Measuring gene expression adjustments over time could assist predict T1D diabetes development

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TAMPA, Florida (June 4, 2021) – Type 1 diabetes (T1D) is an autoimmune disease in which a malfunctioning immune system gradually destroys healthy islet β cells in the pancreas, leading to insulin deficiency. The exact cause of T1D remains unknown. However, β-cell reactive autoantibodies can be detected in the circulating blood months to years before diagnosis, increasing the possibility of intervening to stop or delay T1D before children develop the disease.

Monitoring the number, type, and concentration of autoantibodies appearing in the blood can help predict the long-term risk of progression from autoimmunity to symptomatic T1D.

New findings now suggest that measuring how patterns of gene expression in white blood cells change in children from infancy – before autoantibodies that indicate an autoimmune reaction against the β cells appear – can predict which are genetically susceptible earlier and more robustly Individuals will develop into T1D. Co-researchers from the Health Informatics Institute (HII) at the University of South Florida took part in the comprehensive international study.

The research was published in Science Translational Medicine on March 31.

HII Director Jeffrey Krischer, PhD, Professor in the Department of Internal Medicine at USF Health Morsani College of Medicine; and Hemang M. Parikh, PhD, Assistant Professor of Bioinformatics in the Department of Pediatrics, USF Health Morsani College of Medicine, investigators on the study led by UK researchers from the University of Cambridge.

“Our identification of specific changes in the blood related to natural killer cells provides evidence of the potential involvement of these immune cells in the onset or progression of type 1 diabetes in asymptomatic children,” said Dr. Parikh. “This creates a possible new point of attack for early therapeutic intervention using immune modulation.”

This study was based on blood samples taken from 400 children from The Environmental Determinants of Diabetes in the Young (TEDDY) consortium, ages from birth to 6, samples well before symptoms of the disease appeared.)

The blood samples were processed using genomic approaches and bioinformatic analysis methods in order to measure the expression of thousands of genes simultaneously. In this way, the researchers were able to determine which genes were switched on and off in each child at different times.

Among the main results of the study:

  • Discovered dynamic, early changes in white blood cell gene expression: Whether or not they developed autoimmunity or T1D with age, all of the children in the study showed marked changes in the patterns of gene expression in their blood within the first few years of life. This observation underscores the dynamic context in which healthy infants develop early autoimmune disease. When the researchers took into account the large changes in gene expression patterns with age, very specific patterns became apparent that correlated with progression to T1D diagnosis. They identified changes in gene expression in the blood that were not seen in healthy children, and these changes began before any other evidence of autoimmunity. The faster the changes occurred, the faster the children developed towards the onset of T1D.
  • Linked NK cell signature with T1D progression: By comparing a specific pattern of gene expression associated with T1D progression with groups of genes expressed by many different cell types, the researchers found that this pattern came from a specific immune cell population known as natural killer cells ( NK) is known. Although NK cells have been observed in the pancreas of children with recent T1D, the role of these immune cells does not play a prominent role in the current theories explaining how the immunopathology of T1D develops. A more detailed study is needed to determine whether NK cells actively contribute to the T1D-related autoimmune process that destroys β cells in the pancreas, reflecting a pathophysiological response.
  • Builds a robust predictive model, independently verified: The researchers used their new knowledge of longitudinal changes in gene expression patterns to create a model to predict which infants would get T1D and when the disease was likely to occur. The predictive model takes into account the latest findings on how seroconversion of autoantibodies affects progression to T1D. Its accuracy has been validated against a second, independent group of prediabetic children from the Type 1 Diabetes Prediction and Prevention Study.

“This type of large-scale research is only possible with the collaboration of many people, including healthy children at risk of T1D, patients with T1D, their families, and myriad others,” added Dr. Parikh added. “USF is fortunate to be involved in such a major international effort to combat this complex autoimmune disease.”

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The work was supported by several grants from the National Institutes of Health. Dr. USF Health’s Krischer heads the coordination center for the NIH-funded TEDDY consortium.

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