Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.
Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.
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DOI：
10.1002/gepi.20628
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发表时间：
2011-12
影响因子：
2.1
通讯作者：
Conti, David
中科院分区：
文献类型：
--
作者：
Li, Dalin;Lewinger, Juan Pablo;Gauderman, William J.;Murcray, Cassandra Elizabeth;Conti, David
最近基于共同疾病共同变异假说的全基因组关联研究中发现的变异远远不能完全解释复杂性状的可遗传性。罕见的变异可能在一定程度上解释了一些缺失的遗传性。在这里，我们探索了极端表型抽样在罕见变异分析中的优势，并为未来数量性状的大规模关联研究完善了这一设计框架。我们首先提出了一种基于似然分析方法的功率计算方法。然后，我们使用这种方法来证明极端表型取样对罕见变异的潜在优势。接下来，我们从成本效益（包括表型成本）的角度讨论了这种设计如何影响未来基于测序的关联研究。此外，我们还讨论了以极端样本为第一阶段，其余非极端受试者为第二阶段的两阶段设计的可能性。我们证明了这种两阶段设计是一种经济高效的选择，可以替代单阶段截面设计或传统的两阶段设计。然后讨论了这种极端两阶段设计的分析策略，并提出了相应的设计优化流程。为了解决许多实际问题，例如极端情况下的测量误差或表型异质性，我们研究了一种方法，在这种方法中，具有非常极端表型的个体被丢弃。我们证明，即使丢弃了这些极端个体的很大一部分，基于极端的抽样仍然可以更有效。最后，我们扩展了当前的分析和设计框架，以适应CMC方法，其中联合分析同一基因区域的多个罕见变异。
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly.
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DOI：
10.1038/nrg2544
发表时间：
2009-05
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
Ioannidis JP;Thomas G;Daly MJ
通讯作者：
Daly MJ
中国汉族人群8个基因/位点遗传变异与2型糖尿病的关联研究
影响因子：
--
作者：
Lin, Ying;Li, Pengqiu;Yang, Zhenglin
通讯作者：
Yang, Zhenglin
影响因子：
9.8
作者：
Huang, B. E.;Lin, D. Y.
通讯作者：
Lin, D. Y.
影响因子：
9.8
作者：
Li, Bingshan;Leal, Suzanne M.
通讯作者：
Leal, Suzanne M.
影响因子：
1
作者：
KIEFER, J
通讯作者：
KIEFER, J