Identifying Susceptibility Genes Using Linkage and Linkage Disequilibrium Analysis in Large Pedigrees

Linkage and linkage disequilibrium tests are powerful tools for mapping complex disease genes. We investigated two approaches to identifying markers associated with disease. One method applied linkage analysis and then linkage disequilibrium tests to markers within linked regions. The other method looked for linkage disequilibrium with disease using all markers. Additionally, we investigated using Simes’ test to combine p‐values from linkage disequilibrium tests for nearby markers. We applied both approaches to all replicates of the Genetic Analysis Workshop 12 problem 2 isolated population data set. We reported results from the 25^th replicate as if it were a real problem and assessed the power of our methods using all replicates. Using all replicates, we found that testing all markers for linkage disequilibrium with disease was more powerful than identifying markers that were in linkage with disease and then testing markers within those regions for linkage disequilibrium with the implementations that we chose. Using Simes’ test to combine p‐values for linkage disequilibrium tests on correlated markers seemed to be of marginal value. © 2001 Wiley‐Liss, Inc.     

Parametric Linkage Analysis and Disequilibrium Methods to Identify Loci for Complex Disease

A two‐step process was used to find loci contributing to the qualitative disease phenotype in the Genetic Analysis Workshop (GAW) 12 simulated data. The first step used parametric linkage analysis with a limited number of dominant and recessive models to detect linkage to chromosomal regions. Subsequently, a subset of the simulated biallelic sequence polymorphisms was used for transmission/disequilibrium tests and to build haplotypes to fine map the disease‐predisposing polymorphism(s). A haplotype, strongly associated with the disease phenotype whose proximal end was within 39 base pairs of the functional allele for simulated major gene 6, was identified in the isolated population. © 2001 Wiley‐Liss, Inc.     

Linkage Disequilibrium Structure and Its Impact on the Localization of a Candidate Functional Mutation

We have used the unblinded MG1/Q1 Genetic Analysis Workshop 12 simulated data as a model system for investigating the use of linkage disequilibrium structure and simple genotype‐phenotype associations to identify candidate functional mutations within a gene of interest. Analysis of the pattern of pair‐wise linkage disequilibrium indicated three groups of single‐nucleotide polymorphisms for which the linkage disequilibrium was high between sites within a group, but lower between sites of different groups. Using linear regression to predict levels of the trait Q1 showed that the known functional site, 5782, was usually not the best genetic predictor of Q1, but sites belonging to the same group as 5782 (i.e., group 2) were always included in the prediction model. In 49 out of the 50 replicates, the functional site was not the best predictor of the trait. Finally, more detailed analyses demonstrate that the relationship between the adjusted R² for the marker in the prediction model and its disequilibrium with 5782 was linear with the intercept at the origin and terminating at the R² value for the known functional mutation when the disequilibrium is maximal. These data indicate that simple association studies will not identify the functional mutation, but rather will identify candidate functional mutations that are in very tight linkage disequilibrium with the functional mutation. © 2001 Wiley‐Liss, Inc.     

Test of Association for Quantitative Traits in General Pedigrees: The Quantitative Pedigree Disequilibrium Test

Many statistical methods have been proposed in recent years to test for genetic linkage and association between genetic markers and traits of interest through unrelated nuclear families. However, most of these methods are not valid tests of association in the presence of linkage when some of the nuclear families are related. As a result, related nuclear families in large pedigrees cannot be included in a single analysis to test for linkage disequilibrium. Recently, Martin et al. [Am J Hum Genet 67:146–54, 2000] proposed the pedigree disequilibrium test (PDT) to test for linkage and association in general pedigrees for qualitative traits. In this article, we develop a similar quantitative pedigree disequilibrium test (QPDT) to test for linkage and association in general pedigrees for quantitative traits. We apply both the PDT and the QPDT to analyze the sequence data from the seven candidate genes in the simulated data sets in the Genetic Analysis Workshop 12. © 2001 Wiley‐Liss, Inc.     

Analysis of Single Nucleotide Polymorphisms in Candidate Genes Using the Pedigree Disequilibrium Test

The pedigree disequilibrium test (PDT) has been proposed recently as a test for association in general pedigrees [Martin et al., Am J Hum Genet 67:146–54, 2000]. The Genetic Analysis Workshop (GAW) 12 simulated data, with many extended pedigrees, is an example the type of data to which the PDT is ideally suited. In replicate 42 from the general population the PDT correctly identifies candidate genes 1, 2, and 6 as containing single nucleotide polymorphisms (SNPs) that arc significantly associated with the disease. We also applied the truncated product method (TPM) [Zaykin et al., Genet Epidemiol, in press] to combine p‐values in overlapping windows across the genes. Our results show that the TPM is helpful in identifying significant SNPs as well as removing spurious false positives. Our results indicate that, using the PDT, functional disease‐associated SNPs can be successfully identified with a dense map of moderately polymorphic SNPs. © 2001 Wiley‐Liss, Inc.     

