Greenberg D A
Department of Psychiatry, Mount Sinai Medical Center, New York, New York 10029.
Genet Epidemiol. 1990;7(6):467-79. doi: 10.1002/gepi.1370070608.
What happens to the results of linkage analysis when one assumes that a disease results from a single genetic locus with reduced penetrance when the actual cause is two epistatically interacting loci? We wanted to (1) determine whether assuming the correct mode of inheritance at the linked locus leads to a higher lod score than assuming the incorrect mode of inheritance irrespective of penetrance assumptions and (2) determine whether it is possible to estimate the apparent penetrance due to the second, unlinked locus from the linkage data. Linkage data were simulated under three different two-locus models. Different "penetrances" were simulated by using different disease allele frequencies at the unlinked locus. Data were then analyzed assuming a single locus with reduced penetrance. The maximum lod score was maximized with respect to penetrance (LVP curves). We found that if there were enough data, assuming the correct (i.e., generating) mode of inheritance at the linked locus always led to a higher lod score than assuming the incorrect mode of inheritance no matter what the penetrance assumption. In contrast to the case where reduced penetrance is due to random factors, the estimate of the apparent penetrance (the "penetrance" due to the second locus) was biased, thus making any estimation of the gene frequency at the second locus doubtful. The ability to detect linkage was apparently not affected when the effects of the second locus were treated as random reduced penetrance. The results suggest that analyzing the data under the assumption of a single-locus model with reduced penetrance rather than a two-locus model will not substantially decrease the ability to establish linkage nor will it affect determining the mode of inheritance at the linked locus from the linkage data.
当实际病因是两个上位性相互作用基因座,而假设疾病由一个外显率降低的单基因座导致时,连锁分析的结果会怎样?我们想要:(1)确定在连锁基因座假设正确的遗传模式是否比假设错误的遗传模式能得到更高的对数优势分数(lod score),而不考虑外显率假设;(2)确定是否有可能从连锁数据中估计由于第二个非连锁基因座导致的表观外显率。在三种不同的双基因座模型下模拟连锁数据。通过在非连锁基因座使用不同的疾病等位基因频率来模拟不同的“外显率”。然后假设一个外显率降低的单基因座来分析数据。相对于外显率最大化最大对数优势分数(LVP曲线)。我们发现,如果有足够的数据,在连锁基因座假设正确(即产生数据的)遗传模式总是比假设错误的遗传模式能得到更高的对数优势分数,无论外显率假设如何。与外显率降低是由于随机因素的情况相反,表观外显率(由于第二个基因座导致的“外显率”)的估计存在偏差,因此使得对第二个基因座基因频率的任何估计都值得怀疑。当将第二个基因座的效应视为随机降低的外显率时,检测连锁的能力显然不受影响。结果表明:在假设一个外显率降低的单基因座模型而非双基因座模型下来分析数据,不会大幅降低建立连锁的能力,也不会影响从连锁数据确定连锁基因座的遗传模式。