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

机译:掺入基因环境相互作用在测试中与稀有遗传变异的关联

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摘要

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:掺入基因 - 环境相互作用可以提高与复杂性状的遗传关联检测遗传关联的能力。对于常见的遗传变体,已经很好地确定了单标记相互作用和基因 - 环境相互作用的单标相互作用试验和基因环境相互作用的联合试验,并用于鉴定复杂疾病和连续性状的新型关联基因座。然而,对于稀有遗传变体,由于较小的等位基因频率低,单标记试验严重受到功耗,并且仅开发了几种基因环境相互作用测试。我们针对与罕见变种的基因环境相互作用发展强大和计算的有效测试。方法:在本文中,我们提出了用于测试稀有遗传变异的基因环境相互作用的相互作用和关节试验。我们的方法是在某些条件下对多种遗传变异的现有基因环境相互作用试验的概括。结果:我们在我们的仿真研究中展示了我们的相互作用和联合试验具有正确的I次错误,并且联合试验是测试遗传关联的强大方法,允许基因环境相互作用。我们还在Framingham心脏研究中说明了我们在真实数据示例中的方法。结论:我们的方法可以应用于二进制和连续特征,它是强大的和计算效率。

著录项

  • 来源
    《Human Heredity》 |2014年第2期|共10页
  • 作者

    ChenH.; MeigsJ.B.; DupuisJ.;

  • 作者单位

    Department of Biostatistics Boston University School of Public Health Boston Mass. USA;

    Department of Biostatistics Boston University School of Public Health Boston Mass. USA;

    Department of Biostatistics Boston University School of Public Health Boston Mass. USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 医学遗传学;
  • 关键词

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