Date(s) - 25/02/2014
1:00 pm - 3:00 pm
After GWAS: using dense genotype data to identify causal genes and relevant tissues for type 1 diabetes
Dr Chris Wallace (firstname.lastname@example.org)
Association studies have now identified libraries of genetic markers associated with individual and multiple diseases in the population. But genetic variation doesn’t cause disease. Rather, it influences the mix of genetic products, perhaps in a cell specific manner, that, together with environment, influence the stochastic events that ultimately lead to disease. If we are to build upon our genetic results to identify druggable targets and understand the effects of those drugs, we must first identify the genetic products which are affected by disease associated genetic variation. In a minority of cases, we have this knowledge, demonstrated through specific and often painstaking experiments. General, systematic identification of causal disease would enable the next rounds of these experiments to be properly targeted at the right genes in appropriate cells. I will show how we have approached this question in type 1 diabetes, by combining Bayesian fine mapping of genetic disease association signals in dense genotyping data with external publicly available datasets.
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