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Novel technology holds promise for improving accuracy of type 1 diabetes tests

Researchers from the Johns Hopkins University School of Medicine, Stanford University and the University of Florida report the development of a novel antibody detection technology that holds promise for improving the accuracy of diagnostic tests for type 1 diabetes in young children and making populationwide screening practical.

In a report on the work, published in the Proceedings of the National Academy of Sciences on Sept. 5, the scientists say the technology enables screening for more autoimmune antibodies implicated in type 1 diabetes than current tests by incorporating a full-length pancreatic protein, called the pancreatic zinc transport 8 (ZnT8), that is targeted for autoimmune attack in people with the disease. By improving the accuracy of this test, researchers hope to catch the disease earlier and extend testing to all people. Type I diabetes, once known as juvenile diabetes, is a relatively rare form of the disorder in which the pancreas produces no insulin. It accounts for about 5 percent of all cases of diabetes in the United States.

“Although current tests are about 94 percent accurate in detecting the antibodies years before children and young adults lose all blood sugar control, they are not accurate enough to rely upon for populationwide screening, so current antibody testing is limited to confirming diagnosis in symptomatic children and adults. Increasing the test accuracy will help expand screening for asymptomatic type 1 diabetes into the general population,” says Dax Fu, Ph.D., associate professor of physiology at the Johns Hopkins University School of Medicine. At the clinical onset of type 1 diabetes, most children and young adults develop symptoms such as fainting, exhaustion, vomiting and confusion. And by then, a large majority of pancreatic beta cells may already be lost. “Presymptomatic diagnosis will provide the benefit of beginning preventative therapies” says Fu.

Fu explains that ZnT8 has long been…

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