Composite Kernel Association Test (CKAT) for SNP-set joint assessment of genotype and genotype-by-treatment interaction in Pharmacogenetics studies.

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    • Source:
      Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
    • Publication Information:
      Original Publication: Oxford : Oxford University Press, c1998-
    • Subject Terms:
    • Abstract:
      Motivation: It is of substantial interest to discover novel genetic markers that influence drug response in order to develop personalized treatment strategies that maximize therapeutic efficacy and safety. To help enable such discoveries, we focus on testing the association between the cumulative effect of multiple single nucleotide polymorphisms (SNPs) in a particular genomic region and a drug response of interest. However, the currently existing methods are either computational inefficient or not able to control type I error and provide decent power for whole exome or genome analysis in Pharmacogenetics (PGx) studies with small sample sizes.
      Results: In this article, we propose the Composite Kernel Association Test (CKAT), a flexible and robust kernel machine-based approach to jointly test the genetic main effect and SNP-treatment interaction effect for SNP-sets in Pharmacogenetics (PGx) assessments embedded within randomized clinical trials. An analytic procedure is developed to accurately calculate the P-value so that computationally extensive procedures (e.g. permutation or perturbation) can be avoided. We evaluate CKAT through extensive simulation studies and application to the gene-level association test of the reduction in Clostridium difficile infection recurrence in patients treated with bezlotoxumab. The results demonstrate that the proposed CKAT controls type I error well for PGx studies, is efficient for whole exome/genome association analysis and provides better power performance than existing methods across multiple scenarios.
      Availability and Implementation: The R package CKAT is publicly available on CRAN https://cran.r-project.org/web/packages/CKAT/.
      Supplementary Information: Supplementary data are available at Bioinformatics online.
      (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected].)
    • Molecular Sequence:
      ClinicalTrials.gov NCT01513239
    • Publication Date:
      Date Created: 20200227 Date Completed: 20201029 Latest Revision: 20220531
    • Publication Date:
      20221213
    • Accession Number:
      10.1093/bioinformatics/btaa125
    • Accession Number:
      32101275