Mendelian Randomisation [GE10]
Monday to Wednesday
Jeremy Labrecque, Carolina Borges, Katerina Trajanoska, and Fernando Rivadeneira
Understanding of genetic epidemiology and Statistics (elementary probability, and regression analysis)
- Genetic Epidemiology
Detailed information about this course:
With the advent of a very large number of genetic databases and resources, opportunities to conduct Mendelian randomization(MR) studies are quickly increasing. The MR approach proposes using genetic variants as instrumental variables to test or estimate the potential causal effect of a (non-genetic) risk factor on a disease or health-related outcome. When the assumptions are met, the MR approach can overcome the limitations of associations drawn from observational epidemiology and help prioritizing potential targets for pharmaceutical and public health interventions. This 3-day course aims to provide all the tools necessary first to understand the basic principles of causal inference underlying MR and second to perform an MR study; covering both simple and complex statistical methods for causal inference within one- and two- sample Mendelian randomisation frameworks. During the first day, basic principles of causal inference and mediation analysis will be covered. On the second day, students will apply the concepts learned on day 1 within a Mendelian randomisation framework; including methods to assess instrumental variable assumptions and working on hands-on practical sessions employing online tools like MR-base, but also using specific R-libraries. During day 3, examples of published MR studies will be presented followed by discussion of the topics and a short Q&A session. In addition, students will be able to run specific hands-on analyses with diverse summary level datasets. While theoretical background is provided on all topics, this is by definition a "hands-on" practical course, meaning you will spend most of the day performing MR analyses." Starting this year, the GE10 course will be given on a yearly basis.
Faculty: Jeremy Labrecque, Caroline Bonilla, Katerina Trajanoska and Fernando Rivadeneira
- Gain insight into disentangling the concepts of causation and association;
- Learn aspects of design, execution and interpretation of MR studies;
- Get familiar with hands-on applications (used for 1-sample and 2-sample MR) commonly used across MR/GWAS consortia.
Epidemiologists, geneticists, biostatisticians, investigators/physicians involved in clinical and pharmacological research.
Reduction on fees
PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 EC points)
No fees are charged for participation of Erasmus MC PhD candidates
Please note that in case of cancellation or no show, the cancellation policy applies based on the full course fee.
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.
25% reduction on our fees for Erasmus MC employees
For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above and Erasmus MC PhD candidates).
25% reduction for all (international) PhD students without formal appointment at Erasmus MC
Upon receipt of your application you will receive a request to upload proof of enrollment as a PhD student.