Exploiting Linkage Disequilibrium in Population Isolates

A comparison of haplotype frequencies between unrelated cases and controls from population isolates identifies a strong signal for the presence/absence of the discrete phenotype in an interval on chromosome 6 bounded by markers 34 and 35. We define a dissimilarity index, D, which is sensitive to differences in allele distributions and differences in the patterns of linkage disequilibrium between cases and controls. We describe two statistical methods to utilize D: a method appropriate for a single moderately sized sample and a sequential approach appropriate for multiple small independent samples. © 2001 Wiley‐Liss, Inc.     

Comparison of Novel and Existing Methods for Detection of Linkage Disequilibrium Using Parent‐Child Trios in the GAW12 Genetic Isolate Simulated Data

A novel method for joint detection of association caused by linkage disequilibrium (LD) and estimation of both recombination fraction and linkage disequilibrium parameters was compared to several existing implementations of the transmission/disequilibrium test (TDT) and modifications of the TDT in the simulated genetic isolate data from Genetic Analysis Workshop 12. The first completely genotyped trio of affected child and parents was selected from each family in each replicate so that the TDT tests are valid tests of linkage and association, rather than being only valid as tests for linkage. In general, power to detect LD using the genome‐wide scan markers was inadequate in the individual replicate samples, but the power was better when analyzing several SNP markers in candidate gene 1. © 2001 Wiley‐Liss, Inc.     

Haplotype Sharing Tests of Linkage Disequilibrium in a Hutterite Asthma Data Set

The Genetic Analysis Workshop 12 genome scan data set for “strict” asthma in a Hutterite population was analyzed using haplotype sharing analysis (HSA), which tests for differences in mean length of haplotype sharing around each marker for pairs of chromosomes in cases versus controls. The regions of chromosome 1 and 8 where evidence for linkage was observed in published analyses were negative by HSA. HSA yielded positive results on chromosomes 7, 12, 16, 18, and 21 (p = 0.003 on 21q). Although there are reports of support for linkage to asthma in some of these regions, it is not known whether any represent true positives. Further study is needed of the possible role of length‐based measures of linkage disequilibrium in recent population isolates. © 2001 Wiley‐Liss, Inc.     

Population Based Linkage Disequilibrium Mapping of QTL: An Application to Simulated Data in an Isolated Population

Despite successes in mapping and cloning genes involved in rare Mendelian diseases, genetic dissection of quantitative traits into single Mendelian factors still remains a challenging task. As the dense map of single nucleotide polymorphism (SNP) markers becomes available in the near future, linkage disequilibrium (LD) mapping will become one of major tools for mapping and identifying quantitative trait loci (QTL). In this report, we present a population‐based linkage disequilibrium mapping of QTL. This method unifies the analysis of mapping QTL in humans and in model organisms and can be used for randomly sampled individuals. The proposed method is applied to search for polymorphism sites within the candidate genes 2 and 6, which influence quantitative traits Q1 and Q2 or Q5, in a simulated data set in an isolated population. © 2001 Wiley‐Liss, Inc.     

Genetic association mapping under founder heterogeneity via weighted haplotype similarity analysis in candidate genes

Taking advantage of increasingly available high-density single nucleotide polymorphism (SNP) markers within genes and across genomes, more and more genetic association studies began to use multiple closely linked markers in candidate genes. A practical analytical challenge arising in such studies is the possibility that not all case chromosomes have inherited disease-causing mutations from a common ancestral chromosome (founder heterogeneity). To alleviate the problem, we propose a method that applies a clustering algorithm to haplotype similarity analysis. The method identifies a sequence of nested subsets of case chromosomes by a peeling procedure, where each subset is relatively homogeneous. The average similarity score estimated from each subset in the sequence is compared to that estimated in controls, and a raw (unadjusted for multiple comparisons) P value is obtained. The test for the association between the trait and the candidate gene is based on the minimum raw P value observed in the comparison sequence, with its significance level estimated by a permutation procedure. The method can be applied to both haplotype and genotype data. Simulation studies suggest that our method has the correct type I error rate, and is generally more powerful than existing methods of haplotype similarity analysis.     

