Evaluation of screening strategies to detect an oligogenic disease

Using data simulated to reflect an oligogenic disease, we evaluated screening strategies based on lod-score and weighted pairwise correlation (WPC) analysis with respect to their ability to efficiently identify regions near disease loci. Lod-score analysis was done twice, once assuming a near-recessive mode of inheritance with a high penetrance and again assuming a semidominant mode of inheritance with lower penetrance. Under the near-recessive model, no disease loci were correctly identified, while there was one false positive result. Under the semidominant model, D1G31 was correctly identified, and there were two false positive results. Due to the lack of highly informative families and possible sensitivity to parameter misspecification, this poor performance was not unexpected. WPC, on the other hand, is assumption-free and thus potentially more powerful than a misspecified parametric model, but almost certainly less powerful than a well-specified parametric model. Using WPC modified to handle binary phenotypes with no age-of-onset, we found results closely resembling those under the semidominant model, although no markers near disease loci exceeded the theoretical critical value for WPC. © 1995 Wiley-Liss, Inc.     

The “possible triangle” test for extreme discordant sib pairs

For the analysis of quantitative traits in nuclear families, extreme discordant sib pairs proved to be more powerful than unselected sib pairs. Here, we present a test that makes use of selected pairs and, in addition, restricts the parameters of the identical-by-descent distribution analogously to the “possible triangle” for affected sib pairs. In the Problem 2A data, extreme discordant sib pairs are selected. The analysis allowed the detection of most simulated major genes. © 1997 Wiley- Liss, Inc.     

Strategy for mapping minor histocompatibility genes involved in graft-versus-host disease: A novel application of discordant sib pair methodology

We introduce a novel application for linkage analysis: using bone marrow donor-recipient sib pairs to search for genes influential in graft-versus-host disease (GVHD), a major cause of morbidity and mortality following allogeneic bone marrow transplantation. In particular, we show that transplant sib pairs in which the recipient developed severe GVHD can be used to map genes in the same way as traditional discordant (affected/unaffected) sib pairs (DSPs). For a plausible GVHD model, we demonstrate that the transplant/discordant sib pair analog of the “possible triangle test” [Holmans (1993) Am J Hum Genet 52:362–374] has similar power to that of the simpler “restricted test” proposed by Risch [(1990b) Am J Hum Genet 46:229–241; (1992) Am J Hum Genet 51:673–675]. Moreover, we show that the restricted test has superior power in much of the DSP possible triangle and significantly inferior power in only a small region. Thus, we conclude that the restricted test is preferable for localizing genes with transplant/discordant sib pairs. Finally, we examine the effects of heterogeneity on the power to detect GVHD loci and demonstrate the gain in efficiency by dividing the sample into genetically more homogeneous subgroups. Genet. Epidemiol. 15:595–607,1998. © 1998 Wiley-Liss, Inc.     

Regional inference with averaged P values increases the power to detect linkage

Controversy exists with respect to the choice of an appropriate critical value when testing for linkage in a genomic screen. A number of critical values have been proposed for single‐locus and multi‐locus linkage analyses. In this study, criteria based on multiple single‐locus analyses (i.e., regional test criteria) are evaluated using simulation methods for three different map densities. Tests based on single loci, multiple consecutive single loci, and moving averages of consecutive single loci are considered. Appropriate critical values are determined based on results from simulations under the null hypothesis of no linkage. The power of each "regional test " was compared to the power of a single‐locus test. Results suggest that the best power was found when averaging P values over an interval size of 9–15 cM, and that testing the average of P values from two consecutive loci is superior to testing each single locus separately. The increase in power ranged from 7– 29% over the simulations considered. Genet. Epidemiol. 17:157–164, 1999. © 1999 Wiley‐Liss, Inc.     

Homozygous parent affected sib pair method for detecting disease predisposing variants: Application to insulin dependent diabetes mellitus

