolated and general populations without knowledge of the disease model, using affection status as phenotype and three different sample sizes. The highest peak for the mean sharing of the haplotypes was found in the isolated population for the markers D06G034 and D06G035, which flank the candidate genes located on chromosome 6, with -log(10)(p) values of 2.9 and 7.0 in the moderate and large study samples, respectively. The whole genome screen detected three further loci with -log(10)(p) values of 3.0, which turned out to be false positives. None of the true gene loci were detected in the general population even in the largest sample. The test of linkage disequilibrium based on excess haplotype sharing over the linkage equilibrium expectation revealed z-values one order of magnitude higher in the isolated than in the general population. This approach appears to be promising for mapping genes of complex diseases depending on population characteristics. (C) 2001 Wiley-Liss, Inc.

Autistic disorder (MIM 209850) is currently viewed as a neurodevelopmental disease. Reelin plays a pivotal role in the development of laminar structures including the cerebral cortex, hippocampus, cerebellum and of several brainstem nuclei. Neuroanatomical evidence is consistent with Reelin involvement in autistic disorder. In this study, we describe several polymorphisms identified using RNA-SSCP and DNA sequencing. Association and linkage were assessed comparing 95 Italian patients to 186 ethnically-matched controls, and using the transmission/disequilibrium test and haplotype-based haplotype relative risk in 172 complete trios from 165 families collected in Italy and in the USA. Both case-control and family-based analyses yield a significant association between autistic disorder and a polymorphic GGC repeat located immediately 5′ of the reelin gene (RELN) ATG initiator codon, as well as with specific haplotypes formed by this polymorphism with two single-base substitutions located in a splice junction in exon 6 and within exon 50. Triplet repeats located in 5′ untranslated regions (5′UTRs) are indicative of strong transcriptional regulation. Our findings suggest that longer triplet repeats in the 5′UTR of the RELN gene confer vulnerability to autistic disorder.

The transmission/disequilibrium test (TDT), which detects linkage between a marker and disease loci in the presence of linkage disequilibrium, was introduced by Spielman et al. The original TDT requires families in which the genotypes are known for both parents and for at least one affected offspring, and this limits its applicability to diseases with late onset. The sib-TDT, or S-TDT, which utilizes families with affected and unaffected siblings, was introduced as an alternative method, by Spielman and Ewens, and the TDT and S-TDT can be combined in an overall test (i.e., a combined-TDT, or C-TDT). The TDT statistics described so far are for autosomal chromosomes. We have extended these TDT methods to test for linkage between X-linked markers and diseases that affect either males only or both sexes. For diseases of late onset, when parental genotypes are often unavailable, the X-linkage C-TDT may allow for more power than is provided by the X-linkage TDT alone.

SummaryMost noninfectious disease is caused by low-penetrance alleles interacting with other genes and environmental factors. Consider the simple setting where a diallelic autosomal candidate gene and a binary exposure together affect disease susceptibility. Suppose that one has genotyped affected probands and their parents and has determined each proband's exposure status. One proposed method for assessment of etiologic interaction of genotype and exposure, an extension of the transmission/disequilibrium test, tests for differences in transmission of the variant allele from heterozygous parents to exposed versus unexposed probands. We show that this test is not generally valid. An alternative approach compares the conditional genotype distribution of unexposed cases, given parental genotypes, versus that of exposed cases. This approach provides maximum-likelihood estimators for genetic relative-risk parameters and genotype-exposure–interaction parameters, as well as a likelihood-ratio test (LRT) of the no-interaction null hypothesis. We show how to apply this approach, using log-linear models. When a genotype-exposure association arises solely through incomplete mixing of subpopulations that differ in both exposure prevalence and allele frequency, the LRT remains valid. The LRT becomes invalid, however, if offspring genotypes do not follow Mendelian proportions in each parental mating type—for example, because of genotypic differences in survival—or if a genotype-exposure association reflects an influence of genotype on propensity for exposure—for example, through behavioral mechanisms. Because the needed assumptions likely hold in many situations, the likelihood-based approach should be broadly applicable for diseases in which probands commonly have living parents.

