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Linking MedDRA®-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors

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Abstract

Introduction

A translational bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.

Objectives

The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity.

Results

Statistical analysis of FAERS data identified 1053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA® and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed “cardiac failure” using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction.

Conclusion

By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA® provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms.

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Acknowledgments

The authors thank Zuoshuang Xiang for his programming assistance in building OAE.

Author information

Authors and Affiliations

  1. Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA

    Sirarat Sarntivijai, Shadia Zaman, Keith K. Burkhart & Darrell R. Abernethy

  2. College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA

    Shelley Zhang

  3. College of Engineering, University of Michigan, Ann Arbor, MI, USA

    Desikan G. Jagannathan

  4. Unit of Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, USA

    Yongqun He

  5. Department of Internal Medicine and Human Genetics and School of Public Health, University of Michigan, Ann Arbor, MI, USA

    Gilbert S. Omenn

  6. Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA

    Sirarat Sarntivijai, Gilbert S. Omenn, Yongqun He & Brian D. Athey

  7. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    Gilbert S. Omenn & Brian D. Athey

  8. Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA

    Yongqun He

  9. Psychiatry Department, University of Michigan, Ann Arbor, MI, USA

    Brian D. Athey

Authors
  1. Sirarat Sarntivijai
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  2. Shelley Zhang
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  9. Darrell R. Abernethy
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Corresponding author

Correspondence to Sirarat Sarntivijai.

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Funding

This work was supported by the Oak Ridge Institute for Science and Education (ORISE) (Sirarat Sarntivijai), the Undergraduate Research Opportunity Program at the University of Michigan (Shelley Zhang, Desikan Jagannathan, Yongqun He), the Food and Drug Administration (FDA) Commissioner’s Fellowship Program (Shadia Zaman), National Institute of Environmental Health Sciences (NIEHS) Grant Number P30ES017885-01A1 (Gilbert Omenn), National Institutes of Health (NIH) Grant Numbers U54 DA021529 and UL1 TR000433-09 (Brian Athey), and National Institute of Allergy and Infectious Disease (NIAID) Grant Number R01 AI081062 (Yongqun He).

Conflict of interest

Sirarat Sarntivijai, Shelley Zhang, Desikan Jagannathan, Shadia Zaman, Keith Burkhart, Gilbert Omenn, Yongqun He, Brian Athey, and Darrell Abernethy have no conflicts of interest that are directly relevant to the content of this study.

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Sarntivijai, S., Zhang, S., Jagannathan, D.G. et al. Linking MedDRA®-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors. Drug Saf 39, 697–707 (2016). https://doi.org/10.1007/s40264-016-0414-0

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