Home Type 1 Study links smaller pancreas size to faster progression to stage 3 type 1 diabetes | VUMC Reporter

Study links smaller pancreas size to faster progression to stage 3 type 1 diabetes | VUMC Reporter

by Jill Clendening
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Team members participating in this study are, from left, Melissa Hilmes, MD, Daniel Moore, MD, Alvin Powers, MD, John Williams, PhD, and Jack Virostko, PhD. (Photo: Jessica Kimber)

A multicenter, longitudinal study co-led by researchers at the Vanderbilt Diabetes Research and Training Center (DRTC) found that a smaller pancreas speeds progression to stage 3 type 1 diabetes (T1D), a clinical diagnostic point. It turned out that it was predicted that this would happen. occurs.

The research team also found that using pancreatic volume measurements in combination with a validated metabolic T1D risk scale more accurately predicted disease onset than either method alone.

These findings were published in the Journal of the American Diabetes Association. diabetes caredemonstrated that pancreatic size is an early marker of the risk of T1D progression and that pancreatic imaging is useful for tracking disease onset and for participation in prevention and treatment trials.

“By the time you develop stage 3 type 1 diabetes, beta cells have decreased significantly and symptoms usually appear,” said lead author Dr. Jack Virostko, assistant professor of diagnostic medicine at the University of Texas Dell School of Medicine. in Austin, where he was previously affiliated with Vanderbilt University’s Imaging Science Institute. “We believe that if we can more accurately predict progression to stage 3, even before diagnosis, we can better identify and apply treatments to slow or even stop disease progression. This is my wish.”

The research team collaborated with TrialNet, an NIH-funded research network that investigates how T1D can be prevented in people at high risk for the disease. TrialNet screening looks for diabetes-related autoantibodies that indicate an increased risk of developing T1D. Screening can detect these autoantibodies years to decades before diagnosis. Although the presence of two or more autoantibodies indicates an increased risk of future disease development, the risk factors that determine when diabetes develops remain unclear.

In this study, pancreatic volume was compared with non-contrast magnetic resonance imaging (MRI), oral glucose tolerance test (OGTT) metabolic score, and pancreatic volume to predict progression to stage 3 in 65 TrialNet participants. Determined using a combination of metabolic scores. Her T1D in an individual with multiple diabetes-related autoantibodies.

MRI scans were performed at 6- or 12-month intervals, following a standardized protocol that was validated for quantitative assessment of the pancreas across imaging centers and hardware. This protocol was previously developed by members of this research team. Multicenter Assessment of the Pancreas in Type 1 Diabetes (MAP-T1D) Consortiumled by VUMC.

“We are investigating whether MRI measurements of pancreatic volume in individuals identified as at risk for type 1 diabetes can predict progression to stage 3 disease and how these imaging measurements correlate with metabolic testing. “We looked at what was going on,” said Daniel Moore, a facility investigator at Vanderbilt University Medical Center (VUMC). , PhD, MD, Associate Professor of Pediatrics, Pathology, Microbiology, and Immunology. “Our results show that a small pancreatic volume is associated with stage 3 disease, with similar discrimination to measurements obtained from the oral glucose tolerance test and the Diabetes Prevention Trial Type 1 Risk Score (DPTRS), a predictive tool validated by TrialNet. This suggests that it may be possible to predict progression to type 1 diabetes.”

“Notably, there is no correlation between pancreatic volume and metabolic measurements, which reflect different aspects of the disease process underlying T1D and may provide different information about disease risk. Our predictive model using both pancreatic volume and metabolic measurements outperformed imaging and metabolic tests alone in predicting progression to stage 3 type 1 diabetes. It performed well.”

Study limitations include small sample size and limited progression events. A larger dataset of pancreatic MRI is needed to evaluate the generalizability of the combination of pancreatic volume and her-oGTT on diabetes risk progression. The overwhelming majority of study participants were non-Hispanic white, so future research is needed to see if the results are replicable in diverse populations.

“It is vital that we better understand the progressive changes that occur in the pancreas and what this means for the development of type 1 diabetes and for everyone,” Professor Moore said. “The results of this study are the result of many years of collaboration between the expert teams that first developed a better way to assess pancreatic volume. We will continue to leverage this foundation for discoveries that will lead to improved patient care. I will continue to do so.”

The multicenter study included researchers from VUMC, Vanderbilt University, the University of Texas at Austin, Tennessee Valley Healthcare System in Virginia, the University of Colorado Barbara Davis Diabetes Center, the University of Chicago, and the University of Melbourne St. Vincent Medical Research Institute. There is.

VUMC’s TrialNet principal investigator is William Russell, MD. In addition to Russell and Moore, VUMC contributors to this study include Liping Du, PhD (Biostatistics), Brenna Hammel RN, CPN (Pediatrics), Melissa Hilmes, MD (Pediatric Radiology), and Hakmook Kang, PhD (Biology). Statistics), Alvin C. Powers, MD (Medicine), Jordan Wright, MD (Medicine), and Jonathan Williams, PhD (Diabetes Center).

Research support was received from the Leona M. and Harry B. Helmsley Charitable Trust, JDRF International, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK, R03 DK129979), the J.P. Fletcher Foundation, and the Thomas J. Beatson, Jr. Foundation . . Funding was provided by grant U24 DK097771 through the NIDDK Information Network New Investigator Pilot Program in Bioinformatics.

This study was supported by the data collection tool REDCap developed at Vanderbilt University and by grant UL1 TR000445 from the National Institutes of Health (NIH) National Center for the Advancement of Translational Sciences, a Vanderbilt Clinical Translational Research Fellowship. (VCTRS) Program resources were used. . Support was also received from Vanderbilt DRTC (DK020593) and the Vanderbilt University Imaging Sciences Institute Human Imaging Center (1 S10OD021771 01).

The Type 1 Diabetes TrialNet Research Group is funded through a cooperative agreement by the NIH through NIDDK, the National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and JDRF.

Written by Jill Clendenning

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