Challenges and opportunities in genome-wide environmental interaction (GWEI) studies.
Challenges and opportunities in genome-wide environmental interaction (GWEI) studies.
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DOI：
10.1007/s00439-012-1192-0
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发表时间：
2012-10
期刊：
影响因子：
5.3
通讯作者：
Van Steen K
中科院分区：
文献类型：
--
作者：
Aschard H;Lutz S;Maus B;Duell EJ;Fingerlin TE;Chatterjee N;Kraft P;Van Steen K
随着先进分子遗传学技术的发展，人们对基因-环境相互作用研究的兴趣也显著增加。在实践中，它成为可能的疾病风险调查的环境因素的作用，从而调查其作为遗传效应调节剂的作用。认识到遗传学在有毒物质的吸收和代谢中的重要性，是遗传特征如何改变疾病的重要环境风险因素的一个例子。建立基因-环境相互作用研究存在几个基本原理，之前已经描述了与这些研究相关的技术挑战-当环境或遗传风险因素的数量相对较少时。在后基因组时代，现在可以研究数千个基因及其与环境的相互作用。这带来了沿着一系列新的挑战和机遇。尽管不断努力开发有效的方法和最佳的生物信息学基础设施来处理可用的丰富数据，但挑战仍然是如何最好地呈现和分析涉及多种遗传和环境因素的全基因组环境相互作用（GWEI）研究。由于GWEI是在统计遗传学、生物信息学和流行病学的交叉点上进行的，因此通常需要处理与全基因组关联基因-基因相互作用（GWAI）研究类似的问题。然而，额外的复杂性需要考虑，这是典型的大规模流行病学研究，但也涉及到“加入”两种异质类型的数据，在解释复杂的疾病性状变异或预测的目的。
The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes.
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影响因子：
1.9
作者：
Bůžková P;Lumley T;Rice K
通讯作者：
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影响因子：
158.5
作者：
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DOI：
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发表时间：
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期刊：
European journal of human genetics : EJHG
影响因子：
--
作者：
通讯作者：
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影响因子：
2.1
作者：
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通讯作者：
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