The susceptibility to develop coeliac disease (CD) has a strong genetic component, which is not entirely explained by HLA associations. Two previous genome wide linkage studies have been performed to identify additional loci outside this region. These studies both used a sib-pair design and produced conflicting results.

Our aim is to identify non-MHC genetic loci contributing to coeliac disease using a family based linkage study. We performed a genome wide search in 16 highly informative multiply affected pedigrees using 400 microsatellite markers with an average spacing of 10 cM. Linkage analysis was performed using lod score and model free methods.

We identified two new potential susceptibility loci with lod scores of 1.9, at 10q23.1, and 16q23.3. Significant, but lower lod scores were found for 6q14 (1.2), 11p11 (1.5), and 19q13.4 (0.9), areas implicated in a previous genome wide study. Lod scores of 0.9 were obtained for both D7S507, which lies 1 cM from the γT-cell receptor gene, and for D2S364, which lies 12 cM from the CTLA4 gene.

The analysis of the hypervariable regions I and II of mitochondrial DNA in Portugal showed that this Iberian population presents a higher level of diversity than some neighbouring populations. The classification of the different sequences into haplogroups revealed the presence of all the most important European haplogroups, including those that expanded through Europe in the Palaeolithic, and those whose expansion has occurred during the Neolithic. Additionally a rather distinct African influence was detected in this Portuguese survey, as signalled by the distributions of haplogroups U6 and L, present at higher frequencies than those usually reported in Iberian populations. The geographical distributions of both haplogroups were quite different, with U6 being restricted to North Portugal whereas L was widespread all over the country. This seems to point to different population movements as the main contributors for the two haplogroup introductions. We hypothesise that the recent Black African slave trade could have been the mediator of most of the L sequence inputs, while the population movement associated with the Muslim rule of Iberia has predominantly introduced U6 lineages.

Forty four families from Guinea–Conakry were analysed to test for association between NRAMP1 (Natural Resistance Associated Macrophage Protein 1) polymorphisms and tuberculosis. Each family included at least one affected sib and one parent. Healthy sibs were also analysed and on average the families included four members. A total of 160 individuals were included in the final dataset. The analysis of association was performed using an extended TDT test, TRANSMIT, to allow for missing information in the parental genotypes. Three polymorphisms in the NRAMP1 gene were typed: a microsatellite (CA) repeat, a 4 bp deletion in the 3′ untranslated region and a single nucleotide change in intron 4. The single base change in intron 4 was significantly associated (p = 0.036) with tuberculosis. Our results therefore confirm, using a family-based approach on a newly studied population, the previously reported association between this polymorphism and tuberculosis in a population-based study of West Africans.

The sex chromosomes enable direct determination of haplotypes, and the analysis of 8 microsatellite markers from the FRAX region on Xq27-q28 contributes 7219 independent haplotypes from our study in Wessex. Allelic association increases with frequency of alleles, and is less for trinucleotide than dinucleotide repeats. The estimate of ε, the exponential decline of association with distance in kb, is 0.0023. The swept radius 1/ε estimates the distance at which disequilibrium falls to e−1 ≈ .37 of its initial value. The current study estimates the swept radius of association to be 433 kb, which is surprisingly close to estimates for SNPs, and suggests that a marker density of 1/100 kb should be powerful in regions such as FRAX. An explanation for these results is offered, and some speculations made about what will be found when SNPs are subjected to an equally intensive study in multiple regions.

Parametric linkage analysis of simultaneous mapping of the two disease loci of a qualitative trait governed by a two-locus model has been shown to provide greater power in detecting linkage than standard lod-score analysis that maps a single disease locus. Despite its great potential for power gains, two-locus parametric analysis has not been used routinely in disease gene mapping, due to the computational intensity of currently available methods and programs. In this paper, we propose a Markov chain Monte Carlo (MCMC) method for performing lod-score analysis of qualitative traits governed by two-locus models. This method obtains lod-score estimates that can be arbitrarily close to their corresponding exact values. The algorithm implementing this MCMC method is linear in the number of markers. This feature enables us to perform two-locus analysis mapping each trait to a set of markers, instead of just to a single marker. We analyzed an alcohol dependence dataset composed of 105 pedigrees with various sizes and various degrees of missingness in the observed marker and disease data. The estimates from our MCMC procedure match up well with the lod scores from exact analysis, but it took much less time for the MCMC procedure to obtain the results. We also performed a simulation study to investigate power gains with additional markers. Our results indicate that an additional marker on each map can provide a great deal more information for linkage measured in terms of the magnitude of lod scores.

