Linear trend tests for case-control genetic association that incorporate random phenotype and genotype misclassification error

Derek Gordon, Chad Haynes, Yaning Yang, Patricia L. Kramer, Stephen J. Finch

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

The purpose of this work is the development of linear trend tests that allow for error (LTTae), specifically incorporating double-sampling information on phenotypes and/or genotypes. We use a likelihood framework. Misclassification errors are estimated via double sampling. Unbiased estimates of penetrances and genotype frequencies are determined through application of the Expectation-Maximization algorithm. We perform simulation studies to evaluate false-positive rates for various genotype classification weights (recessive, dominant, additive). We compare simulated power between the LTT ae and its genotypic test equivalent, the LRTae, in the presence of phenotype and genotype misclassification, to evaluate power gains of the LTTae for multi-locus haplotype association with a dominant mode of inheritance. Finally, we apply LTTae and a method without double-sample information (LTTstd) to double-sampled phenotype data for an actual Alzheimer's disease (AD) case-control study with ApoE genotypes. Simulation results suggest that the LTTae maintains correct false-positive rates in the presence of misclassification. For power simulations, the LTTae method is at least as powerful as LRT ae method, with a maximum power gain of 0.42 over the LRT ae method for certain parameter settings. For AD data, LTT ae provides more significant evidence for association (permutation p = 0.0522) than LTTstd (permutation p = 0.1684). This is due to observed phenotype misclassification. The LTTae statistic enables researchers to apply linear trend tests to case-control genetic data, increasing power to detect association in the presence of misclassification. If the disease MOI is known, LTTae methods are usually more powerful due to the fact that the statistic has fewer degrees of freedom.

Original languageEnglish (US)
Pages (from-to)853-870
Number of pages18
JournalGenetic Epidemiology
Volume31
Issue number8
DOIs
Publication statusPublished - Dec 2007

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Keywords

  • Case
  • Control
  • Diagnosis error
  • Diagnostic error
  • Duplicate sample
  • Genomewide association
  • Genotyping error
  • Haplotype
  • Multi-locus genotype

ASJC Scopus subject areas

  • Genetics(clinical)
  • Epidemiology

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