For complex genetic diseases involving incomplete penetrance, genetic heterogeneity, and multiple disease genes, it is often difficult to determine the molecular variant (s) responsible for the disease pathogenesis. Linkage and association studies may help identify genetic regions and molecular variants suspected of being directly responsible for disease predisposition or protection, but, especially for complex diseases, they are less useful for determining when a predisposing molecular variant has been identified. In this paper, we expand upon the simple concept that if a genetic factor predisposing to disease has been fully identified, then a parent homozygous for this factor should transmit either of his/her copies at random to any affected children. Closely linked markers are used to determine identity by descent values in affected sib pairs from a parent homozygous for a putative disease predisposing factor. The expected deviation of haplotype sharing from 50%, when not all haplotypes carrying this factor are in fact equally predisposing, has been algebraically determined for a single locus general disease model. Equations to determine expected sharing for multiple disease alleles or multiple disease locus models have been formulated. The recessive case is in practice limiting and therefore can be used to estimate the maximum proportion of putative susceptibility haplotypes which are in fact predisposing to disease when the mode of inheritance of a disease is unknown. This method has been applied to 27 DR3/DR3 parents and 50 DR4/DR4 parents who have at least 2 children affected with insulin dependent diabetes mellitus (IDDM). The transmission of both DR3 and DR4 haplotypes is statistically different from 50% (P < 0.05 and P < 0.001, respectively). An upper estimate for the proportion of DR3 haplotypes associated with a high IDDM susceptibility is 49%, and for DR4 haplotypes 38%. Our results show that the joint presence of non-Asp at DQP position 57 and Arg at DQa position 52, which has been proposed as a strong IDDM predisposing factor, is insufficient to explain the HLA component of IDDM predisposition. © 1993 Wiley-Liss, Inc.     

Analysis of complex oligogenic disease

Our analysis of GAW10 problem 2 data set consisted of linear regression analysis followed by linkage analysis. The linear regression analysis allowed some exploration of the relationships between the quantitative variables. Furthermore, it isolated some of the components of certain quantitative variables that were not due to a major locus and facilitated the linkage analysis that followed. For the linkage analysis, we used MAPMAKER/SIBS and the SIBPAL program from S.A.G.E. We found linkage of Q4 to chromosome 8. Analysis using the residuals of Q1 and Q3 showed linkage to chromosomes 5 and 4, respectively. © 1997 Wiley-Liss, Inc.     

Sequential sib-pair and association studies to detect genes in quantitative traits

We applied sib-pair and association methods to a GAW data set of nuclear families with quantitative traits. Our approaches included 1) preliminary statistical studies including correlations and linear regressions, 2) sib-pair methods, and 3) association studies. We used a single data set to screen for linkage and association and, subsequently, additional data sets to confirm the preliminary results. Using this sequential approach, sib-pair analysis provided evidence for the genes influencing Q1, Q2, and Q4. We correctly predicted MG1 for Q1, MG2 for Q2, and MG4 for Q4. We did not find any false positives using this approach. Association studies identified chromosomes 8 and 9 to be associated with Q4; however these are assumed to be false positives as no associations were modeled into the data. © 1997 Wiley-Liss, Inc.     

原发性高血压危险因素同胞对病例对照研究

目的 探讨在相近的原发性高血压(EH)发病的遗传背景下,环境因素对原发性高血压发生的影响.方法 从57户高血压家系中,选取60个年龄相近、性别相同的同胞对,其中一人为原发性高血压患者,另一人为血压正常者,进行1:1配对病例对照研究;应用多因素条件Logistic回归分析筛选原发性高血压的易患危险因素,数据分析采用SPSS 12.0统计软件.结果 单因素分析结果显示,吸烟、饮酒、血糖、甘油三酯(TG)、胆固醇(CHOL)、高密度脂蛋白(HDL)、低密度脂蛋白(LDL)、血钾、血纳、血钙在对照组与病例组之间差异均无统计学意义(P＞0.05),仅体质指数(BMI)在对照组与病例组之间差异有统计学意义(P＜0.05);多因素条件Logistic回归分析结果显示,BMI可能是原发性高血压的易患危险因素( OR =29.330,95% CI =2.594 ～331.613).结论 在相近的遗传条件下,BMI可能是原发性高血压的易患危险因素.     

Two-stage global search designs for linkage analysis using pairs of affected relatives

We investigate the two-stage procedure proposed by Elston [(1992) Proceedings of the XVIth International Biometric Conference, Hamilton, New Zealand, December 7–11, 1992, pp 39–51, and (1994) “Genetic Approaches to Mental Disorders.” Washington, DC: American Psychiatric Press, pp 3–21] for performing a global search of the genome to locate disease genes by linkage analysis using affected relative pairs. The optimal design depends on the type of pairs studied, the effect of the disease locus, the relative costs of recruiting affected persons and typing markers, how informative the markers are, and the amount of genetic heterogeneity. It is specified by the initial number of markers to use, the number of affected relative pairs to study, the initial significance level α^* to use at the first stage, and the number of flanking markers to use at the second stage around markers significant at the first stage. Asymptotically, the optimal design does not depend separately on either the desired final significance level or power, but rather on a function of the two. Both as the effect of the disease locus increases and as the relative cost of recruiting a subject increases, the optimal number of initial markers increases and the optimal number of pairs decreases. The expected cost of the study decreases as the effect of the disease locus increases, but increases as the relative cost of recruiting a subject increases. The optimal initial number of markers decreases but the number of pairs increases when there is genetic heterogeneity present; conversely, the optimal initial number of markers increases when markers are less than fully informative. Compared to a one-stage procedure, a two-stage procedure typically halves the cost of a study. © 1996 Wiley-Liss, Inc.     

