Alarcon F, Bourgain C, Gauthier-Villars M, Planté-Bordeneuve V, Stoppa-Lyonnet D, Bonaïti-Pellié C
University Paris-Sud, Villejuif, France.
Genet Epidemiol. 2009 Jul;33(5):379-85. doi: 10.1002/gepi.20390.
Providing valid risk estimates of a genetic disease with variable age of onset is a major challenge for prevention strategies. When data are obtained from pedigrees ascertained through affected individuals, an adjustment for ascertainment bias is necessary. This article focuses on ascertainment through at least one affected and presents an estimation method based on maximum likelihood, called the Proband's phenotype exclusion likelihood or PEL for estimating age-dependent penetrance using disease status and genotypic information of family members in pedigrees unselected for family history. We studied the properties of the PEL and compared with another method, the prospective likelihood, in terms of bias and efficiency in risk estimate. For that purpose, family samples were simulated under various disease risk models and under various ascertainment patterns. We showed that, whatever the genetic model and the ascertainment scheme, the PEL provided unbiased estimates, whereas the prospective likelihood exhibited some bias in a number of situations. As an illustration, we estimated the disease risk for transthyretin amyloid neuropathy from a French sample and a Portuguese sample and for BRCA1/2 associated breast cancer from a sample ascertained on early-onset breast cancer cases.
为具有可变发病年龄的遗传病提供有效的风险估计是预防策略面临的一项重大挑战。当从通过患病个体确定的家系中获取数据时,必须对确定偏倚进行校正。本文重点关注通过至少一名患者进行的确定,并提出了一种基于最大似然法的估计方法,称为先证者表型排除似然法(PEL),用于利用未根据家族史选择的家系中家庭成员的疾病状态和基因型信息来估计年龄依赖性外显率。我们研究了PEL的特性,并在风险估计的偏差和效率方面与另一种方法——前瞻性似然法进行了比较。为此,在各种疾病风险模型和各种确定模式下模拟了家系样本。我们表明,无论遗传模型和确定方案如何,PEL都能提供无偏估计,而前瞻性似然法在许多情况下表现出一些偏差。作为例证,我们从一个法国样本和一个葡萄牙样本中估计了转甲状腺素蛋白淀粉样变性神经病的疾病风险,并从一个基于早发性乳腺癌病例确定的样本中估计了BRCA1/2相关乳腺癌的疾病风险。