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Ordered subset analysis for case-control studies.

Publication ,  Journal Article
Qin, X; Hauser, ER; Schmidt, S
Published in: Genet Epidemiol
July 2010

Genetic heterogeneity, which may manifest on a population level as different frequencies of a specific disease susceptibility allele in different subsets of patients, is a common problem for candidate gene and genome-wide association studies of complex human diseases. The ordered subset analysis (OSA) was originally developed as a method to reduce genetic heterogeneity in the context of family-based linkage studies. Here, we have extended a previously proposed method (OSACC) for applying the OSA methodology to case-control datasets. We have evaluated the type I error and power of different OSACC permutation tests with an extensive simulation study. Case-control datasets were generated under two different models by which continuous clinical or environmental covariates may influence the relationship between susceptibility genotypes and disease risk. Our results demonstrate that OSACC is more powerful under some disease models than the commonly used trend test and a previously proposed joint test of main genetic and gene-environment interaction effects. An additional unique benefit of OSACC is its ability to identify a more informative subset of cases that may be subjected to more detailed molecular analysis, such as DNA sequencing of selected genomic regions to detect functional variants in linkage disequilibrium with the associated polymorphism. The OSACC-identified covariate threshold may also improve the power of an additional dataset to replicate previously reported associations that may only be detectable in a fraction of the original and replication datasets. In summary, we have demonstrated that OSACC is a useful method for improving SNP association signals in genetically heterogeneous datasets.

Duke Scholars

Published In

Genet Epidemiol

DOI

EISSN

1098-2272

Publication Date

July 2010

Volume

34

Issue

5

Start / End Page

407 / 417

Location

United States

Related Subject Headings

  • Models, Statistical
  • Models, Genetic
  • Linkage Disequilibrium
  • Humans
  • Genotype
  • Genetics, Population
  • Genetic Predisposition to Disease
  • Genetic Linkage
  • Genetic Heterogeneity
  • Gene Frequency
 

Citation

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ICMJE
MLA
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Qin, X., Hauser, E. R., & Schmidt, S. (2010). Ordered subset analysis for case-control studies. Genet Epidemiol, 34(5), 407–417. https://doi.org/10.1002/gepi.20489
Qin, Xuejun, Elizabeth R. Hauser, and Silke Schmidt. “Ordered subset analysis for case-control studies.Genet Epidemiol 34, no. 5 (July 2010): 407–17. https://doi.org/10.1002/gepi.20489.
Qin X, Hauser ER, Schmidt S. Ordered subset analysis for case-control studies. Genet Epidemiol. 2010 Jul;34(5):407–17.
Qin, Xuejun, et al. “Ordered subset analysis for case-control studies.Genet Epidemiol, vol. 34, no. 5, July 2010, pp. 407–17. Pubmed, doi:10.1002/gepi.20489.
Qin X, Hauser ER, Schmidt S. Ordered subset analysis for case-control studies. Genet Epidemiol. 2010 Jul;34(5):407–417.
Journal cover image

Published In

Genet Epidemiol

DOI

EISSN

1098-2272

Publication Date

July 2010

Volume

34

Issue

5

Start / End Page

407 / 417

Location

United States

Related Subject Headings

  • Models, Statistical
  • Models, Genetic
  • Linkage Disequilibrium
  • Humans
  • Genotype
  • Genetics, Population
  • Genetic Predisposition to Disease
  • Genetic Linkage
  • Genetic Heterogeneity
  • Gene Frequency