Burgess Group
Summary¶
The Burgess Group is a statistical genomics and causal inference research group led by Stephen Burgess at the University of Cambridge. The group is split between the MRC Biostatistics Unit (BSU) and the Cardiovascular Epidemiology Unit (CEU) in the Department of Public Health and Primary Care. Their work focuses on developing and applying statistical methods for causal inference in epidemiology, with a primary emphasis on Mendelian randomization and multi-trait colocalization.
Research Areas¶
- Mendelian Randomization: Developing mathematical models and software for utilizing genetic variants as instrumental variables to estimate causal effects from observational data. This includes maintaining the MendelianRandomization R package.
- Multi-trait Colocalization: Developing algorithms like HyPrColoc to scale colocalization analyses across multiple clinical, metabolic, and molecular traits.
- Cardiometabolic Disease Epidemiology: Integrating multi-omics, genetic risk, and clinical trials data to elucidate causal pathways for coronary heart disease and diabetes.
Citations¶
- MRC Biostatistics Unit Group Page: https://www.mrc-bsu.cam.ac.uk/people/group-leaders/stephen-burgess/ (as of 2026-07-19)
- Key Publication: Foley, C. N., Staley, J. R., Breen, P. G., Sun, B. B., Kirk, P. D. W., Burgess, S., & Howson, J. M. M. (2021). A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits. Nature Communications, 12(1), 764. DOI: 10.1038/s41467-020-20885-8. Source paper: s41467-020-20885-8.pdf
- Ingestion Reference: Sanderson, E. et al. (2026). Challenges and future directions for Mendelian randomization. Nature Genetics, 58(5), 984–994. DOI: 10.1038/s41588-026-02546-6. Source paper: s41588-026-02546-6.pdf