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Bjarni Jóhann Vilhjálmsson

Mixed Model with Correction for Case-Control Ascertainment Increases Association Power

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  • Tristan J Hayeck, Ukendt
  • Noah A Zaitlen, Ukendt
  • Po-Ru Loh
  • ,
  • Bjarni Jóhann Vilhjálmsson
  • Samuela Pollack
  • ,
  • Alexander Gusev
  • ,
  • Jian Yang, Danmark
  • Guo-Bo Chen
  • ,
  • Michael E Goddard
  • ,
  • Peter M Visscher
  • ,
  • Nick Patterson
  • ,
  • Alkes L Price

We introduce a liability-threshold mixed linear model (LTMLM) association statistic for case-control studies and show that it has a well-controlled false-positive rate and more power than existing mixed-model methods for diseases with low prevalence. Existing mixed-model methods suffer a loss in power under case-control ascertainment, but no solution has been proposed. Here, we solve this problem by using a χ(2) score statistic computed from posterior mean liabilities (PMLs) under the liability-threshold model. Each individual's PML is conditional not only on that individual's case-control status but also on every individual's case-control status and the genetic relationship matrix (GRM) obtained from the data. The PMLs are estimated with a multivariate Gibbs sampler; the liability-scale phenotypic covariance matrix is based on the GRM, and a heritability parameter is estimated via Haseman-Elston regression on case-control phenotypes and then transformed to the liability scale. In simulations of unrelated individuals, the LTMLM statistic was correctly calibrated and achieved higher power than existing mixed-model methods for diseases with low prevalence, and the magnitude of the improvement depended on sample size and severity of case-control ascertainment. In a Wellcome Trust Case Control Consortium 2 multiple sclerosis dataset with >10,000 samples, LTMLM was correctly calibrated and attained a 4.3% improvement (p = 0.005) in χ(2) statistics over existing mixed-model methods at 75 known associated SNPs, consistent with simulations. Larger increases in power are expected at larger sample sizes. In conclusion, case-control studies of diseases with low prevalence can achieve power higher than that in existing mixed-model methods.

OriginalsprogEngelsk
TidsskriftAmerican Journal of Human Genetics
ISSN0002-9297
DOI
StatusUdgivet - 14 apr. 2015
Eksternt udgivetJa

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