Original Article | Published:

A model of prediction system for adverse cardiovascular reactions by calcineurin inhibitors among patients with renal transplants using gene-based single-nucleotide polymorphisms

Journal of Human Genetics volume 50, pages 442447 (2005) | Download Citation

Abstract

The application of pharmacogenomic information to diagnostic assays is expected to improve the prediction of drug efficacy and toxicity, leading to appropriate therapeutic regimens for individual patients. Cardiovascular events are common and severe adverse drug reactions (ADRs) among transplant patients treated with calcineurin inhibitors (CNIs). We conducted case-control association studies using 50,947 gene-based single-nucleotide polymorphisms (SNPs) to identify genetic variations that might be associated with cardiovascular risk factors in 72 renal transplant recipients with CNI therapy. The overall incidence of cardiovascular events was 13.9% (10/72) among patients receiving cyclosporine or tacrolimus; arrhythmias in six patients (8.3%), ischemic heart diseases in two patients (2.8%), and heart failure in two patients (2.8%). On the basis of results of the genome-wide association studies, we attempted to establish a scoring system to predict individual risks for cardiovascular toxicity of cyclosporine and tacrolimus. Estimation of the predictive performance was carried out by the use of internal leave-one-out cross-validation test. When we combined arrhythmia, ischemic heart disease and heart failure cases as subjects with a cardiotoxicity phenotype, nine of ten ADR patients and 50 of 62 non-ADR patients were correctly classified into the respective categories using the top eight SNPs. In addition, the proportion of individuals in the control population (n=246) with scores over the cut-off (11.0%) was close to the cardiovascular ADR frequency (8.3%) among renal transplant patients in the previous clinical study. Our results open the possibility that prediction of CNI-induced cardiovascular complications can lead to better prognosis and quality of life among kidney-transplant patients, and to improved immunosuppressive regimens.

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Affiliations

  1. Laboratory for Pharmacogenetics, SNP Research Center, The Institute of Physical and Chemical Research (RIKEN), Tokyo, Japan

    • Taisei Mushiroda
    •  & Yusuke Nakamura
  2. Laboratory for SNP Analysis, SNP Research Center, The Institute of Physical and Chemical Research (RIKEN), 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan

    • Susumu Saito
    •  & Yozo Ohnishi
  3. Department of Surgery and Bioengineering, Advanced Clinical Research Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan

    • Yukiko Tanaka
    • , Yoshifumi Beck
    •  & Hideaki Tahara
  4. Laboratory of Statistical Analysis, SNP Research Center, The Institute of Physical and Chemical Research (RIKEN), Tokyo, Japan

    • Junichi Takasaki
    •  & Naoyuki Kamatani
  5. Division of Genomic Medicine, Department of Applied Biomedical Engineering and Science, and Institute of Rheumatology, Tokyo Women's Medical University, Tokyo, Japan

    • Naoyuki Kamatani
  6. Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan

    • Yusuke Nakamura

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Corresponding author

Correspondence to Yozo Ohnishi.

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DOI

https://doi.org/10.1007/s10038-005-0275-3

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