Bias Due to Two-Stage Residual-Outcome Regression Analysis in Genetic Association Studies
Bias Due to Two-Stage Residual-Outcome Regression Analysis in Genetic Association Studies
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DOI：
10.1002/gepi.20607
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发表时间：
2011-11-01
影响因子：
2.1
通讯作者：
Cupples, L. Adrienne
中科院分区：
文献类型：
--
作者：
Demissie, Serkalem;Cupples, L. Adrienne
危险因素与复杂疾病的关联研究需要仔细评估潜在的混杂因素。两阶段回归分析，有时也被称为残差或调整结果分析，已越来越多地用于单核苷酸多态性（snp）和数量性状的关联研究。在这个分析中，首先，从结果变量对协变量的回归中计算残差结果，然后通过调整结果对SNP的简单线性回归来评估调整结果与SNP之间的关系。在这篇文章中，我们检查了这两阶段分析的性能，与多元线性回归（MLR）分析。我们的研究结果表明，当SNP和协变量相关时，两阶段方法会导致偏倚的基因型效应和功率损失。偏差总是趋向于零，并随着SNP和协变量(rho（2)(SC)）之间的平方相关而增加。例如，对于rho(2)(SC) = 0.0、0.1和0.5，两阶段分析的结果分别是SNP效应衰减0、10和50%。不出所料，MLR总是不偏不倚。由于单个SNPs通常与协变量很少或没有相关性，因此在许多遗传研究中，两阶段分析有望发挥与MLR相同的作用；然而，它产生的结果与MLR有很大的不同，当自变量高度相关时，可能会导致不正确的结论。虽然在rho(2)(SC) = 0.0下是MLR的有用替代方案，但两阶段方法具有严重的局限性。应避免将其作为MLR的简单替代品。麝猫。中华流行病学杂志，2011(5):592-596。(C) 2011 Wiley期刊公司
Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual-or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (rho(2)(SC)). For example, for rho(2)(SC) = 0.0, 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under rho(2)(SC) = 0.0, the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. Genet. Epidemiol. 35:592-596, 2011. (C) 2011 Wiley Periodicals, Inc.