Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian randomisation

Katikireddi, S. V. , Green, M. , Taylor, A. E., Smith, G. D. and Munafò, M. R. (2018) Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian randomisation. Addiction, 113(4), pp. 764-774. (doi:10.1111/add.14038) (PMID:28921935) (PMCID:PMC5873430)

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Abstract

Background and aims: Studying the consequences of addictive behaviours is challenging, with understanding causal relationships from observational data being particularly difficult. For example, people who smoke or drink excessively are often systematically different from those who do not, are less likely to participate in research, and may misreport their behaviours when they do. Furthermore, the direction of causation between an addictive behaviour and outcome may be unclear. Mendelian randomisation (MR) offers potential solutions to these problems. Methods: We describe MR's principles and the criteria under which it is valid. We identify challenges and potential solutions in its application (illustrated using two applied examples), and describe methodological extensions in its application. Results: MR is subject to certain assumptions, and requires the availability of appropriate genetic data, large sample sizes, and careful design and conduct. However, it has already been successfully applied to the addiction literature. The relationship between alcohol consumption (proxied by a variant in the ADH1B gene) and cardiovascular risk has been investigated, finding that alcohol consumption increases risk, with no evidence of a cardio-protective effect at moderate consumption levels. In addition, heaviness of smoking (proxied by a variant in the CHRNA5-A3-B4 gene cluster) and risk of depression and schizophrenia have been investigated, with no evidence of a causal effect of smoking on depression but some evidence of a causal effect on schizophrenia. Conclusions: Mendelian randomisation (MR) analyses are already producing robust evidence for addiction-related practice and policy. As genetic variants associated with addictive behaviours are identified, the potential for MR analyses will grow. Methodological developments are also increasing its applicability.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Katikireddi, Dr Srinivasa and Green, Dr Michael
Authors: Katikireddi, S. V., Green, M., Taylor, A. E., Smith, G. D., and Munafò, M. R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > MRC/CSO Unit
Journal Name:Addiction
Publisher:Wiley
ISSN:0965-2140
ISSN (Online):1360-0443
Published Online:17 September 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Addiction 113(4):764-774
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
699162Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiChief Scientist office (CSO)SCAF/15/02IHW - MRC/CSO SPHU
727651SPHSU Core Renewal: Measuring and Analysing Socioeconomic Inequalities in Health Research ProgrammeAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13IHW - MRC/CSO SPHU
727671SPHSU Core Renewal: Informing Healthy Public Policy Research ProgrammePeter CraigMedical Research Council (MRC)MC_UU_12017/15IHW - MRC/CSO SPHU