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A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies

The Pharmacogenomics Journal volume 9, pages 137–146 (2009)Cite this article

Abstract

Biomedical researchers usually test the null hypothesis that there is no difference of the population mean of pharmacokinetics (PK) parameters between genotypes by the Kruskal–Wallis test. Although a monotone increasing pattern with a number of alleles is expected for PK-related genes, the Kruskal–Wallis test does not consider a monotonic response pattern. For detecting such patterns in clinical and toxicological trials, a maximum contrast method has been proposed. We show how that method can be used with pharmacogenomics data to a develop test of association. Further, using simulation studies, we compare the power of the modified maximum contrast method to those of the maximum contrast method and the Kruskal–Wallis test. On the basis of the results of those studies, we suggest rules of thumb for which statistics to use in a given situation. An application of all three methods to an actual genome-wide pharmacogenomics study illustrates the practical relevance of our discussion.

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Acknowledgements

We thank Professor Isao Yoshimura and Professor Chikuma Hamada at Tokyo University of Science for their valuable advice, and Dr Hiromi Sakamoto and Ms Sumiko Ohnami for the SNP genotyping. Yasunori Sato is a recipient of Official Trainee of the Foreign Clinical Pharmacology Training Program, Japanese Society of Clinical Pharmacology and Therapeutics. This work was initiated while Yasunori Sato was a postdoctoral fellow at the Department of Biostatistics, Harvard School of Public Health, and partially supported in Japan by the program for promotion of Fundamental Studies in Health Sciences of the National Institute of Biomedical Innovation (NiBio).

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Authors and Affiliations

  1. Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA

    Y Sato & N M Laird

  2. Genetics Division, National Cancer Center Research Institute, Tokyo, Japan

    Y Sato & T Yoshida

  3. Faculty of Engineering, Tokyo University of Science, Tokyo, Japan

    K Nagashima & R Kato

  4. Hamano Statistical Analysis Ltd., Tokyo, Japan

    T Hamano

  5. Clinic Sendagaya, Tokyo, Japan

    A Yafune

  6. Project Team for Pharmacogenetics, National Institute of Health Sciences, Tokyo, Japan

    N Kaniwa, Y Saito, E Sugiyama, S-R Kim & J-i Sawada

  7. Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan

    N Kaniwa & E Sugiyama

  8. Division of Functional Biochemistry and Genomics, National Institute of Health Sciences, Tokyo, Japan

    Y Saito & J-i Sawada

  9. Hepatobiliary and Pancreatic Oncology Division, National Cancer Center Hospital East, Chiba, Japan

    J Furuse & H Ishii

  10. Hepatobiliary and Pancreatic Oncology Division, National Cancer Center Hospital, Tokyo, Japan

    H Ueno & T Okusaka

  11. National Cancer Center Hospital East, Chiba, Japan

    N Saijo

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  1. Y Sato
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  2. N M Laird
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  3. K Nagashima
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  7. N Kaniwa
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  16. J-i Sawada
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  17. T Yoshida
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Corresponding author

Correspondence to T Yoshida.

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None declared.

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Sato, Y., Laird, N., Nagashima, K. et al. A new statistical screening approach for finding pharmacokinetics-related genes in genome-wide studies. Pharmacogenomics J 9, 137–146 (2009). https://doi.org/10.1038/tpj.2008.17

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  • DOI: https://doi.org/10.1038/tpj.2008.17

Keywords

  • gemcitabine
  • genome-wide study
  • maximum contrast method
  • pharmacokinetics-related gene
  • statistical screening method

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