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A Primer in Mendelian Randomization Methodology with a Focus on Utilizing Published Summary Association Data

  • Niki L. Dimou
  • Konstantinos K. TsilidisEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1793)

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.

Key words

Mendelian randomization Summarized data Instrumental variable Causal inference 

Notes

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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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
  2. 2.Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK

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