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Mapping genes that predict treatment outcome in admixed populations

The Pharmacogenomics Journal volume 10, pages 465–477 (2010)Cite this article

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Abstract

There is great interest in characterizing the genetic architecture underlying drug response. For many drugs, gene-based dosing models explain a considerable amount of the overall variation in treatment outcome. As such, prescription drug labels are increasingly being modified to contain pharmacogenetic information. Genetic data must, however, be interpreted within the context of relevant clinical covariates. Even the most predictive models improve with the addition of data related to biogeographical ancestry. The current review explores analytical strategies that leverage population structure to more fully characterize genetic determinants of outcome in large clinical practice-based cohorts. The success of this approach will depend upon several key factors: (1) the availability of outcome data from groups of admixed individuals (that is, populations recombined over multiple generations), (2) a measurable difference in treatment outcome (that is, efficacy and toxicity end points), and (3) a measurable difference in allele frequency between the ancestral populations.

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Acknowledgements

This study was supported by P30HL10133, U19A170235, U01HG004608, U01HL069757, K01HL103165 and R01DK080007.

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  1. Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA

    T M Baye

  2. Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    R A Wilke

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  1. T M Baye
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Correspondence to T M Baye or R A Wilke.

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Baye, T., Wilke, R. Mapping genes that predict treatment outcome in admixed populations. Pharmacogenomics J 10, 465–477 (2010). https://doi.org/10.1038/tpj.2010.71

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  • DOI: https://doi.org/10.1038/tpj.2010.71

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