Use of linkage disequilibrium data in prenatal diagnosis of cystic fibrosis

Summary The authors report a case of 11;17 translocation associated with recurrent spontaneous abortions, and request contact with colleagues who have observed similar cases.     

Use of linkage disequilibrium data in prenatal diagnosis of cystic fibrosis

Summary Parents at risk of bearing a child with cystic fibrosis, and who have no living affected child, often use prenatal diagnosis based on microvillar enzyme assay in second-trimester amniotic fluid samples. If enzyme levels are abnormal and the pregnancy is terminated, it is possible in principle to use the fetal tissues to establish the phase relationship of linked DNA markers for a subsequent first-trimester prenatal diagnosis. However, the probability of a fetus being affected after an abnormal microvillar enzyme test may be no greater than 80%. The strong linkage disequilibrium between haplotypes at the D7S23 locus and the cystic fibrosis gene may be used to increase this probability. If fetal tissues are homozygous for the 6.6-kb band defined by pKM.19 and PstI and also homozygous for the 2.1-kb band with pXV-2c and TaqI, the chance of being affected increases from 80% to between 95% and 97%. We regard this as being sufficiently certain for use in phase determination.     

Patterns of polymorphism and linkage disequilibrium for cystic fibrosis

Four polymorphic markers that map within 80 kb of an HTF island which is genetically very close to the cystic fibrosis locus have been identified. We have analyzed the linkage disequilibrium between each of these markers and the cystic fibrosis mutation in 89 families from four European countries, Denmark, Finland, Spain, and Great Britain. Strong linkage disequilibrium between three polymorphic sites and cystic fibrosis was observed. The markers on the J3.11 (D7S8) side of the HTF island show stronger disequilibrium than those on the met side. Linkage disequilibrium between markers and disease alters the probability that a person of a given haplotype is a carrier in some populations and helps to identify regions of a sequence that are most likely to contain the cystic fibrosis mutation.     

Further linkage data on cystic fibrosis: The utah study

We reported earlier complete linkage between cystic fibrosis and an RFLP of the met proto-oncogene revealed by the probe pmetH. Another clone, pmetD, detects another polymorphism with the TaqI restriction enzyme. Further linkage studies, now involving 22 families, have confirmed the tight linkage of cystic fibrosis to the MET and D7S8 loci. Significant allelic association was found between CF and allelic series defined by the pmetH probe.     

High-resolution joint linkage disequilibrium and linkage mapping of quantitative trait loci based on sibship data

This paper proposes variance component models for high resolution joint linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) based on sibship data; this can include population data if independent individuals are treated as single sibships. One application of these models is late onset complex disease gene mapping, when parental data are not available. The models simultaneously incorporate both LD and linkage information. The LD information is contained in mean coefficients of sibship data. The linkage information is contained in the variance-covariance matrices of trait values for sibships with at least two siblings. We derive formulas for calculating the probability of sharing two trait alleles identical by descent (IBD) for sibpairs in interval mapping of QTL; this is the coefficient of dominant variance of the trait covariance of sibpairs on major QTL. To investigate the performance of the formulas, we calculate the numerical values via the formulas and get satisfactory approximations. We compare the power and sample sizes for both LD and linkage mapping. By simulation and theoretical analysis, we compare the results with those of Fulker and Abecasis "AbAw" approach. It is well known that the resolution of linkage analysis can be low for complex disease gene mapping. LD mapping, on the other hand, can increase mapping precision and is useful in high resolution mapping. Linkage analysis is less sensitive to population subdivisions and admixtures. The level of LD is sensitive to population stratification which may easily lead to spurious association. Performing a joint analysis of LD and linkage mapping can help to overcome the limits of both approaches. Moreover, the advantages of the two complementary strategies can be utilized maximally. In practice, linkage analysis may be performed using pedigree data to identify suggestive linkage between markers and trait loci based on a sparse marker map. In the presence of linkage, joint LD and linkage mapping can be carried out to do fine gene mapping based on a dense genetic map using both pedigree and population data. Population and pedigree data of any type can be combined to perform a joint analysis of high resolution LD and linkage mapping of QTL by generalizing the method.     

