Bias correction to secondary trait analysis with case–control design

Authors

  • Hua Yun Chen,

    Corresponding author
    • Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL, U.S.A.
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  • Rick Kittles,

    1. Department of Medicine, College of Medicine, Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL, U.S.A.
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  • Wei Zhang

    1. Department of Pediatrics, College of Medicine, University of Illinois at Chicago, Chicago, IL, U.S.A.
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Correspondence to: Hua Yun Chen, Division of Epidemiology & Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 West Taylor Street, Chicago, IL 60612, U.S.A.

E-mail: hychen@uic.edu

Abstract

In genetic association studies with densely typed genetic markers, it is often of substantial interest to examine not only the primary phenotype but also the secondary traits for their association with the genetic markers. For more efficient sample ascertainment of the primary phenotype, a case–control design or its variants, such as the extreme-value sampling design for a quantitative trait, are often adopted. The secondary trait analysis without correcting for the sample ascertainment may yield a biased association estimator. We propose a new method aiming at correcting the potential bias due to the inadequate adjustment of the sample ascertainment. The method yields explicit correction formulas that can be used to both screen the genetic markers and rapidly evaluate the sensitivity of the results to the assumed baseline case-prevalence rate in the population. Simulation studies demonstrate good performance of the proposed approach in comparison with the more computationally intensive approaches, such as the compensator approaches and the maximum prospective likelihood approach. We illustrate the application of the approach by analysis of the genetic association of prostate specific antigen in a case–control study of prostate cancer in the African American population. Copyright © 2012 John Wiley & Sons, Ltd.

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