Kurbasic A, Hössjer O
Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden.
Ann Hum Genet. 2006 Nov;70(Pt 6):907-22. doi: 10.1111/j.1469-1809.2006.00266.x.
Many common diseases are known to have genetic components, but since they are non-Mendelian, i.e. a large number of genetic factors affect the phenotype, these components are difficult to localize. These traits are often called complex and analysis of siblings is a valuable tool for mapping them. It has been shown that the power of the affected relative pairs method to detect linkage of a disease susceptibility locus depends on the locus contribution to increased risk of relatives compared with population prevalence (Risch, 1990a,b). In this paper we generalize calculation of relative risk to arbitrary phenotypes and genetic models, but also show that the relative risk can be split into the relative risk at the main locus and the relative risk due to interaction between the main locus and loci at other chromosomes. We demonstrate how the main locus contribution to the relative risk is related to probabilities of allele sharing identical by descent at the main locus, as well as power to detect linkage. To this end we use the effective number of meioses, introduced by Hössjer (2005a) as a convenient tool. Relative risks and effective number of meioses are computed for several genetic models with binary or quantitative phenotypes, with or without polygenic effects.
已知许多常见疾病都有遗传成分，但由于它们是非孟德尔式的，即大量遗传因素影响表型，这些成分很难定位。这些性状通常被称为复杂性状，对同胞的分析是定位它们的一个有价值的工具。研究表明，受影响亲属对法检测疾病易感位点连锁的能力取决于该位点与人群患病率相比对亲属患病风险增加的贡献（里施，1990a，b）。在本文中，我们将相对风险的计算推广到任意表型和遗传模型，但同时也表明相对风险可以分解为主位点的相对风险以及主位点与其他染色体上的位点之间相互作用导致的相对风险。我们展示了主位点对相对风险的贡献如何与主位点上等位基因通过血缘相同的共享概率以及检测连锁的能力相关。为此，我们使用了赫斯耶（2005a）引入的有效减数分裂数作为一个方便的工具。针对具有二元或定量表型、有或没有多基因效应的几种遗传模型，计算了相对风险和有效减数分裂数。
