Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Biotech I, 800 E. Leigh Street, Richmond, VA 23298-0126, USA.
Hum Genet. 2011 Feb;129(2):221-30. doi: 10.1007/s00439-010-0917-1. Epub 2010 Nov 23.
Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI (p value = 3.19 E-06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits.
全基因组关联研究(GWAS)使用大样本量对体重指数(BMI)进行了研究,发现了大约十几个与 BMI 强相关的变异,并提示了其他的基因座。这些变异的个体效应较小,总体上只解释了一小部分的方差。因此,即使有几千个样本,复制尝试也只有有限的能力达到全基因组的显著性。由于特定变异对 BMI 有很强的遗传影响,因此可以采用替代方法进行复制。与其逐个测试个体基因座,不如测试一个综合了所有风险等位基因的遗传风险总和评分(GRSS)。在当前的研究中,我们对由两个大型荟萃分析编目的 56 个顶级变体组成的 GRSS 进行了测试,以研究其与精神分裂症分子遗传学对照(2653 名欧洲裔美国人,973 名非裔美国人)的 BMI 之间的关联。在考虑了已知影响 BMI 的协变量(祖源、性别、年龄)后,GRSS 与 BMI 高度相关(p 值=3.19E-06),尽管只解释了有限的方差(0.66%)。然而,接收者操作特征曲线下的面积(AUC)估计值表明,GRSS 和协变量可以显著预测超重和肥胖分类,对于预测第三类肥胖(AUC=0.697)具有最大的区分能力。我们事后检验了各个基因座对 GRSS 的相对贡献,结果并不是由于少数几个高度显著的变异,而是由于许多小效应的变异所致。这项研究提供了证据,证明了 GRSS 作为一种替代方法,用于复制复杂性状中常见的多基因变异的有效性。