Linkage analysis of a complex disease through use of admixed populations
Linkage analysis of a complex disease through use of admixed populations
复制标题
DOI：
10.1086/421329
复制
发表时间：
2004-06-01
影响因子：
9.8
通讯作者：
Elston, RC
中科院分区：
文献类型：
--
作者：
Zhu, XF;Cooper, RS;Elston, RC
最近由遗传不同的群体混合引起的连锁不平衡可能有助于绘制复杂疾病的基因图谱。 McKeigue 提出了一种以亲本混合为条件来检测连锁的方法。我们表明，该方法仅在特定假设下测试连锁，例如亲代中的相等混合和单代中发生的混合。实际上，这些假设不太可能适用于自然总体，从而导致在通过此方法测试关联时第一类错误率的膨胀。在本文中，我们概括了 McKeigue 的连锁测试方法，以允许两种不同的混合模型：（1）混合混合物和（2）连续基因流。我们计算了在不同疾病模型下通过该方法进行全基因组搜索所需的样本量：乘法、加法、隐性和显性。我们的结果表明，如果信息标记的密度为 2 cM，则在实践中通常可以达到在全基因组显着性水平 5% 下检测假定突变等位基因所需的 90% 功效所需的样本量。
Linkage disequilibrium arising from the recent admixture of genetically distinct populations can be potentially useful in mapping genes for complex diseases. McKeigue has proposed a method that conditions on parental admixture to detect linkage. We show that this method tests for linkage only under specific assumptions, such as equal admixture in the parental generation and admixture that occurs in a single generation. In practice, these assumptions are unlikely to hold for natural populations, resulting in an inflation of the type I error rate when testing for linkage by this method. In this article, we generalize McKeigue's approach of testing for linkage to allow two different admixture models: (1) intermixture admixture and (2) continuous gene flow. We calculate the sample size required for a genomewide search by this method under different disease models: multiplicative, additive, recessive, and dominant. Our results show that the sample size required to obtain 90% power to detect a putative mutant allele at a genomewide significance level of 5% can usually be achieved in practice if informative markers are available at a density of 2 cM.