Ioannidis John P A
Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
Circ Cardiovasc Genet. 2009 Feb;2(1):7-15. doi: 10.1161/CIRCGENETICS.108.833392. Epub 2009 Jan 23.
Genome-wide association (GWA) platforms have yielded a rapidly increasing number of new genetic markers. The ability of these markers to improve prediction of clinically important outcomes is debated.
A systematic review was performed of GWA-derived markers associated with cardiovascular outcomes or other phenotypes that represent common established risk factors for cardiovascular outcomes. Sources of information included the National Human Genome Research Institute catalog of published GWA studies, and perusal of the eligible GWA articles, meta-analyses on the respective associations, and articles on the incremental predictive performance of common variants in the GWA era. A total of 95 eligible associations were retrieved from the National Human Genome Research Institute catalogue of published GWA studies as of September 2008. Of those 36 have statistical support of P<10(-7). In depth evaluation of the respective articles shows 28 independent associations with such statistical support, pertaining to coronary artery disease, myocardial infarction, atrial fibrillation/flutter, prolongation of QT interval, as well as type 2 diabetes, body mass index, high-density lipoprotein levels, low-density lipoprotein levels, and nicotine dependence. Between-study heterogeneity is not taken into account usually, but it seems common and it would pose a challenge to generalizability across different populations for these markers. Still limited data are available in non-white populations. Effect sizes are small and may be even smaller in subsequent replications and meta-analysis. Population attributable fractions are substantial, given the large frequency of the risk alleles. However, individualized risk measures are typically very small (proportion of variance explained <1% per marker). When used in conjunction with traditional predictors, improvement in overall prediction (eg, area under the curve) or risk reclassification is limited, and subject to methodological caveats.
Despite very promising signals in terms of statistical significance, evidence for improvement in cardiovascular prediction by currently available markers derived from GWA studies is sparse. Clinical use of such markers currently would be premature.
全基因组关联（GWA）平台产生的新遗传标记数量迅速增加。这些标记改善对临床重要结局预测的能力存在争议。
对与心血管结局或代表心血管结局常见既定危险因素的其他表型相关的GWA衍生标记进行了系统评价。信息来源包括国家人类基因组研究所已发表的GWA研究目录，以及对符合条件的GWA文章、各自关联的荟萃分析，以及GWA时代常见变异体增量预测性能的文章的研读。截至2008年9月，从国家人类基因组研究所已发表的GWA研究目录中总共检索到95个符合条件的关联。其中36个有P<10(-7)的统计学支持。对各自文章的深入评估显示，有28个具有此类统计学支持的独立关联，涉及冠状动脉疾病、心肌梗死、心房颤动/扑动、QT间期延长，以及2型糖尿病、体重指数、高密度脂蛋白水平、低密度脂蛋白水平和尼古丁依赖。通常未考虑研究间的异质性，但这似乎很常见，并且这些标记在不同人群中的可推广性将构成挑战。非白人人群中可用的数据仍然有限。效应大小较小，在后续的重复研究和荟萃分析中可能更小。鉴于风险等位基因的频率较高，人群归因分数相当可观。然而，个体风险测量通常非常小（每个标记解释的方差比例<1%）。当与传统预测因子结合使用时，总体预测（如曲线下面积）或风险重新分类的改善有限，并且存在方法学上的注意事项。
尽管在统计学意义方面有非常有前景的信号，但目前来自GWA研究的标记物改善心血管预测的证据很少。目前临床使用此类标记物还为时过早。
