Mendelian Randomization Course

Overview: We regularly run a three-week course on Mendelian randomization based on our book “Mendelian randomization: Methods for Causal Inference Using Genetic Variants”.

The course will be run on our online learning platform. Further information about the course, including an up-to-date timetable, can be found on the group website.

The next course will be in March 2023. Registration is now open HERE.

Course overview: Studies based on Mendelian randomization are increasingly being used to distinguish causal relationships from observational associations in epidemiology and to prioritize potential targets for pharmaceutical intervention. This course intends to explain both simple and more complex statistical methods for causal inference in Mendelian randomization studies, and the instrumental variable assumptions on which they are based.

The course includes several computing practicals in R and attendees are expected to bring a laptop with R installed.

Intended audience: Medical / applied / pharmaceutical statisticians, and quantitative epidemiologists. The course material is relevant to causal inference in a wide range of fields including epidemiology, drug development and social sciences, and would be particularly suitable for a PhD or post-doc about to start a project using Mendelian randomization.

Prerequisites: Knowledge of applied statistical methods used in epidemiological studies is assumed (e.g. epidemiological study designs, multiple logistic regression). No prior knowledge of genetics, instrumental variable techniques, or Mendelian randomization is necessary.

Computing practicals: Participants will gain most from the practicals if they have a working knowledge of R. We are happy for participants to use other statistical software packages (e.g. Stata), but we may not be able to support users as effectively.

Course objectives: After the course, participants should have sufficient knowledge to undertake their own Mendelian randomization analyses, to understand the assumptions on which causal inferences are based, and to critically appraise published studies using Mendelian randomization.

Software download: Details of software to be downloaded for use on the course practicals will be given to course participants. It should ideally be downloaded and installed prior to the course, but please do not worry if there are any problems with the software as there will be an opportunity for software assistance during the course.

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Online course: The course will be delivered via the Moodle online learning platform.

The course consists of four half-days worth of content plus the final hackathon, and will take place over 3 weeks (plus a preliminary week 0). It will consist of some on-demand pre-recorded content and some timetabled (live) content. All the core content of the course is pre-recorded – live sessions are not compulsory to attend, but are supplementary to the core content. They represent a chance to engage with the course tutors. Several of the live sessions will be recorded.

Each half-day can be done whenever is convenient. A half-day of content includes three pre-recorded talks (around 20-30 minutes each) and one practical session (around 1-1.5 hour). Each of the three computer practicals should be performed individually, but there is an associated live drop-in session to come and ask questions. There is also a recorded debrief session that runs through the practical content. In terms of live content, in addition to the practical drop-in sessions, paper discussion, and hackathon, there is also a question and answer session each week to ask your questions. Questions can be asked during the week on a dedicated Slack channel, or you can ask questions live (Q+A sessions will be recorded).

The hackathon is an opportunity to perform your own Mendelian randomization investigation to use the skills you have gained during the course. This can be done individually or as part of a group.

Participants should choose one of the papers for the timetabled paper discussion (Practical 3), and one hackathon session, based on their availability and preference.

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Course tutors:

• Stephen Burgess (MRC Biostatistics Unit and Cardiovascular Epidemiology Unit, University of Cambridge)
• Verena Zuber (Imperial College London)
• Eric Slob (MRC Biostatistics Unit, University of Cambridge)
• Andrew Grant (MRC Biostatistics Unit, University of Cambridge)
• Amy Mason (Cardiovascular Epidemiology Unit, University of Cambridge)
• Dipender Gill (Imperial College London)

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Contact: For any queries relating to the course, please email burgess-group-admin@mrc-bsu@cam.ac.uk