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Robust analysis of secondary phenotypes in case-control genetic association studies.

Publication ,  Journal Article
Xing, C; M McCarthy, J; Dupuis, J; Adrienne Cupples, L; B Meigs, J; Lin, X; S Allen, A
Published in: Stat Med
October 15, 2016

The case-control study is a common design for assessing the association between genetic exposures and a disease phenotype. Though association with a given (case-control) phenotype is always of primary interest, there is often considerable interest in assessing relationships between genetic exposures and other (secondary) phenotypes. However, the case-control sample represents a biased sample from the general population. As a result, if this sampling framework is not correctly taken into account, analyses estimating the effect of exposures on secondary phenotypes can be biased leading to incorrect inference. In this paper, we address this problem and propose a general approach for estimating and testing the population effect of a genetic variant on a secondary phenotype. Our approach is based on inverse probability weighted estimating equations, where the weights depend on genotype and the secondary phenotype. We show that, though slightly less efficient than a full likelihood-based analysis when the likelihood is correctly specified, it is substantially more robust to model misspecification, and can out-perform likelihood-based analysis, both in terms of validity and power, when the model is misspecified. We illustrate our approach with an application to a case-control study extracted from the Framingham Heart Study. Copyright © 2016 John Wiley & Sons, Ltd.

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Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

October 15, 2016

Volume

35

Issue

23

Start / End Page

4226 / 4237

Location

England

Related Subject Headings

  • Statistics & Probability
  • Polymorphism, Single Nucleotide
  • Phenotype
  • Models, Genetic
  • Likelihood Functions
  • Humans
  • Genome-Wide Association Study
  • Genetic Association Studies
  • Case-Control Studies
  • 4905 Statistics
 

Citation

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Xing, C., M McCarthy, J., Dupuis, J., Adrienne Cupples, L., B Meigs, J., Lin, X., & S Allen, A. (2016). Robust analysis of secondary phenotypes in case-control genetic association studies. Stat Med, 35(23), 4226–4237. https://doi.org/10.1002/sim.6976
Xing, Chuanhua, Janice M McCarthy, Josée Dupuis, L. Adrienne Cupples, James B Meigs, Xihong Lin, and Andrew S Allen. “Robust analysis of secondary phenotypes in case-control genetic association studies.Stat Med 35, no. 23 (October 15, 2016): 4226–37. https://doi.org/10.1002/sim.6976.
Xing C, M McCarthy J, Dupuis J, Adrienne Cupples L, B Meigs J, Lin X, et al. Robust analysis of secondary phenotypes in case-control genetic association studies. Stat Med. 2016 Oct 15;35(23):4226–37.
Xing, Chuanhua, et al. “Robust analysis of secondary phenotypes in case-control genetic association studies.Stat Med, vol. 35, no. 23, Oct. 2016, pp. 4226–37. Pubmed, doi:10.1002/sim.6976.
Xing C, M McCarthy J, Dupuis J, Adrienne Cupples L, B Meigs J, Lin X, S Allen A. Robust analysis of secondary phenotypes in case-control genetic association studies. Stat Med. 2016 Oct 15;35(23):4226–4237.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

October 15, 2016

Volume

35

Issue

23

Start / End Page

4226 / 4237

Location

England

Related Subject Headings

  • Statistics & Probability
  • Polymorphism, Single Nucleotide
  • Phenotype
  • Models, Genetic
  • Likelihood Functions
  • Humans
  • Genome-Wide Association Study
  • Genetic Association Studies
  • Case-Control Studies
  • 4905 Statistics