Curtis David, Knight Jo, Sham Pak C
Academic Department of Psychiatry, Queen Mary's School of Medicine and Dentistry, London E1 1BB, UK.
Psychiatr Genet. 2005 Sep;15(3):181-7. doi: 10.1097/01.ypg.0000173119.04430.65.
Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance.
The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism.
With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set, suggesting that QMFLINK may have been able to detect a true linkage which was not picked up by the other methods.
The application of model-free LOD score analysis to quantitative traits is novel and deserves further evaluation of its merits and disadvantages relative to other methods.
尽管对数优势（LOD）评分方法已应用于具有复杂遗传模式的疾病，但数量性状的连锁分析往往依赖于基于回归或方差成分分析的非参数方法。在此，我们描述了一种用于数量性状LOD评分分析的新方法，该方法不需要指定遗传模式。
该技术源自用于二分性状的MFLINK方法。构建一系列合理的传递模型，这些模型被约束以产生该性状正确的总体均值和方差，但在所考虑的基因座对方差的贡献方面有所不同。计算在同质性和混合情况下的最大LOD评分，以及一个无模型的LOD评分，该评分比较了在假设连锁和不连锁的混合情况下的最大似然性。这些LOD评分具有已知的渐近分布，因此可用于提供连锁的统计检验。该方法已在一个名为QMFLINK的程序中实现。它被应用于使用各种传递模型模拟的数据集，以及来自酒精中毒遗传学协作研究的105个家系中的单胺氧化酶活性测量值。
对于模拟数据，结果表明，如果该性状的真实等位基因频率接近指定频率，新方法能够很好地检测连锁。然而，在真实等位基因频率非常罕见的模型上，它的表现很差。对于酒精中毒遗传学协作研究数据集，新方法获得的结果与先前使用回归和方差成分分析对相同数据进行分析时获得的结果之间仅观察到适度的重叠。有趣的是，D17S250在同质性和混合情况下产生的最大LOD评分为2.6，但使用先前的方法未表明存在连锁。然而，该区域在另一个数据集中确实产生了连锁证据，这表明QMFLINK可能能够检测到其他方法未发现的真正连锁。
将无模型LOD评分分析应用于数量性状是新颖的，相对于其他方法，其优缺点值得进一步评估。
