Monitoring T-Cells Prevent Type 1 Diabetes

Scripps Scientists have discovered that monitoring a certain type of immune cell in the blood can help identify people who are at risk of developing type 1 diabetes, a potentially fatal autoimmune illness. If verified in future research, the new approach could be used to select potential people for treatment that stops the autoimmune process, making type 1 diabetes a preventable condition.

The researchers isolated T cells (a type of immune cell) from mouse and human blood samples in the article, “Measuring anti-islet autoimmunity in mouse and human by profiling peripheral blood antigen-specific CD4 T cells,” which was published in Science Translational Medicine on July 5, 2023. They were able to distinguish at-risk patients with active autoimmunity from those with no significant autoimmunity with 100% accuracy in a small sample by evaluating the T cells that can cause type 1 diabetes.

“These findings represent a big step forward because they offer the possibility of catching this autoimmune process while there is still time to prevent or greatly delay diabetes,” says study senior author Luc Teyton, MD, Ph.D., professor in the Department of Immunology and Microbiology at Scripps Research.

The first authors of the paper were graduate student Siddhartha Sharma and research assistants Josh Boyer and Xuqian Tan, all of whom were members of the Teyton lab at the time of the study.

Type 1 diabetes develops when the pancreas’ insulin-producing “islet cells” are destroyed by the immune system. The autoimmune process that causes type 1 diabetes can last for years, with several starts and stops. The exact mechanism by which the process begins is unknown, though it is known to entail genetic elements and may be triggered by routine viral infections. It usually occurs in childhood or early adulthood and necessitates lifelong insulin replacement. Researchers estimate that approximately two million people in the United States alone have type 1 diabetes.

In 2022, the US Food and Drug Administration approved an immune-suppressing medication that, if given in the early stages of autoimmunity, can protect islet cells and delay diabetes onset by months to years. Doctors, on the other hand, have not had a solid strategy for selecting persons who potentially benefit from such treatment. Anti-islet antibodies have historically been measured in patient blood samples, but this antibody response has not proven a very accurate predictor of autoimmune development.

“Anti-islet antibody levels are poorly predictive at the individual level, and type 1 diabetes is fundamentally a T cell-driven disease,” Teyton says.

Teyton and his colleagues created protein complexes to simulate the mix of immunological proteins and insulin fragments that specialized T cells known as CD4 T cells normally identify to trigger the autoimmune response. These constructs were utilized as bait to collect anti-insulin CD4 T cells in blood samples. They next examined gene activity within the collected T cells as well as protein expression on the cells to determine their activation level.

As a result, scientists were able to create a classification algorithm that properly identified which of nine at-risk individuals had persistent anti-islet autoimmunity.

Teyton now intends to confirm the CD4 T cell-based technique in a wider cohort of people with a long-term research comparing this strategy to the standard approach of detecting anti-islet antibodies.

Teyton and his colleagues are also aiming to make the technique of isolating and evaluating anti-islet T cells in blood samples more economical and convenient, so that it can be used in clinical settings more easily.

“If we can develop this into a useful method for identifying at-risk patients and tracking their autoimmunity status, we not only would have a way of getting the right people into treatment, but also would be able to monitor their disease progress and evaluate potential new preventive therapies,” Teyton says.

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