Xiao R, Boehnke M. Quantifying and correcting for the winner's curse in genetic association studies. Genet Epidemiol 33: 453-462

University of Michigan, Ann Arbor, Michigan, United States
Genetic Epidemiology (Impact Factor: 2.6). 07/2009; 33(5):453-62. DOI: 10.1002/gepi.20398
Source: PubMed


Genetic association studies are a powerful tool to detect genetic variants that predispose to human disease. Once an associated variant is identified, investigators are also interested in estimating the effect of the identified variant on disease risk. Estimates of the genetic effect based on new association findings tend to be upwardly biased due to a phenomenon known as the "winner's curse." Overestimation of genetic effect size in initial studies may cause follow-up studies to be underpowered and so to fail. In this paper, we quantify the impact of the winner's curse on the allele frequency difference and odds ratio estimators for one- and two-stage case-control association studies. We then propose an ascertainment-corrected maximum likelihood method to reduce the bias of these estimators. We show that overestimation of the genetic effect by the uncorrected estimator decreases as the power of the association study increases and that the ascertainment-corrected method reduces absolute bias and mean square error unless power to detect association is high.

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    • "Thus, even conservative estimates of the sample size needed for tests of replication based on the lower bound of the original effect size estimate may be too small. Statistical methods have been developed to improve sample size estimates under conditions of expected shrinking effect sizes, however (Xiao and Boehnke 2009). "

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    • "Therefore, detection of an association would require a larger sample size, regardless of disease prevalence [87]. Most candidate gene studies for IS had small cohorts, so it is difficult to discern whether associations were not replicated in other cohorts (same or different ethnic background) as a consequence of genetic heterogeneity or ascertainment bias (e.g., “winner’s curse”) [88] (Fig. 2). Based on estimations from Hattersley and McCarthy [89], a study needs thousands of individuals to detect a common variant of a risk allele with a low-to-moderate effect. "
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    • "While they are relatively easy to perform, interpretation of the results of successful association studies is neither straightforward nor always replicable. In addition, overestimation of genetic effect size in initial studies due to "winner's curse" may cause follow-up studies to be underpowered and so to fail [25]. Results of the current study and others do not replicate previously identified hypertension-related SNPs in GWAS. "
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    ABSTRACT: A recent genome wide association study in 1017 African Americans identified several single nucleotide polymorphisms that reached genome-wide significance for systolic blood pressure. We attempted to replicate these findings in an independent sample of 2474 unrelated African Americans in the Milwaukee metropolitan area; 53% were women and 47% were hypertensives. We evaluated sixteen top associated SNPs from the above genome wide association study for hypertension as a binary trait or blood pressure as a continuous trait. In addition, we evaluated eight single nucleotide polymorphisms located in two genes (STK-39 and CDH-13) found to be associated with systolic and diastolic blood pressures by other genome wide association studies in European and Amish populations. TaqMan MGB-based chemistry with fluorescent probes was used for genotyping. We had an adequate sample size (80% power) to detect an effect size of 1.2-2.0 for all the single nucleotide polymorphisms for hypertension as a binary trait, and 1% variance in blood pressure as a continuous trait. Quantitative trait analyses were performed both by excluding and also by including subjects on anti-hypertensive therapy (after adjustments were made for anti-hypertensive medications). For all 24 SNPs, no statistically significant differences were noted in the minor allele frequencies between cases and controls. One SNP (rs2146204) showed borderline association (p = 0.006) with hypertension status using recessive model and systolic blood pressure (p = 0.02), but was not significant after adjusting for multiple comparisons. In quantitative trait analyses, among normotensives only, rs12748299 was associated with SBP (p = 0.002). In addition, several nominally significant associations were noted with SBP and DBP among normotensives but none were statistically significant. This study highlights the importance of replication to confirm the validity of genome wide association study results.
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