IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-16969-0.html
   My bibliography  Save this article

Genetic drug target validation using Mendelian randomisation

Author

Listed:
  • Amand F. Schmidt

    (University College London
    UCL BHF Research Accelerator Centre
    University Medical Center Utrecht)

  • Chris Finan

    (University College London
    UCL BHF Research Accelerator Centre)

  • Maria Gordillo-Marañón

    (University College London)

  • Folkert W. Asselbergs

    (University College London
    University Medical Center Utrecht
    Health Data Research UK)

  • Daniel F. Freitag

    (Bayer AG Pharmaceuticals, Open Innovation & Digital Technologies)

  • Riyaz S. Patel

    (University College London
    UCL BHF Research Accelerator Centre)

  • Benoît Tyl

    (Institut de Recherches Internationales Servier)

  • Sandesh Chopade

    (University College London
    UCL BHF Research Accelerator Centre)

  • Rupert Faraway

    (University College London
    UCL BHF Research Accelerator Centre
    The Francis Crick Institute)

  • Magdalena Zwierzyna

    (University College London
    UCL BHF Research Accelerator Centre)

  • Aroon D. Hingorani

    (University College London
    UCL BHF Research Accelerator Centre
    Health Data Research UK)

Abstract

Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the ‘no horizontal pleiotropy assumption’ is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses.

Suggested Citation

  • Amand F. Schmidt & Chris Finan & Maria Gordillo-Marañón & Folkert W. Asselbergs & Daniel F. Freitag & Riyaz S. Patel & Benoît Tyl & Sandesh Chopade & Rupert Faraway & Magdalena Zwierzyna & Aroon D. Hi, 2020. "Genetic drug target validation using Mendelian randomisation," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16969-0
    DOI: 10.1038/s41467-020-16969-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-16969-0
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-16969-0?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. Jie Ma & Yang Li & Ping Li & Xinying Yang & Shuolin Zhu & Ke Ma & Fei Gao & Hai Gao & Hui Zhang & Xin-liang Ma & Jie Du & Yulin Li, 2024. "S100A8/A9 as a prognostic biomarker with causal effects for post-acute myocardial infarction heart failure," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. María Gordillo-Marañón & Magdalena Zwierzyna & Pimphen Charoen & Fotios Drenos & Sandesh Chopade & Tina Shah & Jorgen Engmann & Nishi Chaturvedi & Olia Papacosta & Goya Wannamethee & Andrew Wong & Ree, 2021. "Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    3. Anders Mälarstig & Felix Grassmann & Leo Dahl & Marios Dimitriou & Dianna McLeod & Marike Gabrielson & Karl Smith-Byrne & Cecilia E. Thomas & Tzu-Hsuan Huang & Simon K. G. Forsberg & Per Eriksson & Mi, 2023. "Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Lucas A. Mavromatis & Daniel B. Rosoff & Andrew S. Bell & Jeesun Jung & Josephin Wagner & Falk W. Lohoff, 2023. "Multi-omic underpinnings of epigenetic aging and human longevity," Nature Communications, Nature, vol. 14(1), pages 1-15, 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:11:y:2020:i:1:d:10.1038_s41467-020-16969-0. 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.