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常见变异与精神分裂症风险相关:GWAS 数据的通路分析。

Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data.

机构信息

Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.

出版信息

Schizophr Res. 2010 Sep;122(1-3):38-42. doi: 10.1016/j.schres.2010.07.001. Epub 2010 Jul 24.

Abstract

Unlike the typical analysis of single markers in genome-wide association studies (GWAS), we incorporated Gene Set Enrichment Analysis (GSEA) and hypergeometric test and combined them using Fisher's combined method to perform pathway-based analysis in order to detect genes' combined effects on mediating schizophrenia. A few pathways were consistently found to be top ranked and likely associated with schizophrenia by these methods; they are related to metabolism of glutamate, the process of apoptosis, inflammation, and immune system (e.g., glutamate metabolism pathway, TGF-beta signaling pathway, and TNFR1 pathway). The genes involved in these pathways had not been detected by single marker analysis, suggesting this approach may complement the original analysis of GWAS dataset.

摘要

与全基因组关联研究(GWAS)中分析单个标记不同,我们采用了基因集富集分析(GSEA)和超几何检验,并使用 Fisher 合并方法将它们结合起来,以进行基于通路的分析,从而检测基因对介导精神分裂症的综合影响。通过这些方法,我们发现一些通路始终名列前茅,可能与精神分裂症有关;它们与谷氨酸代谢、细胞凋亡过程、炎症和免疫系统有关(例如,谷氨酸代谢途径、TGF-β信号通路和 TNFR1 途径)。参与这些通路的基因在单个标记分析中未被检测到,这表明该方法可能补充了 GWAS 数据集的原始分析。

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