Department: MRC Epidemiology Unit
Organisation: University of Cambridge
We develop and apply genomic and computational methods to investigate the genetic architecture of complex traits, including disease risk and drug response. We are interested in what can be learned from DNA sequence and multi-omics data about disease mechanism, therapeutic intervention, molecular evolution, and genome function.
We are interested in elucidating the genetic basis of human traits and diseases using novel computational methodologies, integrative analyses of heterogeneous multi-omics data, and innovative experimental approaches. A primary research focus is the development of methods in statistical and population genetics. The knowledge gained can be the basis for a genetics-driven forward pharmacology that enables identification of molecules with a desired phenotypic effect or mechanism of action. We leverage functional genomics to dissect the transcriptional regulatory logic and its context specificity in order to advance our understanding of biological mechanisms.
1. Zhou D, Jiang Y, Zhong X, Cox NJ, Liu C, Gamazon ER. (2020) A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis. Nature Genetics. doi: 10.1038/s41588-020-0706-2.
2. Gamazon ER, Segre AV, van de Bunt M, et al. (2018) Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. Nature Genetics. doi: 10.1038/s41588-018-0154-4.
3. Gamazon ER, Wheeler HE, Shah KP, et al. (2015) A gene-based association method for mapping traits using reference transcriptome data. Nature Genetics. doi: 10.1038/ng.3367.
4. Geeleher P, Gamazon ER, Seoighe C, et al. (2016) Consistency in large pharmacogenomic studies. Nature. doi: 10.1038/nature19838.
5. The GTEx Consortium* (2015) The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science. 348 (6235):648-660. *Gamazon ER was co-chair of the GTEx GWAS Working Group and a member of the GTEx Analysis Working Group.