IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-09407-3.html
   My bibliography  Save this article

Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects

Author

Listed:
  • Phuong A. Nguyen

    (Amgen, Inc.)

  • David A. Born

    (Amgen, Inc.)

  • Aimee M. Deaton

    (Amgen, Inc.)

  • Paul Nioi

    (Amgen, Inc.
    Alnylam Pharmaceuticals, Inc.)

  • Lucas D. Ward

    (Amgen, Inc.
    Alnylam Pharmaceuticals, Inc.)

Abstract

Only a small fraction of early drug programs progress to the market, due to safety and efficacy failures, despite extensive efforts to predict safety. Characterizing the effect of natural variation in the genes encoding drug targets should present a powerful approach to predict side effects arising from drugging particular proteins. In this retrospective analysis, we report a correlation between the organ systems affected by genetic variation in drug targets and the organ systems in which side effects are observed. Across 1819 drugs and 21 phenotype categories analyzed, drug side effects are more likely to occur in organ systems where there is genetic evidence of a link between the drug target and a phenotype involving that organ system, compared to when there is no such genetic evidence (30.0 vs 19.2%; OR = 1.80). This result suggests that human genetic data should be used to predict safety issues associated with drug targets.

Suggested Citation

  • Phuong A. Nguyen & David A. Born & Aimee M. Deaton & Paul Nioi & Lucas D. Ward, 2019. "Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09407-3
    DOI: 10.1038/s41467-019-09407-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-09407-3
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-019-09407-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09407-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.