Replicability and Prediction: Lessons and Challenges from GWAS.
Replicability and Prediction: Lessons and Challenges from GWAS.
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DOI：
10.1016/j.tig.2018.03.005
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发表时间：
2018-07
期刊：
影响因子：
--
通讯作者：
Navarro A
中科院分区：
文献类型：
--
作者：
Marigorta UM;Rodríguez JA;Gibson G;Navarro A
自10年前Wellcome Trust Case Control Consortium（WTCCC）里程碑式的研究发表以来，全基因组关联研究（GWAS）已经发现了数千种与疾病病因学相关的风险变异。这个成功的故事有两个经常被忽视的角度。首先，全球WAS的发现具有高度可复制性。这是复杂性状遗传学中前所未有的现象，事实上，在过去几十年中一直受到假阳性困扰的许多科学领域也是如此。在对缺乏可重复性的关注日益增加的时候，我们研究了GWAS可重复性的生物学和方法学原因，并确定了未来的挑战。与疾病基因发现的典型成功相反，目前GWAS的发现对预测表型没有帮助。最后，我们概述了个性化预测疾病风险的前景及其在临床实践中可预见的影响。
Since the publication of the Wellcome Trust Case Control Consortium (WTCCC) landmark study a decade ago, genome-wide association studies (GWAS) have led to the discovery of thousands of risk variants involved in disease aetiology. This successful story has two angles that are often overlooked. First, GWAS findings are highly replicable. This is an unprecedented phenomenon in complex trait genetics, and indeed in many areas of science, which in past decades had been plagued by false positives. At a time of increasing concerns about the lack of reproducibility, we examine the biological and methodological reasons that account for the replicability of GWAS and identify the challenges ahead. In contrast to the exemplary success at disease gene discovery, at present GWAS findings are not useful to predict phenotypes. We close with an overview of the prospects for individualized prediction of disease risk and its foreseeable impact in clinical practice.
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