A multivariate approach to affected-sib-pair analysis using highly dense molecular maps

A multivariate approach to affected-sib-pair analyses was performed to localize disease-susceptibility genes with a minimum number of type I errors (false positives). Using 1,155 independent affected sib pairs extracted from Problem 2A of the GAW10 data set, we were able to localize major genes (MG) 1 and 2. Using 30% of the affected-sib-pair sample (N = 337) we were able to localize MG1. False positives were not detected in either of these samples. © 1997 Wiley-Liss, Inc.     

Affected-sib-pair test for linkage based on constraints for identical-by-descent distributions corresponding to disease models with imprinting

Holmans' possible triangle test for affected sib pairs has proven to be a powerful tool for linkage analysis. This test is a likelihood-ratio test for which maximization is restricted to the set of possible sharing probabilities. Here, we extend the possible triangle test to take into account genomic imprinting, which is also known as parent-of-origin effect. While the classical test without imprinting looks at whether affected sib pairs share 0, 1, or 2 alleles identical-by-descent, the likelihood-ratio test allowing for imprinting further distinguishes whether the sharing of exactly one allele is through the father or mother. Thus, if the disease gene is indeed subject to imprinting, the extended test presented here can take into account that affecteds will have inherited the mutant allele preferentially from one particular parent. We calculate the sharing probabilities at a marker locus linked to a disease susceptibility locus. Using our formulation, the constraints on these probabilities given by Dudoit and Speed ([1999] Statistics in Genetics; New York: Springer) can easily be verified. Next, we derive the asymptotic distribution of the restricted likelihood-ratio test statistic under the null hypothesis of no linkage, and give LOD-score criteria for various test sizes. We show, for various disease models, that the test allowing for imprinting has significantly higher power to detect linkage if imprinting is indeed present, at the cost of only a small reduction in power in case of no imprinting. Altogether, unlike many methods currently available, our novel model-free sib-pair test adequately models the epigenetic parent-of-origin effect, and will hopefully prove to be a useful tool for the genetic mapping of complex traits.     

Analysis of quantitative risk factors for a common oligogenic disease

All three simulated loci influencing the quantitative variables Q1, Q2, and Q3 were successfully mapped by using a strategy of covariate adjustment and segregation analysis, coupled with association analyses and lod-score analyses. © 1995 Wiley-Liss, Inc.     

Power comparison of generalizations of the mean test for affected sib pairs in case of incompletely informative markers

Previously applied test statistics for affected sib pairs (ASP) have been criticized for not fully exploiting the power of a given sample, because they do not account for incomplete informativity of an affected sib pair. To circumvent this problem, recently a new test had been proposed which weighs families proportional to their marker informativity. Here, the behavior of this new test is explored under scenarios considered to be relevant in the context of complex diseases. The results show that the new test does not represent an improvement. The asymptotic version of the new test tends to be markedly anticonservative even for larger sample sizes, whereas the permutation procedure proposed for the simulation of exact P values is at least questionable. Most importantly, the new test is less powerful than its competitors, especially in case of low marker informativity it was designed for.     

Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs

Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for theta, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (theta = (1/2)). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model.     

Identification of susceptibility loci contributing to a complex disease using conventional segregation,linkage, and association methods

We set out to apply conventional analytic methods to a GAW data set of nuclear families with an oligogenic disease that has a population prevalence of 0.023. We chose methods generally applied to disorders with at least one major gene. Our approaches included: (1) complex segregation analysis under two models of ascertainment, (2) linkage analysis assuming either a single-locus trait with possible genetic heterogeneity or a two-locus trait, and (3) allelic association studies using both a case/control approach and the haplotype relative risk (HRR) test. The association study was the only analysis of the three that provided evidence for genes playing a role in the etiology of this disorder. ©1995 Wiley-Liss, Inc.     

Combining extremely concordant sibpairs with extremely discordant sibpairs provides a cost effective way to linkage analysis of quantitative trait loci

Extremely discordant (ED) sibpairs have been shown to be very powerful for linkage analysis of human quantitative traits [Risch and Zhang (1995) Science 268:1584–1589]. In many cases, the extremely concordant (EC) sibpairs collected in the process of screening for ED sibpairs carry valuable information for linkage. Therefore, it seems justifiable to investigate the advantages of genotyping and to include them with the ED sibpairs for linkage analysis. Herein we explore the distributions of EC as well as ED sibpairs under various genetic models and provide a basis for combining both types of sibpairs. A simple statistic testing means of genes shared identical by descent (IBD) is applied to combine both types of EC sibpairs (high-high and low-low) with the ED pairs. We show that when a decent number of EC pairs is added to the ED sample for analysis, the power is much enhanced, making it especially desirable when the number of available ED pairs is small. We show at the same time that combining EC pairs with ED pairs is more cost effective than pursuing ED sibpairs alone. © 1996 Wiley-Liss, Inc.     

