理解遗传变异在风湿性疾病中致病作用的综合方法
Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases.
作者信息
Laufer Vincent A, Chen Jake Y, Langefeld Carl D, Bridges S Louis
机构信息
Division of Clinical Immunology and Rheumatology, School of Medicine, University of Alabama at Birmingham, 1720 2nd Avenue South, SHEL 236, Birmingham, AL 35294-2182, USA.
The Informatics Institute, School of Medicine, University of Alabama at Birmingham, 1720 2nd Avenue South, THT 137, Birmingham, AL 35294-0006, USA.
出版信息
Rheum Dis Clin North Am. 2017 Aug;43(3):449-466. doi: 10.1016/j.rdc.2017.04.012.
The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases.
高通量组学的应用可能有助于理解基因变异在风湿性疾病发病机制中的作用。我们讨论了“遗传力缺失”的概念：即基因变异无法解释类风湿关节炎及相关风湿性疾病的遗传力。除了概述整合数据分析如何能为风湿性疾病的发病机制带来新见解外，我们还描述了用于为未来功能分析确定基因变异优先级的统计方法。我们举例说明了对大型数据集的分析如何为改进风湿性疾病的诊断、治疗和预防方法带来希望。
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