University of Leicester
Browse
DOCUMENT
Supplementary.docx (18.94 kB)
DOCUMENT
Pingault_V2_PRR_DB3_1524574686_73_FD.pdf (770.98 kB)
1/0
2 files

Using genetic data to strengthen causal inference in observational research.

Download all (789.92 kB)
journal contribution
posted on 2018-08-10, 11:28 authored by Jean-Baptiste Pingault, Paul F. O'Reilly, Tabea Schoeler, George B. Ploubidis, Frühling Rijsdijk, Frank Dudbridge
Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.

Funding

The authors thank S. Gage and J. M. Vink for cannabis initiation summary statistics and syntax and J. Rees for multivariable Mendelian randomization (MR) syntax. J.-B.P. is a fellow of MQ: Transforming Mental Health (MQ16IP16) and affiliated with the Centre for Research in Epidemiology and Population Health (CESP), French National Institute for Health and Medical Research (INSERM), Université de Paris-Sud, Université de Versailles-Saint Quentin, and Université Paris-Saclay, Paris, France. P.F.O. receives funding from the UK Medical Research Council (MR/N015746/1) and the Wellcome Trust (109863/Z/15/Z). This report represents independent research (partly) funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service (NHS) Foundation Trust and King’s College London.

History

Citation

Nature Reviews Genetics, 2018

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health Sciences

Version

  • AM (Accepted Manuscript)

Published in

Nature Reviews Genetics

Publisher

Nature Publishing Group

issn

1471-0056

eissn

1471-0064

Copyright date

2018

Available date

2018-12-05

Publisher DOI

Publisher version

https://www.nature.com/articles/s41576-018-0020-3

Notes

Supplementary information is available for this paper at https://doi.org/10.1038/s41576-018-0020-3;The file associated with this record is under embargo until 6 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

Administrator link

Usage metrics

    University of Leicester Publications

    Categories

    No categories selected

    Keywords

    IR content

    Licence

    All Rights Reserved

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC