Scientists Identify New Risk Factor for Diabetes

The ITPR3 gene regulates calcium flow within cells. The researchers found that one particular variant of ITPR3 is more common in people with type 1 diabetes, which may point to ITPR3 as a cause of the disease. The finding was reported in the October 2006 issue of the American Journal of Human Genetics. Both environmental and genetic factors are thought to contribute to the disease.

"Scientists having been working to understand the genetics of type 1 diabetes for thirty years. We have long known that the human leukocyte antigen [HLA] class II genes play an important role in risk for type 1 diabetes, but other involved genes have remained elusive,” said Jared Roach, M.D., Ph.D.,a senior research scientist at the ISB. "This study begins to examine one of those involved genes.”

The team, co-directed by Dr. Marta Janer, Ph.D., a senior research scientist at the ISB, analyzed genetic data from patients who had participated in the Swedish Childhood Diabetes study and the Diabetes Incidence in Sweden study, both based in Sweden and represented by Dr. Åke Lernmark of the University of Washington (Seattle, USA). The ITPR3 gene has been studied for years in the nervous system but has never been thought to cause diabetes. A number of studies have found that ITPR3 is abundant in pancreatic islets, which are the parts of the pancreas that contain the beta cells, indicating this protein may be important to the function of beta cells and that a defect may make beta cells more susceptible to an autoimmune attack.

At least in Sweden, ITPR3 may account for a significant portion of the previously unknown genetic risk for type 1 diabetes, concluded the researchers. Preliminary estimates suggest that ITPR3 may be responsible for approximately 20% of the cases of type 1 diabetes in Sweden.

ISB seeks to unravel the mysteries of human biology and identify strategies for predicting and preventing diseases such as cancer, diabetes and AIDS. The driving force behind its approach is the integration of biology, computation, and technology. This approach allows scientists to analyze all of the elements in a system rather than one gene or protein at a time.



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