Uses GABA as a Biomarker to Measure Pancreatic Islet Cell Concentrations and Evaluate Diseases That Impair Pancreas Function
This non-invasive procedure measures the density of pancreatic islet cells to characterize the progression of diabetes. The global market for diabetes diagnostics and treatments will exceed $230 billion by 2027. In patients with diabetes, progression involves the loss of insulin-secreting pancreatic islet cells. Traditional diabetes diagnosis and monitoring measures concentrations of serum insulin, c-peptides, and proinsulin in drawn blood to determine the level of insulin produced by the pancreas. However, these results only measure insulin circulating at the time of taking the sample and not insulin secretion, making them ineffective at evaluating pancreatic function for certain patients.
Researchers at the University of Florida have developed a non-invasive assay that uses Gamma-aminobutyric acid (GABA) as a biomarker to characterize the function of pancreatic islet cells, indicating their ability to secrete insulin. This procedure more directly measures the pancreas’s ability to secrete insulin.
Application
Diagnostic imaging of the pancreas using GABA as a biomarker that aids treatment of patients with diabetes or impaired pancreatic function
Advantages
- Characterizes islet cell density, allowing for more precise measurement of the pancreas’ ability to produce insulin
- Uses non-invasive MRI equipment with an automated analysis system, making it easy to implement for diagnostic testing
- Results are standardized, giving clear information for clinical decisions
Technology
The molecule GABA is a known metabolite of pancreatic islet cells and is integral in the production of insulin. Thus, using GABA as a biomarker can directly measure the ability of the pancreas to secrete insulin. The non-invasive test uses a magnetic resonance spectroscopy assay carried out with MRI equipment and analyzed in a proprietary software pipeline to determine the density of functioning pancreatic islet cells. The output will be a single value that is readily interpretable to inform relevant clinical treatments. No additional contrast agent needed, making the only requirement for implementation minimal training with the automated software.
Brochure