It has been demonstrated in the literature that the transmission/disequilibrium test (TDT) has higher power than the affected-sib-pair (ASP) mean test when linkage disequilibrium (LD) is strong but that the mean test has higher power when LD is weak. Thus, for ASP data, it seems clear that the TDT should be used when LD is strong but that the mean test or other linkage tests should be used when LD is weak or absent. However, in practice, it may be difficult to follow such a guideline, because the extent of LD is often unknown. Even with a highly dense genetic-marker map, in which some markers should be located near the disease-predisposing mutation, strong LD is not inevitable. Besides the genetic distance, LD is also affected by many factors, such as the allelic heterogeneity at the disease locus, the initial LD, the allelic frequencies at both disease locus and marker locus, and the age of the mutation. Therefore, it is of interest to develop methods that are adaptive to the extent of LD. In this report, we propose a disequilibrium maximum-binomial-likelihood (DMLB) test that incorporates LD in the maximum-binomial-likelihood (MLB) test. Examination of the corresponding score statistics shows that this method adaptively combines two sources of information: (a) the identity-by-descent (IBD) sharing score, which is informative for linkage regardless of the existence of LD, and (b) the contrast between allele-specific IBD sharing score, which is informative for linkage only in the presence of LD. For ASP data, the proposed test has higher power than either the TDT or the mean test when the extent of LD ranges from moderate to strong. Only when LD is very weak or absent is the DMLB slightly less powerful than the mean test; in such cases, the TDT has essentially no power to detect linkage. Therefore, the DMLB test is an interesting approach to linkage detection when the extent of LD is unknown.

SummaryThe transmission/disequilibrium test (TDT) is a popular method for detection of the genetic basis of a disease. Investigators planning such studies require computation of sample size and power, allowing for a general genetic model. Here, a rigorous method is presented for obtaining the power approximations of the TDT for samples consisting of families with either a single affected child or affected sib pairs. Power calculations based on simulation show that these approximations are quite precise. By this method, it is also shown that a previously published power approximation of the TDT is erroneous.

SummarySpielman and Ewens recently proposed a method for testing a marker for linkage with a disease, which combines data from families with and without information on parental genotypes. For some families without parental-genotype information, it may be possible to reconstruct missing parental genotypes from the genotypes of their offspring. The treatment of such a reconstructed family as if parental genotypes have been typed, however, can introduce bias. In the present study, a new method is presented that employs parental-genotype reconstruction and corrects for the biases resulting from reconstruction. The results of an application of this method to a real data set and of a simulation study suggest that this approach may increase the power to detect linkage.

SummaryRecent admixture between genetically differentiated populations can result in high levels of association between alleles at loci that are ≤10 cM apart. The transmission/disequilibrium test (TDT) proposed by Spielman et al. (1993) can be a powerful test of linkage between disease and marker loci in the presence of association and therefore could be a useful test of linkage in admixed populations. The degree of association between alleles at two loci depends on the differences in allele frequencies, at the two loci, in the founding populations; therefore, the choice of marker is important. For a multiallelic marker, one strategy that may improve the power of the TDT is to group marker alleles within a locus, on the basis of information about the founding populations and the admixed population, thereby collapsing the marker into one with fewer alleles. We have examined the consequences of collapsing a microsatellite into a two-allele marker, when two founding populations are assumed for the admixed population, and have found that if there is random mating in the admixed population, then typically there is a collapsing for which the power of the TDT is greater than that for the original microsatellite marker. A method is presented for finding the optimal collapsing that has minimal dependence on the disease and that uses estimates either of marker allele frequencies in the two founding populations or of marker allele frequencies in the current, admixed population and in one of the founding populations. Furthermore, this optimal collapsing is not always the collapsing with the largest difference in allele frequencies in the founding populations. To demonstrate this strategy, we considered a recent data set, published previously, that provides frequency estimates for 30 microsatellites in 13 populations.