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确定乙醇和酒精中毒神经生物学背后的基因网络。

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

作者信息

Wolen Aaron R, Miles Michael F

机构信息

Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia.

出版信息

Alcohol Res. 2012;34(3):306-17.

Abstract

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

摘要

对于诸如酒精中毒这样的复杂疾病,确定与这些疾病相关的基因及其特定作用是困难的。传统的遗传学方法,如基因关联研究(包括全基因组关联研究)以及对人类和实验动物的数量性状基因座(QTL)分析,已经有助于识别一些候选基因。然而,由于技术障碍,如任何单个基因的影响较小,这些方法在识别导致复杂疾病的特定基因方面仅具有有限的有效性。新兴的系统生物学领域允许对整个基因网络进行分析,这可能有助于研究人员更好地阐明人类和动物模型中酒精中毒的遗传基础。可以使用高通量分子谱分析方法(例如通过基于微阵列的基因表达分析)或称为遗传基因组学的策略,如表达QTL(eQTL)定位,来识别这样的网络。基因网络的表征可以揭示复杂性状背后的生物学途径,并为识别那些导致疾病发展的基因提供功能背景。

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