IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v9y2018i1d10.1038_s41467-018-06540-3.html
   My bibliography  Save this article

Phenome-wide association studies across large population cohorts support drug target validation

Author

Listed:
  • Dorothée Diogo

    (Merck Sharp & Dohme)

  • Chao Tian

    (23andMe Inc)

  • Christopher S. Franklin

    (Genomics plc)

  • Mervi Alanne-Kinnunen

    (University of Helsinki)

  • Michael March

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Chris C. A. Spencer

    (Genomics plc)

  • Ciara Vangjeli

    (Genomics plc)

  • Michael E. Weale

    (Genomics plc)

  • Hannele Mattsson

    (University of Helsinki
    National Institute for Health and Welfare)

  • Elina Kilpeläinen

    (University of Helsinki)

  • Patrick M. A. Sleiman

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Dermot F. Reilly

    (Merck Sharp & Dohme)

  • Joshua McElwee

    (Merck Sharp & Dohme
    Nimbus Therapeutics)

  • Joseph C. Maranville

    (Merck Sharp & Dohme
    Celgene)

  • Arnaub K. Chatterjee

    (Merck Sharp & Dohme
    McKinsey & Co.)

  • Aman Bhandari

    (Merck Sharp & Dohme
    Vertex Pharmaceuticals)

  • Khanh-Dung H. Nguyen

    (Biogen, Research and Early Development)

  • Karol Estrada

    (Biogen, Research and Early Development)

  • Mary-Pat Reeve

    (Eisai)

  • Janna Hutz

    (Eisai)

  • Nan Bing

    (Pfizer)

  • Sally John

    (Biogen, Research and Early Development)

  • Daniel G. MacArthur

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • Veikko Salomaa

    (National Institute for Health and Welfare)

  • Samuli Ripatti

    (University of Helsinki
    Broad Institute of MIT and Harvard
    University of Helsinki)

  • Hakon Hakonarson

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Mark J. Daly

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • Aarno Palotie

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Massachusetts General Hospital)

  • David A. Hinds

    (23andMe Inc)

  • Peter Donnelly

    (Genomics plc)

  • Caroline S. Fox

    (Merck Sharp & Dohme)

  • Aaron G. Day-Williams

    (Merck Sharp & Dohme
    Biogen, Research and Early Development)

  • Robert M. Plenge

    (Merck Sharp & Dohme
    Celgene)

  • Heiko Runz

    (Merck Sharp & Dohme
    Biogen, Research and Early Development)

Abstract

Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P

Suggested Citation

  • Dorothée Diogo & Chao Tian & Christopher S. Franklin & Mervi Alanne-Kinnunen & Michael March & Chris C. A. Spencer & Ciara Vangjeli & Michael E. Weale & Hannele Mattsson & Elina Kilpeläinen & Patrick , 2018. "Phenome-wide association studies across large population cohorts support drug target validation," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06540-3
    DOI: 10.1038/s41467-018-06540-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-06540-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-018-06540-3?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Patrick Wu & QiPing Feng & Vern Eric Kerchberger & Scott D. Nelson & Qingxia Chen & Bingshan Li & Todd L. Edwards & Nancy J. Cox & Elizabeth J. Phillips & C. Michael Stein & Dan M. Roden & Joshua C. D, 2022. "Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

    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:9:y:2018:i:1:d:10.1038_s41467-018-06540-3. 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.