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Exploring Autoimmune Diseases with GWAS

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Jeffrey Barrett
Title: Junior Investigator, Wellcome Trust Sanger Institute
Education: PhD, University of Oxford, 2008
Recommended by: Richard Durbin

Jeffrey Barrett got his first taste of human genetics research during his undergraduate days in Mark Daly's lab at the Whitehead Institute. After graduating with a bachelor's degree in physics in 2002, he continued to work with Daly on the HapMap project and developed software tools such as the Haploview program, a widely used application that expedites the process of haplotype analysis. Three years later, Barrett decided to pursue his graduate degree in statistics at Oxford University, where he worked as a member of the analysis team for the Wellcome Trust Case Control Consortium. There, he led the analysis of the replication effort in Crohn's disease.

After finishing his postdoctoral studies, Barrett came on board at the Wellcome Trust Sanger Institute in November 2008 to start his own statistical and computational genetics team. In his capacity as a junior investigator, Barrett works on the design and analysis of complex gene hunting using genome-wide association studies of auto-inflammatory diseases, such as inflammatory bowel disease and type 1 diabetes. He is also involved in two international consortiums, the 1,000 Genomes Project and the International IBD Genetics Consortium. "Here at the Sanger, we're building up our expertise in the statistical and computational side of those analyses, both with on-going genome-wide association studies and genome-wide sequencing disease studies," Barrett says.

He is definitely happy about the trajectory of his young career, noting that Sanger is a great place to be when starting out. "One of the benefits of being at the Sanger is that we get to have access to the institute's pretty enormous sequencing and genotyping capacities," he says.

Looking ahead

The transition from SNP chips of half a million to a million SNPs to having a complete sequence, not to mention hundreds or thousands of disease samples, is a computational and statistical hurdle he and his colleagues are going to face. "The big challenge a lot of us are thinking about is how to condense huge amounts of sequence data into some distilled, relevant thing," says Barrett. "Combining information about many distinct, rare mutations in different cases that are all saying the same gene but each one is in a different location is something everyone is trying to think of the right way to do."

Despite those headaches, having easy access to those complete sequences is going to push his research to the next level of discovery. "We've had a great deal of success in identifying genes that confer weak risk for a whole lot of different human traits," Barrett says. "But we would really like to move into understanding the functional biological connection between the DNA variation and the phenotype variation and having the sequence that's going to enable us to get much closer than that in a lot of cases."

Publications of note

A good example of Barrett's work is "Genome-wide -association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes," a paper that appeared in Nature Genetics this past May. In it, he and his colleagues report the findings of their genome-wide association study of type 1 diabetes, which they combined in a meta-analysis with two previously published studies. The end results of their study suggested several new candidate genes.

And the Nobel goes to...

Barrett would like to accept his Nobel for establishing some "understanding of how so many of the associations we discover [that are linked] to disease are not acting through the coding sequence — for example, 80 percent of the things we find that give you risk for disease don't seem to have anything to do with changing the sequence of proteins."

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