Willis-Owen Saffron A G, Cookson William O, Moffatt Miriam F
Molecular Genetics, National Heart and Lung Institute, London, United Kingdom.
Curr Allergy Asthma Rep. 2009 Jan;9(1):3-9. doi: 10.1007/s11882-009-0001-x.
The field of asthma genetics has progressed rapidly over the past decade, implicating many genes and variants in the etiology of this complex disease. However, many of these factors have failed to replicate consistently, indicating a high false-positive rate and/or insufficient power for the detection of small effects. Technological limitations also have restricted the potential to detect novel mechanisms, fostering a dependence on existing knowledge. Since its inception almost 4 years ago, genome-wide association (GWA) has transformed genetic studies of multifactorial traits and yielded unprecedented insights into mechanisms of causation. Asthma is at the forefront of this revolution, as it uses GWA to map not only genetic determinants of clinical status but also transcript and protein abundance and structural (copy number) variants that may underlie disease susceptibility. In this review, we consider the applications of GWA data to asthma and describe the factors likely to influence the procedure's success.
在过去十年中,哮喘遗传学领域取得了迅速进展,许多基因和变异与这种复杂疾病的病因相关。然而,其中许多因素未能得到一致的重复验证,这表明假阳性率很高和/或检测微小效应的能力不足。技术限制也制约了发现新机制的潜力,导致对现有知识的依赖。自大约4年前启动以来,全基因组关联研究(GWA)改变了对多因素性状的遗传学研究,并对因果机制产生了前所未有的见解。哮喘处于这场革命的前沿,因为它利用GWA不仅绘制临床状态的遗传决定因素,还绘制可能是疾病易感性基础的转录本和蛋白质丰度以及结构(拷贝数)变异。在本综述中,我们考虑了GWA数据在哮喘中的应用,并描述了可能影响该方法成功的因素。