Daw E W, Heath S C, Wijsman E M
Department of Medicine, Division of Medical Genetics, Box 357720, University of Washington, Seattle, WA 98195-7720, USA. warwickd@u. washington.edu
Am J Hum Genet. 1999 Mar;64(3):839-51. doi: 10.1086/302276.
It is usually difficult to localize genes that cause diseases with late ages at onset. These diseases frequently exhibit complex modes of inheritance, and only recent generations are available to be genotyped and phenotyped. In this situation, multipoint analysis using traditional exact linkage analysis methods, with many markers and full pedigree information, is a computationally intractable problem. Fortunately, Monte Carlo Markov chain sampling provides a tool to address this issue. By treating age at onset as a right-censored quantitative trait, we expand the methods used by Heath (1997) and illustrate them using an Alzheimer disease (AD) data set. This approach estimates the number, sizes, allele frequencies, and positions of quantitative trait loci (QTLs). In this simultaneous multipoint linkage and segregation analysis method, the QTLs are assumed to be diallelic and to interact additively. In the AD data set, we were able to localize correctly, quickly, and accurately two known genes, despite the existence of substantial genetic heterogeneity, thus demonstrating the great promise of these methods for the dissection of late-onset oligogenic diseases.
定位导致晚发型疾病的基因通常很困难。这些疾病常常呈现复杂的遗传模式，并且只有最近几代可用于进行基因分型和表型分析。在这种情况下，使用具有许多标记和完整家系信息的传统精确连锁分析方法进行多点分析是一个计算上难以处理的问题。幸运的是，蒙特卡罗马尔可夫链抽样提供了一种解决此问题的工具。通过将发病年龄视为右删失定量性状，我们扩展了希思（1997年）使用的方法，并使用阿尔茨海默病（AD）数据集对其进行了说明。这种方法估计数量性状基因座（QTL）的数量、大小、等位基因频率和位置。在这种同时进行的多点连锁和分离分析方法中，假设QTL是双等位基因的并且以加性方式相互作用。在AD数据集中，尽管存在大量遗传异质性，我们仍能够正确、快速且准确地定位两个已知基因，从而证明了这些方法在剖析晚发型寡基因疾病方面的巨大前景。
