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Incorporating Gene-Environment Interaction in Testing for Association with Rare Genetic Variants

机译:在与稀有遗传变异的关联测试中纳入基因-环境相互作用

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Objectives: The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. Methods: In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. Results: We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Conclusion: Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.
机译:目的:整合基因-环境相互作用可以提高检测具有复杂性状的遗传关联的能力。对于常见的遗传变异,已经建立了单标记相互作用测试以及遗传主要作用和基因-环境相互作用的联合测试,并用于鉴定复杂疾病和连续性状的新型关联基因座。然而,对于稀有的遗传变异,由于较低的次要等位基因频率,单标记测试的能力严重不足,并且仅开发了少数基因-环境相互作用测试。我们旨在开发功能强大且计算效率高的测试,用于与罕见变体进行基因-环境相互作用。方法:在本文中,我们提出了相互作用和联合测试,以测试稀有遗传变异的基因-环境相互作用。我们的方法是在一定条件下对多种基因变异的现有基因-环境相互作用测试的概括。结果:我们在模拟研究中表明,我们的交互和联合测试具有正确的I型错误,并且联合测试是测试遗传关联的强大方法,可以实现基因与环境的交互。我们还将在Framingham心脏研究的真实数据示例中说明我们的方法。结论:我们的方法可以应用于二进制和连续性状,它功能强大且计算效率高。

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