A whole-genome approach to monogenic and type 1 diabetes: Copy-number variation and exome screening

Diabetes is an epidemically increasing, common disease with high morbidity. Recently, there has been a break-through in the identification of diabetes risk genes. Although the genome-wide association studies in type 2 diabetes have been successful in iden tifying common gene variants associated with diabetes, the value for predicting outcomes like development of diabetes and complications seems limited. Candidate and positional cloning of genes causing monogenic diabetes and type 1B diabetes have, however, led to the identification of at least ten diabetes genes where the predictive value is very high. Thus, our approach is to go back to family studies and monogenic diabetes. We hypothesize that there are undiscovered diabetes genes that are discernible in patients with monogenic diabetes and type 1B diabetes and that it is possible to find these by a systematic approach using genome-wide copy-number variant analysis and ?deep? sequencing of the exome (all 32,000 genes). Using our population-based registri es for monogenic and childhood diabetes, we aim to screen selected cases by copy-number variant analysis and ?deep? sequencing. Our research is multidisciplinary, has a translational approach and takes advantage of FUGE platforms. The identification of ne w diabetes genes is important for diagnosis and treatment of patients with diabetes.