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Challenges and opportunities in genome-wide environmental interaction (GWEI) studies

机译:全基因组环境相互作用(GWEI)研究中的挑战和机遇

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摘要

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 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.
机译:随着先进的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大大增加。实际上,有可能研究环境因素在疾病风险中的作用,从而研究其作为遗传效应修饰剂的作用。遗传学对有毒物质的吸收和代谢很重要的认识是遗传学谱如何改变疾病的重要环境危险因素的一个例子。建立基因与环境的相互作用研究存在几种基本原理,而当环境或遗传危险因素的数量相对较少时,与这些研究相关的技术挑战已经在前面进行了描述。在后基因组时代,现在有可能研究成千上万的基因及其与环境的相互作用。这带来了一系列新的挑战和机遇。尽管人们一直在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大量数据,但挑战仍然是如何最好地展示和分析涉及多个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-基因相互作用研究类似的问题。但是,还需要考虑其他复杂性,这些复杂性是大规模流行病学研究的典型特征,但也与在解释复杂疾病特征变异或预测目的时“合并”两种异构类型的数据有关。

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  • 来源
    《Human Genetics》 |2012年第10期|p.1591-1613|共23页
  • 作者单位

    Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA;

    Departments of Epidemiology &amp Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;

    Systems and Modeling Unit, Montefiore Institute, University of Liège, Liège, Belgium;

    Departments of Epidemiology &amp Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;

    Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA;

    Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA;

    Systems and Modeling Unit, Montefiore Institute, University of Liège, Liège, Belgium;

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  • 入库时间 2022-08-18 01:50:09

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