Sir Henry Dale Fellow
My research to date has largely focused on identifying genetic associations with diagnosis or disease presentation in inflammatory bowel disease (IBD), and developing statistical techniques to understand the function of genetic risk variants. As a field, statistical genetics has been very successful at finding risk variants for a host of complex diseases of the immune system. These risk variants tend to be shared across multiple immune diseases, and many of them are in genes involved in relevant immune pathways or expressed in relevant immune cells (such as monocytes and CD4 T-cells for IBD variants). However, we have had significantly less success in identifying the impact of genetic risk pathways on the function of the human immune system, and cross-disease analysis implies that these risk variants fall into a dizzying diversity of immune pathways. To translate disease genetics into real diagnostic, prognostic or treatment solutions we need to understand these pathways from genetic variation through healthy immune variation to disease risk. It is only through close collaborations between statistical geneticists, immunologists and molecular biologists that we will start to untangle these pathways.
My plan of research at the Kennedy Institute has three interrelated strands. The first is the analysis of large-scale human medical cohort data using statistical and computational techniques that are specifically designed to identify multi-gene signatures of shared underlying immune variation that drive a variety of different health outcomes. The second is to collaborate with other researchers to generate and analyse human immune variation data (including host immune function and exposure to both commensal and pathogenic organisms) in order to tie genetic risk of disease to variation in specific measurable immune phenotypes. The final strand is to collaborate with immunologists, cell biologists and clinical researchers to develop new ways of measuring the function of the human immune system in order to profile the specific pathways that confer genetic risk of chronic disease.
Bayesian meta-analysis across genome-wide association studies of diverse phenotypes.
Trochet H. et al, (2019), Genetic epidemiology, 43, 532 - 547
Correction: Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.
Rivas MA. et al, (2019), PLoS genetics, 15
INFERIORITY OF LABORAS OVER INCAPACITANCE TESTING TO MEASURE SPONTANEOUS MURINE OSTEOARTHRITIS PAIN
von Loga IS. et al, (2019), OSTEOARTHRITIS AND CARTILAGE, 27, S420 - S420
Graphical model selection for Gaussian conditional random fields in the presence of latent variables
(2018), Journal of the American Statistical Association
Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank.
Cortes A. et al, (2017), Nature genetics, 49, 1311 - 1318