Using gene to phenotype studies to identify type 1 diabetes genes and their func...
Using gene to phenotype studies to identify type 1 diabetes genes and their functions
Following the recent explosion of GWAS publications, we now have a much better grasp of the common genetic basis of many human complex traits. This dramatic development of genotyping and analytic technologies has allowed to charac...
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Descripción del proyecto
Following the recent explosion of GWAS publications, we now have a much better grasp of the common genetic basis of many human complex traits. This dramatic development of genotyping and analytic technologies has allowed to characterize many novel variants associated with human disease. Nevertheless, the identification of these disease-associated loci hasn’t yet translated into a better understanding of the exact nature of the defects causing the pathologic manifestations. In the current research project, we propose to assess the physiological role of the risk variants on relevant phenotypes to identify functional the causal genes associated with type 1 diabetes (T1D) pathogenesis. To address this issue, we will develop highly sensitive and reproducible assays to measure the impact of the different genotypes on the selected phenotypes. By using this quantitative approach, we expect not only to be able to reduce the complexity inherent to the disease phenotype, but also to have the power and sensitivity to detect the important but quantitative physiological effects of common susceptibility alleles of low phenotypic penetrance.
In this study we will develop highly sensitive molecular assays, and will take advantage of the core flow cytometry facilities to characterize the cell surface, cytokine production and signaling profile of immune subsets in individuals carrying specific risk alleles. Importantly, we will take advantage of our core genotyping and clinical databases to assess the impact of disease-associated genotypes on these quantitative phenotypes. By integrating the phenotyping data with a high throughput genotyping database in a large sample of individuals, we expect to translate the current knowledge of the genetic risk, into a more physiologically relevant context, in order to narrow down on the actual causal genes contributing to the etiology of human diseases.