Prenatal diagnosis and linkage disequilibrium with cystic fibrosis for markers surrounding D7S8

Summary Three polymorphic DNA markers surrounding the D7S8 locus were tested for their usefulness in the diagnosis of cystic fibrosis (CF) by linkage analysis. The markers correspond to the loci D7S424 and D7S426. These polymorphisms were studied by centers in the U.S., the United Kingdom, the Netherlands, and Italy, using samples from populations throughout Europe and North America. The additional information provided by these probes increased the heterogeneity of the region from 50% to 58% and was essential for a completely informative diagnosis in one family. A very high degree of linkage disequilibrium was found between these markers, which span a distance of approximately 250kb. In addition, linkage disequilibrium with CF was noted. Significant heterogeneity of linkage disequilibrium was found among the populations, both for the marker-marker pairs and between the markers and CF.     

Disentangling linkage disequilibrium and linkage from dense single-nucleotide polymorphism trio data

Parent-offspring trios are widely collected for disease gene-mapping studies and are being extensively genotyped as part of the International HapMap Project. With dense maps of markers on trios, the effects of LD and linkage can be separated, allowing estimation of recombination rates in a model-free setting. Here we define a model-free multipoint method on the basis of dense sequence polymorphism data from parent-offspring trios to estimate intermarker recombination rates. We use simulations to show that this method has up to 92% power to detect recombination hotspots of intensity 25 times background over a region of size 10 kb typed at density 1 marker per 2.5 kb and almost 100% power to detect large hotspots of intensity >125 times background over regions of size 10 kb typed with just 1 marker per 5 kb (alpha = 0.05). We found strong agreement at megabase scales between estimates from our method applied to HapMap trio data and estimates from the genetic map. At finer scales, using Centre d'Etude du Polymorphisme Humain (CEPH) pedigree data across a 10-Mb region of chromosome 20, a comparison of population recombination rate estimates obtained from our method with estimates obtained using a coalescent-based approximate-likelihood method implemented in PHASE 2.0 shows detection of the same coldspots and most hotspots: The Spearman rank correlation between the estimates from our method and those from PHASE is 0.58 (p < 2.2(-16)).     

Haplotype-based linkage disequilibrium mapping via direct data mining

MOTIVATION: With the availability of large-scale, high-density single-nucleotide polymorphism markers and information on haplotype structures and frequencies, a great challenge is how to take advantage of haplotype information in the association mapping of complex diseases in case-control studies. RESULTS: We present a novel approach for association mapping based on directly mining haplotypes (i.e. phased genotype pairs) produced from case-control data or case-parent data via a density-based clustering algorithm, which can be applied to whole-genome screens as well as candidate-gene studies in small genomic regions. The method directly explores the sharing of haplotype segments in affected individuals that are rarely present in normal individuals. The measure of sharing between two haplotypes is defined by a new similarity metric that combines the length of the shared segments and the number of common alleles around any marker position of the haplotypes, which is robust against recent mutations/genotype errors and recombination events. The effectiveness of the approach is demonstrated by using both simulated datasets and real datasets. The results show that the algorithm is accurate for different population models and for different disease models, even for genes with small effects, and it outperforms some recently developed methods.     

Haplotype distribution of and linkage disequilibrium between four polymorphic markers near the CFTR locus in Brazilian cystic fibrosis patients

