Schliekelman Paul, Slatkin Montgomery
Department of Integrative Biology, University of California, Berkeley, USA.
Am J Hum Genet. 2002 Dec;71(6):1369-85. doi: 10.1086/344779. Epub 2002 Nov 21.
Knowledge of the number of causative loci is necessary to estimate the power of mapping studies of complex diseases. In the present article, we reexamine a theory developed by Risch and its implications for estimating the number L of causative loci affecting a complex inherited disease. We first show that methods based on Risch's analysis can produce estimates of L that are inconsistent with the observed population prevalence of the disease. We demonstrate this point by showing that the maximum-likelihood estimate for L produced by the method of Farrall and Holder for cleft lip/cleft palate data is not consistent with the prevalence under the multiplicative model. We show how to incorporate disease prevalence and develop a maximum-likelihood method for estimating L that uses the entire distribution of numbers of affected individuals in families containing an affected individual. This method avoids the potential inconsistencies of the Risch method and has greater precision. We apply our method to data on cleft lip/cleft palate and schizophrenia.
了解致病基因座的数量对于估计复杂疾病图谱研究的效能是必要的。在本文中,我们重新审视了里施提出的一个理论及其对估计影响复杂遗传疾病的致病基因座数量L的意义。我们首先表明,基于里施分析的方法可能会得出与所观察到的疾病人群患病率不一致的L估计值。我们通过展示法勒尔和霍尔德方法对唇腭裂数据得出的L的最大似然估计值与乘法模型下的患病率不一致来证明这一点。我们展示了如何纳入疾病患病率,并开发了一种最大似然方法来估计L,该方法使用了包含患病个体的家庭中患病个体数量的整个分布。这种方法避免了里施方法可能存在的不一致性,并且具有更高的精度。我们将我们的方法应用于唇腭裂和精神分裂症的数据。