TWO STAGE GLOBAL SEARCH DESIGNS FOR LINKAGE ANALYSIS

我们继续比较使用总体的病例对照设计 控件与使用从其亲属中选择的控件的控件的对比 (即，兄弟姐妹、堂兄弟姐妹或基于父母等位基因的“假同胞”) 用于评估候选基因和基因环境的影响 互动。我们现在已经制作了三份手稿来调查 这些研究设计。第一份手稿比较了基本的家庭 设计、评估相对风险估计中的渐近偏差 当由于以下原因而出现混乱时使用人口控制 人口分层。使用兄弟姐妹或伪兄弟姐妹作为对照 完全解决了这个问题，而堂兄弟提供了部分 控制人口分层。接下来，我们将展示 配对病例对照研究的常规条件似然 可以给出渐近有偏效应估计 伪SIB方法；渐近偏向于零和 随着疾病的罕见而消失。这种偏见反映了这样一种假设 伪同胞的(非传递的)亲本等位基因不会导致 疾病。然后，我们展示了使用种群或伪同胞的设计 控件通常是最有效的估计主要 候选基因的影响，紧随其后的是使用 堂兄弟。最后，我们展示了使用同级控件的设计可以 然而，在研究基因环境时，效率相当高 互动。在第二个手稿中，我们调查了偏见和 使用基于以下限制的族设计的效率 家族病史。这些设计帮助重新获得了一些 在处理以下问题时因使用基于家庭的控制而导致的效率损失 人口分层。第三部手稿深入探讨 以家庭为基础的前瞻性和追溯性可能性 病例对照设计。我们用回顾的方式展示了 可能性可以提高估计影响的效率 候选基因或基因与环境的相互作用。

We continue to compare case-control designs that use population controls versus those that use controls selected from their relatives (i.e., siblings, cousins, or ``pseudosibs'' based on parental alleles) for estimating the effect of candidate genes and gene-environment interactions. We have now produced three manuscripts investigating these study designs. The first manuscript compares basic familial designs, evaluating the asymptotic bias in relative risk estimates due to using population controls when there is confounding due to population stratification. Using siblings or pseudosibs as controls completely addresses this issue, whereas cousins provide partial control for population stratification. Next, we show that the conventional conditional likelihood for matched case-control studies can give asymptotically biased effect estimates when applied to the pseudosib approach; the asymptoticbias is towards the null and disappears with disease rarity. This bias reflects the assumption that the pseudosib's (non-transmitted) parental alleles do not lead to disease. We then show that the designs using population or pseudosib controls are generally the most efficient for estimating the main effect of a candidate gene, followed in efficiency by the design using cousins. Finally, we show that the design using sibling controls can be quite efficient, however, when studying gene-environment interactions. In the second manuscript, we investigate the bias and efficiency in using familial designs that are restricted based on family history of disease. These designs help regain some of the efficiency loss due to using family-based controls, while dealing with population stratification. The third manuscript delves into prospective and retrospective likelihoods for family-based case-control designs. We show that using the retrospective likelihoods can improve efficiency for estimating the effects of candidate genes or gene-environment interactions.