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Using genetic data to strengthen causal inference in observational research.
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 DudbridgeCausal 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, 2018Author affiliation
/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health SciencesVersion
- AM (Accepted Manuscript)