Pal Deb K, Greenberg David A
Department of Psychiatry, Joseph Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Hum Hered. 2002;53(4):216-26. doi: 10.1159/000066195.
The Admixture test is routinely used in linkage analysis to take account of genetic heterogeneity, and yields an estimate of the proportion of families (alpha) segregating the linked disease gene. In complex disorders, the assumptions of the Admixture test are violated. We therefore explore how the estimate of alpha relates to the true proportion of linked families with a complex disorder in a population or dataset.
We simulated a two-locus heterogeneity model and varied genetic parameters, ascertainment scheme and phenocopy frequency.
In this model, alpha is almost always overestimated, by as little as 5% to as much as 60%. The bias is largely attributable to (1). intrafamilial heterogeneity arising from ascertainment of families with many affected members or from analysis of dense pedigrees; (2). low informativeness, which occurs in the presence of reduced penetrance; and (3). differences in the evidence for linkage in linked and unlinked families. This bias is also affected by the analysis phenocopy frequency, but only if the linked locus is dominant and the unlinked locus is recessive.
We conclude that, in complex diseases, the Admixture test has greater value in detecting linkage than in estimating the proportion of linked families in a dataset.
混合测试通常用于连锁分析以考虑遗传异质性，并得出分离连锁疾病基因的家系比例（α）的估计值。在复杂疾病中，混合测试的假设不成立。因此，我们探讨α的估计值与人群或数据集中患有复杂疾病的连锁家系的真实比例之间的关系。
我们模拟了一个双位点异质性模型，并改变了遗传参数、确定方案和拟表型频率。
在这个模型中，α几乎总是被高估，低估幅度小至5%，大至60%。偏差主要归因于：（1）由于确定有许多患病成员的家系或分析密集家系而产生的家系内异质性；（2）信息性低，这在存在降低的外显率时出现；（3）连锁家系和非连锁家系中连锁证据的差异。这种偏差也受分析拟表型频率的影响，但仅当连锁位点为显性且非连锁位点为隐性时才会如此。
我们得出结论，在复杂疾病中，混合测试在检测连锁方面比在估计数据集中连锁家系的比例方面具有更大的价值。
