Dr Jason Torres
- Mexico City Prospective Study: mapping genetic risk factors of major non-communicable diseases (MRC-PHRU)
- Mexico City Prospective Study: genetic determinants and cardio-metabolic consequences of kidney disease in a large population-based study of Mexican adults [MRC PHRU]
- Mexico City Prospective Study: leveraging genetic admixture and relatedness to advance rare variant discovery in Mexicans adults
Senior Genetic Epidemiologist
Jason Torres is a senior genetic epidemiologist in the Clinical Trial Service Unit & Epidemiological Studies Unit in the Nuffield Department of Population Health, where he leads genetic analyses of the Mexico City Prospective Study.
He analyses large-scale genetic data (i.e. genome-wide array, WGS, WES) with the aim of identifying genetic risk factors for complex diseases such as type 2 diabetes and related cardiometabolic traits. Through fine-mapping and data integrative methods, Jason elucidates underlying biological processes that mediate genetic susceptibility to disease onset and progression. Moreover, he leverages genetic information to construct and evaluate polygenic risk scores and to facilitate inference of causal risk factors through Mendelian randomisation.
Jason received his PhD at the University of Chicago where he conducted genome-wide association studies and heritability estimation. Before joining NPDH, he worked at the Wellcome Centre for Human Genetics in Oxford as a postdoctoral research fellow where he integrated genetic fine-mapping data with functional genomic and molecular epigenomic features to resolve causal genes and relevant tissues at loci associated with type 2 diabetes.
Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity.
Akbari P. et al, (2021), Science, 373
Abdominal and gluteo-femoral markers of adiposity and risk of vascular-metabolic mortality in a prospective study of 150 000 Mexican adults.
Gnatiuc L. et al, (2021), Eur J Prev Cardiol
Low-intensity daily smoking and cause-specific mortality in Mexico: prospective study of 150 000 adults.
Thomson B. et al, (2021), Int J Epidemiol
Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.
Wesolowska-Andersen A. et al, (2020), Elife, 9