精神分裂症患者中单胺氧化酶A和B多态性位点的连锁不平衡研究

目的 为研究单胺氧化酶与精神分裂症的关系。方法 采用聚合酶链式反应,对140例无血缘关系的高加索男性精神分裂症患和91例对照的两个X连锁的微卫星序列即单胺氧化酶A位点中的（AC）n重复序列和单胺氧化酶B位点的（TG）n等位基因进行了研究。结果 基因分布频率在病人组和对照组中未发现差异。但（AC）18（TG）23单倍体增多与精神分裂有关,相对危险度是4．05（95％CI1.15-14.26),精确概率P＝0．011,连锁不平衡系数在精神分裂症组是0．019;在对照组是－0．046。结论 单胺氧化酶A和B多态性位点的连锁不平衡与精神分裂症有关。     

Nonparametric Linkage Regression II: Identification of Influential Pedigrees in Tests for Linkage

We applied case‐deletion‐based diagnostics to the combined Caucasian genome scan data for asthma and IgE from the Collaborative Study on the Genetics of Asthma (CSGA) and German family studies in order to identify influential pedigrees in tests for linkage. These methods identified 12 pedigrees whose data appear not to fit the asthma linkage model and for whom alternative genetic and nongenetic explanations can be explored. The methods also identified four pedigrees for chromosome 1 and two pedigrees for chromosome 2 that provide strong evidence for linkage at their respective loci. Similarly, these methods helped identify four pedigrees that strongly influenced the linkage tests for IgE. From these data, we can construct an enriched subset of pedigrees to be used in further analysis for mapping region‐specific putative trait predisposing loci. © 2001 Wiley‐Liss, Inc.     

传递不平衡的对称性检验的适用性

目的 探讨父母传递的独立性条件对传递不平衡的对称性检验的影响。方法 把父亲的传递与母亲的传递联合进行考虑，利用联合传递的概率分布规律进行推导检验统计量的分布。结果 亲代传递的不独立性并不影响检验统计量的统计特性。结论 即使父母传递不独立时，对称性检验仍然适合检验连锁与连锁不平衡。     

Genome Scan for Linkage to Asthma Using a Linkage Disequilibrium‐lod Score Test

We report a genome‐wide linkage study of asthma on the German and Collaborative Study on the Genetics of Asthma (CSGA) data. Using a combined linkage and linkage disequilibrium test and the nonparametric linkage score, we identified 13 markers from the German data, 1 marker from the African American (CSGA) data, and 7 markers from the Caucasian (CSGA) data in which the p‐values ranged between 0.0001 and 0.0100. From our analysis and taking into account previous published linkage studies of asthma, we suggest that three regions in chromosome 5 (around D5S418, D5S644, and D5S422), one region in chromosome 6 (around three neighboring markers D6S1281, D6S291, and D6S1019), one region in chromosome 11 (around D11S2362), and two regions in chromosome 12 (around D12S351 and D12S324) especially merit further investigation. © 2001 Wiley‐Liss, Inc.     

Incorporating Age at Onset Information into the Transmission/Disequilibrium Test

In this paper, we proposed two approaches for incorporating the age at onset into the transmission/disequilibrium test (TDT). Trios (affected offspring and their parents) were extracted from the first four replicate data sets of the general population type. Focusing on chromosome 6 where MG6 and MG7 reside, we compared the usual TDT with the newly proposed tests in terms of gene localization. © 2001 Wiley‐Liss, Inc.     

Comparison of Likelihood Approaches for Combined Segregation and Linkage Analysis of a Complex Disease and a Candidate Gene Marker Under Different Ascertainment Schemes

We compared two joint likelihood approaches, with complete (L1) or without (L2) linkage disequilibrium, under different ascertainment schemes, for the genetic analysis of the disease trait and marker gene 1 in replicate 42. Joint likelihoods were computed without a correction for the selection scheme. For the different sampling schemes we have explored, our results suggest that L1 is a more powerful approach than L2 to detect major gene and covariatc effects as well as to identify accurately gene×covariate interaction effects in a common and complex disease such as the Genetic Analysis Workshop 12 MG6 simulated trait. © 2001 Wiley‐Liss, Inc.     

