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基因与环境研究中的设计与分析问题。

Design and analysis issues in gene and environment studies.

机构信息

Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.

出版信息

Environ Health. 2012 Dec 19;11:93. doi: 10.1186/1476-069X-11-93.

Abstract

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.

摘要

先天因素(遗传因素)和后天因素(环境因素)在人类疾病病因学中都起着重要作用。传统上,人们认为这些影响是相互独立的。但这种观点对于非孟德尔复杂疾病并不适用,因为这些疾病是遗传因素和环境因素相互作用的结果。为了了解健康和疾病,我们必须研究先天因素和后天因素是如何相互作用的。人类基因组学和高通量生物技术的最新进展使得同时研究大量遗传标记和基因产物以探索它们与环境的相互作用成为可能。本文旨在讨论“组学”时代基因-环境相互作用研究的设计和分析问题,重点是环境和遗传流行病学研究。我们提出了一个扩展的环境基因组疾病范例。我们讨论了基因-环境相互作用研究中的几个设计问题,包括混杂和选择偏倚、暴露和基因型的测量。我们讨论了不同研究设计中研究基因-环境相互作用的统计问题,例如统计模型的选择、对生物因素的假设以及功效和样本量的考虑,特别是在全基因组基因-环境研究中。还讨论了未来的研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96a4/3551668/98f46f115b40/1476-069X-11-93-1.jpg

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