Barrett Team

Medical Genomics

Archive Page

This page is maintained as a historical record and is no longer being updated.

Jeff Barrett left the Sanger Institute in 2018 to become Chief Scientific Officer for Genomics Plc. This page is being maintained as historical record of the research group’s work at the Sanger Institute and is no longer being updated.

The Barrett team studied how genetic variation affects risk for diseases, and finds ways to apply that knowledge to improve health care. We analyzed genome-wide association studies and next-generation sequence data collected on thousands of individuals, and developed statistical and computational methods for these analyses.

For most common human diseases it is impossible to predict with certainty whether any particular person will become sick, or even to explain the causes of an illness after it has occurred. A person’s total risk for common, complex diseases such as heart disease is a combination of their unique genetic make-up and their environment and behaviour. The challenge of human disease genetics is to translate genetic experiments into an understanding of the underlying biology of human disease.

We were involved in a number of first generation genome-wide association studies (GWAS), including the Wellcome Trust Case Control Consortium (WTCCC). Because the number of samples involved in GWAS is directly linked to the power to detect weak association signals we have led meta-analyses of multiple GWAS in type 1 diabetes and inflammatory bowel disease.

While the discovery of so many associations to common human disease has generated a great deal of excitement, we still face the critical challenge of translating that information into a deeper understanding of biology. We worked both on methods to find causal mutations in associated regions (which are usually implicated by a nearby variant in linkage disequilibrium) as well as collaborative work within the Institute to understand what happens to experimental organisms when the newly discovered loci are disrupted.