Mendelian Randomization

Course dates

Due to demand, this 3 day course will run twice:

  • 19 - 21 March 2018
  • 10 - 12 July 2018

Course duration

3 days (approximately 18 hours teaching). The course will comprise of around 50% lectures, 40% practicals and 10% group discussions.
Registration will start at 9am on the first day, the course will finish by 5pm on the final day.

Course tutors

Professor Debbie Lawlor, Dr Kaitlin Wade (course organisers) and others.

Course aims 

Mendelian randomization is a study that uses genetic variants as instrumental variables to test the causal effect of a (non-genetic) risk factor on a disease or health related outcome. Since its first proposal in 2003 it has been increasingly used to determine population causal effects using observational data. It is used in a large amount of the applied research in the MRC Integrative Epidemiology Unit (IEU) and throughout Population Health at the University of Bristol Medical School. Academics working in the IEU and Bristol University (including those who are tutors on this course) have been at the forefront of developing methods for assessing and limiting potential biases with this approach.    

This course aims to provide an introduction to the conduct, assumptions, strengths and limitations of Mendelian randomization, including the use of up-to-date methods for sensitivity analyses that explore likely violation of Mendelian randomization assumptions.    

This is a beginners to intermediate level course. Students will learn about one-sample and two-sample Mendelian randomization, including their assumptions and gaining practical experience of how to apply these methods to real data. They will also learn about a range of sensitivity analyses that explore likely violation of the assumptions of Mendelian randomization.  Prior experience of using Mendelian randomization is not required, but participants should have an understanding of aetiological epidemiological principles, and ideally be working on causal population health questions.

Course objectives

By the end of the course students will:

  • understand the principles and assumptions of instrumental variable analyses;
  • understand the properties of genetic variants that make them suitable to be used as instrumental variables;
  • understand the strengths and limitations of one-sample and two-sample Mendelian randomization for addressing population health causal questions;
  • be able to complete a (straight-forward) one-sample and two-sample Mendelian randomization analysis;
  • understand the concepts behind sensitivity analyses to test for potential violation of the key assumptions of Mendelian randomization;
  • be able to apply up-to-date sensitivity analyses in one- and two-sample Mendelian randomization analyses.

Who the course is intended for

The course is intended for anyone who wants to be able to undertake Mendelian randomization analyses. It is an introductory to intermediate course. However, as Mendelian randomization is an advanced epidemiological / statistical method, those intending to take this course should already understand epidemiological principles and have knowledge and skills in statistical analysis to the level of running, and correctly interpreting results, from multivariable regression analyses. They must have experience in running such analyses efficiently in Stata or R as all practicals on the course will be run in Stata or R and the focus of these practicals will be on Mendelian randomization (not learning how to use the statistical packages).
[Note: it is not necessary for those participating in the course to be able to use both Stata and R, but they must be able to use one of these].    

The course will not include any genetic epidemiology teaching, how to undertake a genome wide association study. However, genetic epidemiology and the ability to complete a genome-wide association study are NOT a pre-requisite for being able to understand this course. The course will not cover more complex Mendelian randomization methods such as two-step or network Mendelian randomization.

Please note: Practical sessions of this course will be held in a computer lab, so you will not need to bring a laptop. Both Stata and R will be used during the course. (NOTE: students must be able to efficiently use ONE of these two analysis packages).

Recommended reading

1. Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Statistics in Medicine 2008; 27: 1133-63.  

2. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal of Epidemiology 2015; 512–525. doi: 10.1093/ije/dyv080.  

3. Lawlor DA. Two-sample Mendelian randomization: opportunities and challenges. International Journal of Epidemiology 2016; 908–915. doi: 10.1093/ije/dyw127.  

4. Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. American Journal of Clinical Nutrition 2016; 103: 965–78.  


Make a booking

July 2018 - this course is now fully booked.

This was an excellent introduction to MR with motivation and methods well explained and lots of time for discussion and practical exploration of the techniques.

Course feedback, February 2017

Course fee


More information on course fees, fee waivers and reduced prices.

Course venue

March 2018
Bristol Medical School
Canynge Hall
39 Whatley Road
United Kingdom

Map and directions

July 2018
School of Experimental Psychology
12a Priory Road
United Kingdom

Map and directions

Course refreshments

We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.

If you have specific dietary needs we ask that you let us know in advance.

Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch. 


Information about accommodation in the area.

Related short courses


For further information please email

Edit this page