Research

These are our primary areas of research and also the most likely broad project areas for new members of the team.

Nearly all chronic diseases that cause the greatest health burden have complex etiologies. It is a long-standing goal of biomedicine to subtype these diseases based on biological processes, rather than clinical presentation. The objective of this project is to discover, understand, and measure mechanistically meaningful subtypes (called endotypes) of a range of diseases with diverse clinical presentations and pathologies.

We integrate genomic, metabolomic, proteomic and healthcare data from over a million individuals in multiple national biobanks. We develop machine learning methods to learn interpretable (as opposed to merely predictive) signatures of disease risk, progression and treatment response. To understand the biological basis of these signatures and identify endotypes we use explainable AI, functional genomics, and disease-associated genetic variants of large effect.

When individuals start taking a new drug, they experience biological cascades that potentially drive both its therapeutic efficacy and the possibility of severe side effects. It may be possible to measure these biological changes using high throughput proteomics on readily accessibly blood samples, and use those observations to identify individuals most likely to benefit from treatment, or conversely at greatest risk of side effects.

This approach is increasingly showing promising results in samples from clinical trials, and we are excited to test the same concepts using real world data and samples from the Finnish biobank system.

This area of research is a collaboration with Andrea Ganna’s Data Science - Genetic Epidemiology Lab.

Selected papers from Jeff’s previous research. View the full list here.

• Nightingale Health Biobank Collaborative Group. Metabolomic and genomic prediction of common diseases in 700,217 participants in three national biobanks. Nature Communications. 2024 Nov 21;15(1):10092. doi:10.1038/s41467-024-54357-0

• Vöhringer HS, Sanderson T, Sinnott M, De Maio N, Nguyen T, Goater R, …, Birney E, Volz E, Funk S, Kwiatkowski D, Chand M, Martincorena I, Barrett JC^*, Gerstung M^*. Genomic reconstruction of the SARS-CoV-2 epidemic in England. Nature. 2021 Dec;600(7889):506-511. doi:10.1038/s41586-021-04069-y

• Martin HC, Jones WD, McIntyre R, …, Wright CF, FitzPatrick DR, Firth HV, Hurles ME, Barrett JC. Quantifying the contribution of recessive coding variation to developmental disorders. Science. 2018 Dec 7;362(6419):1161-1164. doi:10.1126/science.aar6731

• Niemi MEK, Martin HC, Rice DL, Gallone G, Gordon S, Kelemen M, McAloney K, McRae J, Radford EJ, Yu S, Gecz J, Martin NG, Wright CF, Fitzpatrick DR, Firth HV, Hurles ME, Barrett JC. Common genetic variants contribute to risk of rare severe neurodevelopmental disorders. Nature. 2018 Oct;562(7726):268-271. doi:10.1038/s41586-018-0566-4

• Singh T, Walters JTR, Johnstone M, Curtis D, Suvisaari J, Torniainen M, Rees E, Iyegbe C, Blackwood D, McIntosh AM, Kirov G, Geschwind D, Murray RM, Di Forti M, Bramon E, Gandal M, Hultman CM, Sklar P; INTERVAL Study; UK10K Consortium; Palotie A, Sullivan PF, O’Donovan MC, Owen MJ, Barrett JC. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat Genet. 2017 Aug;49(8):1167-1173. doi:10.1038/ng.3903

• Singh T, Kurki MI, Curtis D, Purcell SM, …, O’Donovan MC, Palotie A, Owen MJ, Barrett JC. Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat Neurosci. 2016 Apr;19(4):571-7. doi:10.1038/nn.4267

• Huang H, Fang M, Jostins L, Umićević Mirkov M, …, Mathew CG, Rioux JD, McGovern DPB, Cho JH, Georges M, Daly MJ^*, Barrett JC^*. Fine-mapping inflammatory bowel disease loci to single-variant resolution. Nature. 2017 Jul 13;547(7662):173-178. doi:10.1038/nature22969

• Jostins L, Ripke S, Weersma RK, Duerr RH, …, Daly MJ, Franke A, Parkes M, Vermeire S, Barrett JC^*, Cho JH^*. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012 Nov 1;491(7422):119-24. doi:10.1038/nature11582

* shared senior author