When searching for trait loci along the genome, properly incorporating prior genomic information into the analysis will almost certainly increase the chance of success. Recently, we devised a method that utilizes such prior information in the mapping of trait genes for complex disorders (Vieland, 1998; Wang et al. 1999; Vieland et al. 2000). This method uses the posterior probability of linkage (PPL) based on the admixture model as a measure of linkage information. In this paper, we study the consistency of the PPL. It is shown that, as the number of pedigrees increases, the PPL converges in probability to 1 when there is linkage between the marker and a trait locus, and converges to 0 otherwise. This conclusion is shown to be true for general pedigrees and trait models, even when the likelihood functions are based on misspecified trait models. As part of the effort to prove this conclusion, it is shown that when there is no linkage, the maximum likelihood estimator of the recombination fraction in the admixture model is asymptotically 0.5, even when the admixture model misrepresents the true model.

The transmission/disequilibrium test (TDT) is a powerful method of locating disease genes. The TDT was originally proposed for use in studies of qualitative traits in families with both parents available. Recently, the TDT has been extended to studies of qualitative traits in sibships without parents available and in families with one parent available. It has also been extended for use in studies of quantitative traits in families with both parents available and in sibships with multiple offspring. In this paper, we first propose a new class of TDT-type tests for linkage in the presence of linkage disequilibrium for use in studies of families with both parents available. The TDT of Spielman et al. (1993) for qualitative traits and the TDT of Rabinowitz (1997) for quantitative traits are special cases of the new tests. Second, we propose a new class of TDT-type tests for linkage for use in studies of families with one parent available. Third, we study the validity and the power of the tests using simulations. Finally, we propose a method of combining data from different types of families. The combined test is valuable and allows researchers full use of the available data in detecting linkage between a marker locus and an unobservable quantitative trait locus. An important feature of the tests proposed in this paper is that no assumptions on the distribution of the quantitative traits are needed.

Spielman et al. (1993) popularized the transmission/disequilibrium test (TDT) to test for linkage between disease and marker loci that show a population association. Several authors have proposed extensions to the TDT for multi-allelic markers. Many of these approaches exhibit a ‘swamping’ effect in which a marker with a strong effect is not detected by a global test that includes many markers with no effect. To avoid this effect, Schaid (1996) proposed using the maximum of the bi-allelic TDT statistics computed for each allele versus all others combined. The maximal TDT statistic, however, no longer follows a chi-square distribution. Here, a refinement to Bonferroni's correction for multiple testing provided by Worsley (1982) based on maximal spanning trees is applied to calculate accurate upper bounds for the type I error and p-values for the maximal TDT. In addition, an accurate lower Bonferroni bound is applied to calculate power. This approach does not require any simulation-based analysis and is less conservative than the standard Bonferroni correction. The bounds are given for both the exact probability calculations and for those based on the normal approximation. The results are assessed through simulations.

It is well known that the TDT proposed by Spielman et al. (1993) is potentially anti-conservative if families with one missing parental genotype are included (Curtis & Sham, 1995). We now bring attention to another situation that could give rise to an inflated rate of false positive results. This occurs when families in which the affected offspring and both parents have the same heterozygous genotype are excluded. If the heterozygous genotype is denoted as AB, then it is clear that one parent must have transmitted allele A and the other allele B. The standard TDT procedure is to increment the counts for transmissions of both A and B by one. It may seem reasonable to disregard such trios because it is ambiguous which parent has transmitted which allele. Although the resulting test statistic would retain all the information concerning preferential transmission of alleles, it can be shown that referring it to a χ2 distribution would lead to an increased type I error rate (see Appendix A).