Abstract
Mendelian randomization (MR) is becoming a popular approach to estimate the causal effect of an exposure on an outcome overcoming limitations of observational epidemiology. The advent of genome-wide association studies and the increasing accumulation of summarized data from large genetic consortia make MR a powerful technique. In this review, we give a primer in MR methodology, describe efficient MR designs and analytical strategies, and focus on methods and practical guidance for conducting an MR study using summary association data. We show that the analysis is straightforward utilizing either the MR-base platform or available packages in R. However, further research is required for the development of specialized methodology to assess MR assumptions.
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Acknowledgements
NLD was supported by the IKY scholarship programme, which is co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the action entitled “Reinforcement of Postdoctoral Researchers” in the framework of the Operational Programme “Human Resources Development Program, Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) 2014 – 2020. KKT was supported by the World Cancer Research Fund International Regular Grant Programme (WCRF 2014/1180).
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Dimou, N.L., Tsilidis, K.K. (2018). A Primer in Mendelian Randomization Methodology with a Focus on Utilizing Published Summary Association Data. In: Evangelou, E. (eds) Genetic Epidemiology. Methods in Molecular Biology, vol 1793. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7868-7_13
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