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Stratification-score matching improves correction for confounding by population stratification in case-control association studies.

Publication ,  Journal Article
Epstein, MP; Duncan, R; Broadaway, KA; He, M; Allen, AS; Satten, GA
Published in: Genet Epidemiol
April 2012

Proper control of confounding due to population stratification is crucial for valid analysis of case-control association studies. Fine matching of cases and controls based on genetic ancestry is an increasingly popular strategy to correct for such confounding, both in genome-wide association studies (GWASs) as well as studies that employ next-generation sequencing, where matching can be used when selecting a subset of participants from a GWAS for rare-variant analysis. Existing matching methods match on measures of genetic ancestry that combine multiple components of ancestry into a scalar quantity. However, we show that including nonconfounding ancestry components in a matching criterion can lead to inaccurate matches, and hence to an improper control of confounding. To resolve this issue, we propose a novel method that assigns cases and controls to matched strata based on the stratification score (Epstein et al. [2007] Am J Hum Genet 80:921-930), which is the probability of disease given genomic variables. Matching on the stratification score leads to more accurate matches because case participants are matched to control participants who have a similar risk of disease given ancestry information. We illustrate our matching method using the African-American arm of the GAIN GWAS of schizophrenia. In this study, we observe that confounding due to stratification can be resolved by our matching approach but not by other existing matching procedures. We also use simulated data to show our novel matching approach can provide a more appropriate correction for population stratification than existing matching approaches.

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Published In

Genet Epidemiol

DOI

EISSN

1098-2272

Publication Date

April 2012

Volume

36

Issue

3

Start / End Page

195 / 205

Location

United States

Related Subject Headings

  • Software
  • Schizophrenia
  • Models, Genetic
  • Humans
  • Genome-Wide Association Study
  • Epidemiology
  • Case-Control Studies
  • Black or African American
  • 4202 Epidemiology
  • 3105 Genetics
 

Citation

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Chicago
ICMJE
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Epstein, M. P., Duncan, R., Broadaway, K. A., He, M., Allen, A. S., & Satten, G. A. (2012). Stratification-score matching improves correction for confounding by population stratification in case-control association studies. Genet Epidemiol, 36(3), 195–205. https://doi.org/10.1002/gepi.21611
Epstein, Michael P., Richard Duncan, K Alaine Broadaway, Min He, Andrew S. Allen, and Glen A. Satten. “Stratification-score matching improves correction for confounding by population stratification in case-control association studies.Genet Epidemiol 36, no. 3 (April 2012): 195–205. https://doi.org/10.1002/gepi.21611.
Epstein MP, Duncan R, Broadaway KA, He M, Allen AS, Satten GA. Stratification-score matching improves correction for confounding by population stratification in case-control association studies. Genet Epidemiol. 2012 Apr;36(3):195–205.
Epstein, Michael P., et al. “Stratification-score matching improves correction for confounding by population stratification in case-control association studies.Genet Epidemiol, vol. 36, no. 3, Apr. 2012, pp. 195–205. Pubmed, doi:10.1002/gepi.21611.
Epstein MP, Duncan R, Broadaway KA, He M, Allen AS, Satten GA. Stratification-score matching improves correction for confounding by population stratification in case-control association studies. Genet Epidemiol. 2012 Apr;36(3):195–205.
Journal cover image

Published In

Genet Epidemiol

DOI

EISSN

1098-2272

Publication Date

April 2012

Volume

36

Issue

3

Start / End Page

195 / 205

Location

United States

Related Subject Headings

  • Software
  • Schizophrenia
  • Models, Genetic
  • Humans
  • Genome-Wide Association Study
  • Epidemiology
  • Case-Control Studies
  • Black or African American
  • 4202 Epidemiology
  • 3105 Genetics