A general class of association tests for family-based data using weight functions

Based on the symmetry of transmitted/nontransmitted alleles from heterozygous parents under the null hypothesis of no association, the work proposed here establishes a general statistical framework for constructing association tests with data from nuclear families with multiple affected children. A class of association tests is proposed for both diallelic and multiallelic markers. The proposed test statistics reduce to the transmission disequilibrium test for trios, to T(su) by Martin et al. ([1997] Am. J. Hum. Genet. 61:439-448) for affected sib pairs, and to the pedigree disequilibrium test by Martin et al. ([2000] Am. J. Hum. Genet. 67:146-154); [2001] Am. J. Hum. Genet. 68:1065-1067) when using affected sibships only. The association test used in simulation and for real data (sitosterolemia) is the one which has the best overall power in detecting association. This association test is generally more powerful than the association tests proposed by Martin et al. ([2000] Am. J. Hum. Genet. 67:146-154); [2001] Am. J. Hum. Genet. 68:1065-1067) when using only affected sibships. For the sitosterolemia data set, the association test has its most significant result (P-value=0.0012) for the marker locus on the same bacterial artificial chromosome as the disease locus.     

A general method for linkage disequilibrium correction for multipoint linkage and association

Lately, many different methods of linkage, association or joint analysis for family data have been invented and refined. Common to most of those is that they require a map of markers that are in linkage equilibrium. However, at the present day, high-density single nucleotide polymorphisms (SNPs) maps are both more inexpensive to create and they have lower genotyping error. When marker data is incomplete, the crucial and computationally most demanding moment in the analysis is to calculate the inheritance distribution at a certain position on the chromosome. Recently, different ways of adjusting traditional methods of linkage analysis to denser maps of SNPs in linkage disequilibrium (LD) have been proposed. We describe a hidden Markov model which generalizes the Lander-Green algorithm. It combines Markov chain for inheritance vectors with a Markov chain modelling founder haplotypes and in this way takes account for LD between SNPs. It can be applied to association, linkage or combined association and linkage analysis, general phenotypes and arbitrary score functions. We also define a joint likelihood for linkage and association that extends an idea of Kong and Cox (1997 Am. J. Hum. Genet. 61: 1179-1188) for pure linkage analysis.     

Genotype prediction using a dense map of SNPs

The International Haplotype Mapping Project (HapMap) aims to characterize the distribution and extent of linkage disequilibrium (LD) throughout the human genome, thereby facilitating genome-wide association analysis and the search for the genetic determinants of complex diseases. Implicit in the rationale behind the project is the expectation that hidden (unobserved) disease-causing variants will be in significant LD with surrounding typed markers and will thus be amenable to detection using association-based mapping approaches. In order to investigate the validity of this assumption, we examined more than 5,000 SNPs across a 10-MB region of chromosome 20 in a sample of 96 unrelated African-American and 96 unrelated Caucasian individuals. We treated observed loci as surrogates for hidden SNPs by pretending that individuals' genotypes were unknown. We then attempted to predict these genotypes at the surrogate hidden SNP by using information about LD in the region and genotypes at surrounding observed loci. Our method is based on finding the most likely genotype for each individual, given all possible haplotype pairs consistent with observed genotypes for that individual at surrounding loci, and given the frequencies of those haplotypes in an independent sample. Our method performs extremely well in predicting genotypes in areas of high LD. Furthermore, in areas of low LD, our method results in substantial gains in predictive accuracy as compared to pair-wise strategies. These results suggest that pair-wise tests of disease-marker association may be inferior to multipoint methods, which take advantage of the information contained within multi-locus haplotypes.     

PedBLIMP: Extending Linear Predictors to Impute Genotypes in Pedigrees

Recently, Wen and Stephens (Wen and Stephens [2010] Ann Appl Stat 4(3):1158–1182) proposed a linear predictor, called BLIMP, that uses conditional multivariate normal moments to impute genotypes with accuracy similar to current state‐of‐the‐art methods. One novelty is that it regularized the estimated covariance matrix based on a model from population genetics. We extended multivariate moments to impute genotypes in pedigrees. Our proposed method, PedBLIMP, utilizes both the linkage‐disequilibrium (LD) information estimated from external panel data and the pedigree structure or identity‐by‐descent (IBD) information. The proposed method was evaluated on a pedigree design where some individuals were genotyped with dense markers and the rest with sparse markers. We found that incorporating the pedigree/IBD information can improve imputation accuracy compared to BLIMP. Because rare variants usually have low LD with other single‐nucleotide polymorphisms (SNPs), incorporating pedigree/IBD information largely improved imputation accuracy for rare variants. We also compared PedBLIMP with IMPUTE2 and GIGI. Results show that when sparse markers are in a certain density range, our method can outperform both IMPUTE2 and GIGI.