Improvement of the power to detect complex disease genes by regional inference procedures

Theoretical studies and simulations suggest that “true” linkage peaks are longer than “false” peaks of the same significance level. Our goal for this study was to improve the power of linkage detection by using a regional criterion for linkage; that is, requiring more than one p-value in a given region to pass a threshold. We tested this method by determining the power and type I error for finding the underlying loci on chromosomes 5 and 8 that contribute to the variability of Q1 (after adjusting Q1 for covariates). We used the Haseman-Elston sib-pair statistic to test for linkage of all 367 markers to the adjusted Q1 trait in 100 replicates. We compared the regional inference procedure to that of the Lander and Kruglyak (LK) criteria for significant and suggestive linkage. For example, the power to detect the chromosome 5 locus was 48% for the LK criterion for significant linkage (p ≤ 0.0001) and 63% when we required two p-values out of five consecutive ones to be ≤ 0.001. The type I error was not more than 5% for either method (2% for the LK and 5% for our criterion). This suggests that using a criterion based on length may improve the power of linkage detection for complex traits. © 1997 Wiley-Liss, Inc.     

Power of multipoint identity-by-descent methods to detect linkage using variance component models.

Multipoint linkage analysis gives increased power over single-point analysis to detect linkage for quantitative trait loci (QTL). Besides increased power, the use of multipoint methods makes it possible to estimate not only the location but also the magnitude of the QTL. Currently, two methods are commonly used for calculating multipoint identity-by-descent (IBD) allele-sharing estimates for pedigrees of moderate sizes. The method of Fulker et al. is based on multiple regression of the IBD status at the observed marker loci, whereas the hidden Markov model approach of Kruglyak and Lander estimates the true inheritance distribution at each chromosomal location. Simulation studies of full sibs and nuclear pedigrees show that the two methods for estimating multipoint IBD scores may give very different estimates for a pair of relatives and that a small increase in power to detect linkage can be obtained by using the hidden Markov model compared with the regression method.     

Analytic strategies to detect linkage to a common disorder with genetically determined age of onset: Diabetes mellitus in Pima Indians

Segregation analysis suggests that the high prevalence of non-insulin-dependent diabetes mellitus in Pima Indians may be partially due to a single locus with a major effect on age of onset. A simulation study was conducted to evaluate the power of various age-adjustment strategies in linkage analysis to detect this putative gene in 1,862 sib-pairs from 264 potentially informative nuclear families. Simulations were performed at a recombination fraction (θ) of 0.05 for values of polymorphism information content (PIC) ranging from 0.38 to 1.00. Under the codominant age-of-onset model supported by segregation analysis, power to detect linkage (at P < 0.0001) at PIC = 1.00 was 75% for the Haseman-Elston (HE) sib-pair test and 63% for the affected sib-pair test (ASP) with no age adjustment. Substantial improvements in power were possible for the HE test by defining the trait as a survival analysis "residual" (power = 91%) and for the ASP test by use of an age-of-onset threshold above which individuals are not included in the analysis (power = 90%, for age of onset < 45 yrs). The parametric method of linkage analysis was most powerful, as long as both the analysis model and the simulation model involved a genetic effect on age of onset, regardless of whether dominance at the trait locus was misspecified. Methods of age adjustment based on the probability of eventually becoming affected only improved power when the genetic effect was on susceptibility rather than age of onset. The method of age adjustment in linkage analysis may depend on whether one anticipates a genetic effect primarily on age of onset or on ultimate susceptibility. Genet. Epidemiol. 15:299–315, 1998. © 1998 Wiley-Liss, Inc. This article is a US Government work and, as such, is in the public domain in the United States of America.     

Linkage analysis of a complex disease: Application to familial Alzheimer's disease

Evidence for linkage of the Alzheimer's gene to markers on chromosomes 19 and 21 was assessed using single-locus and two-locus models of inheritance. Families were divided into groups determined by their average age at onset. The youngest group produced higher lod scores for markers on chromosome 21 while an older group showed evidence for linkage to markers on chromosome 19. Two-locus models of disease were used to analyze the youngest group for linkage to pairs of markers on chromosome 21 and an older group with markers on chromosome 19. © 1993 Wiley-Liss, Inc.