To contribute to a better understanding of the origin and distribution of CFTR mutations in the Brazilian population, we have investigated the linkage between four polymorphic markers (XV2c, KM19, GATT, and TUB9) within or near the CFTR locus. The distribution of alleles for each polymorphism for both parental and cystic fibrosis (CF) chromosomes from Rio de Janeiro CF families were ascertained using a maximum-likelihood method. This same method was applied to study the distribution of the haplotypes defined by these markers. There was no significant association between the XV2c and KM19 loci on the parental and CF chromosomes. On the other hand, a strong association between GATT and TUB9 loci was observed on both CF and parental chromosomes, and striking linkage disequilibrium between the GATT-TUB9 pair and deltaF508 was observed (chi2 = 26.48, p < 0.0001). Remarkable linkage disequilibrium between the GATT-TUB9 marker pair and non-deltaF508 was also found (chi2 = 17.05, p < 0.0001). Our finding of a linkage disequilibrium between GATT-TUB9 and the CFTR locus could suggest that gene flow between different ethnic groups, mainly sub-Saharan and Mediterranean populations, with Brazilian populations could have resulted in some CF mutations originating on chromosomes that carried the GATT-TUB9 marker haplotype 7-2 (OR = 1.34 < 2.83 < 6.00; p = 0.0066).     

Linkage disequilibrium, cystic fibrosis, and genetic counseling.

Strong linkage disequilibrium occurs between the cystic fibrosis (CF) locus and polymorphisms detected with the DNA probes XV-2c and KM-19. In a North American population, 86% of CF chromosomes occur with a haplotype which occurs on only 14% of normal chromosomes. An individual homozygous for the highest-risk haplotype has an 81-fold greater probability of carrying a CF allele than does an individual homozygous for the lowest-risk haplotype. The linkage-disequilibrium data can be used for prenatal diagnosis and genetic counseling in CF families. The data are useful in 1-in-4-risk pregnancies when DNA is not available from the propositus and in counseling close relatives of CF families. Serious problems arise with some pregnancies which remain at intermediate risks after analysis, and families are left with difficult decisions. It is not clear that genetic testing for couples at less than 1-in-4 risk is cost-effective or standard care, but use of linkage-disequilibrium data will provide more accurate risk probabilities in a substantial proportion of cases if such testing is carried out. Our results emphasize the need for a specific biological or molecular carrier test. This experience in using linkage-disequilibrium and linkage data in combination for genetic counseling provides a model system for the diagnosis of other disorders.     

Molecular data on cystic fibrosis in Bulgaria

Summary A group of 42 cystic fibrosis (CF) patients and 80 heterozygote carriers was analysed for determining the prevalent CF haplotypes and the frequency of ΔF508. The “high-risk” haplotype B (XV2c-KM19/1 2) was found in 66% of CF chromosomes. The prevalent normal haplotypes were A (1 1) and B (2 1). The deletion was detected in 54 CF chromosomes (56%), homozygotes constituting 35% of all CF patients. In 88% of cases the mutation was linked to haplotype B, and in 12% to haplotype D (2 2). Chromosomes that did not have ΔF508 were found to be evenly distributed among all four XV2c-KM19 haplotypes. The use of restriction fragment length polymorphisms and direct detection of the mutation makes 94% of CF families fully informative for prenatal analysis.     

Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data

A multi-locus QTL mapping method is presented, which combines linkage and linkage disequilibrium (LD) information and uses multitrait data. The method assumed a putative QTL at the midpoint of each marker bracket. Whether the putative QTL had an effect or not was sampled using Markov chain Monte Carlo (MCMC) methods. The method was tested in dairy cattle data on chromosome 14 where the DGAT1 gene was known to be segregating. The DGAT1 gene was mapped to a region of 0.04 cM, and the effects of the gene were accurately estimated. The fitting of multiple QTL gave a much sharper indication of the QTL position than a single QTL model using multitrait data, probably because the multi-locus QTL mapping reduced the carry over effect of the large DGAT1 gene to adjacent putative QTL positions. This suggests that the method could detect secondary QTL that would, in single point analyses, remain hidden under the broad peak of the dominant QTL. However, no indications for a second QTL affecting dairy traits were found on chromosome 14.     

Linkage detection adaptive to linkage disequilibrium: the disequilibrium maximum-likelihood-binomial test for affected-sibship data

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.     

JLIN: A java based linkage disequilibrium plotter

Background  

A great deal of effort and expense are being expended internationally in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Techniques such as Linkage Disequilibrium mapping are being increasingly used to examine and compare markers across increasingly large datasets. Visualisation techniques are becoming essential to analyse the ever-growing volume of data and results available with any given analysis.