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多基因精神障碍的基因表达微阵列研究:应用与数据分析

Gene expression microarray studies in polygenic psychiatric disorders: applications and data analysis.

作者信息

Konradi Christine

机构信息

Laboratory of Neuroplasticity, McLean Hospital, 115 Mill Street, Belmont, MA 02478, USA.

出版信息

Brain Res Brain Res Rev. 2005 Dec 1;50(1):142-55. doi: 10.1016/j.brainresrev.2005.05.004. Epub 2005 Jun 20.

Abstract

Gene expression microarrays have become a mainstream technology that can provide valuable insight into psychiatric disorders. Gene expression studies in post mortem brain samples of schizophrenia and bipolar disorder have the potential to yield novel clues about the pathophysiology of these complex trait disorders. In the present review, a short introduction of the genetic and molecular background of schizophrenia and bipolar disorder is followed by a discussion of the basic concept and limits of gene expression microarray technology, and the complexities surrounding the analysis of thousands of gene transcripts. Although this review is intended for use in most platforms, it has a particular focus on the commercially available Affymetrix system. Various computer programs and their principal features are discussed, and it is shown how these programs can be applied to reveal a biological context of microarray findings. I will demonstrate how the programs can help to judge the results rather than focus on their statistical principles. The strength of gene array experiments is their emphasis on broad, biological themes, rather than on specific genes, and proper biostatistical approaches are important to ensure reproducibility of the findings. All results should be verified by independent means. This review is intended to help brain researchers who want to apply gene expression microarray technology to conceptualize research strategies and sample analysis.

摘要

基因表达微阵列已成为一项主流技术,能够为精神疾病提供有价值的见解。对精神分裂症和双相情感障碍患者死后大脑样本进行的基因表达研究,有可能为这些复杂性状疾病的病理生理学提供新线索。在本综述中,首先简要介绍精神分裂症和双相情感障碍的遗传和分子背景,随后讨论基因表达微阵列技术的基本概念和局限性,以及围绕数千个基因转录本分析的复杂性。尽管本综述适用于大多数平台,但特别关注市售的Affymetrix系统。讨论了各种计算机程序及其主要特点,并展示了如何应用这些程序来揭示微阵列研究结果的生物学背景。我将展示这些程序如何有助于判断结果,而不是关注其统计原理。基因阵列实验的优势在于强调广泛的生物学主题,而非特定基因,适当的生物统计学方法对于确保研究结果的可重复性很重要。所有结果都应通过独立方法进行验证。本综述旨在帮助希望应用基因表达微阵列技术的脑研究人员构思研究策略和样本分析。

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