Genetic association mapping based on discordant sib pairs: The discordant-alleles test
Genetic association mapping based on discordant sib pairs: The discordant-alleles test
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DOI：
10.1086/301787
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发表时间：
1998-04-01
影响因子：
9.8
通讯作者：
Langefeld, CD
中科院分区：
文献类型：
--
作者：
Boehnke, M;Langefeld, CD
以家庭为基础的关联测试提供了测试疾病和遗传标记之间关联的机会。这种测试避免了人口分层产生的假阳性结果，因此相关性的证据可能被解释为联系或因果关系的证据。已经提出了几种方法，使用基于家庭的控制，包括单倍型相对风险，传播不平衡测试，和受影响的家庭为基础的控制。然而，由于这些方法需要受影响的个体及其父母的基因型，因此它们并不理想地适合于晚发型疾病的研究。在本文中，我们开发了几个家庭为基础的测试，使用不一致的同胞对（DSP），其中一个同胞是受疾病和其他同胞是不是。这些检验基于比较等位基因或基因型计数或检验等位基因或基因型表中的对称性的统计数据。我们描述了使用置换框架来评估这些统计数据的意义。这些基于DSP的测试提供了与基于父母-后代三重测试相同的一般优势，同时基本上适用于任何疾病;它们也可以针对关于遗传模型的特定假设进行定制。我们比较了我们的DSP为基础的测试的统计特性，通过计算机模拟和说明其使用与阿尔茨海默病和载脂蛋白E多态性的应用程序。我们的研究结果表明，不一致等位基因测试，比较DSP中不匹配等位基因的数量，是我们考虑的最强大的测试，对于广泛的疾病模型和标记类型。最后，我们讨论了遗传关联图DSP设计的优点和缺点。
Family-based tests of association provide the opportunity to test for an association between a disease and a genetic marker. Such tests avoid false-positive results produced by population stratification, so that evidence for association may be interpreted as evidence for linkage or causation. Several methods that use family-based controls have been proposed, including the haplotype relative risk, the transmission-disequilibrium test, and affected family-based controls. However, because these methods require genotypes on affected individuals and their parents, they are not ideally suited to the study of late-onset diseases. In this paper, we develop several family-based tests of association that use discordant sib pairs (DSPs) in which one sib is affected with a disease and the other sib is not. These tests are based on statistics that compare counts of alleles or genotypes or that test for symmetry in tables of alleles or genotypes. We describe the use of a permutation framework to assess the significance of these statistics. These DSP-based tests provide the same general advantages as parent-offspring trio-based tests, while being applicable to essentially any disease; they may also be tailored to particular hypotheses regarding the genetic model. We compare the statistical properties of our DSP-based tests by computer simulation and illustrate their use with an application to Alzheimer disease and the apolipoprotein E polymorphism. Our results suggest that the discordant-alleles test, which compares the numbers of nonmatching alleles in DSPs, is the most powerful of the tests we considered, for a wide class of disease models and marker types. Finally, we discuss advantages and disadvantages of the DSP design for genetic association mapping.