New app helps diabetes researchers to classify glucose response

Adam Hulman, DDA postdoc at Aarhus University, and his colleagues has developed an online application which can help diabetes researchers estimate glucose response patterns in their datasets. The application has already been well received with over 170 users from 32 different countries.

A new application developed by Adam Hulman and colleagues already seem requested. The application has been developed in continuation to his own research upon pathophysiological characteristics underlying glucose response during the oral glucose tolerance test (OGTT), which also was the main topic of his research as a DDA postdoc.

Adam Hulman explains the study that lies behind the application.

“We have been exploring the heterogeneity of glucose response by analyzing data from frequently sampled OGTTs (e.g. at 0, 30, 60, 90, 120 mins) with advanced statistical methods. The frequent sampling allowed us to focus on glucose response curves instead of separate time points, which gives a more complete picture of glucose dynamics and metabolic function during the OGTT,” he says.

Although the research result was a significant step in the project, there is still a way to go concerning the understanding of heterogeneity of type 2 diabetes.

“One possible question is whether the identified subgroups respond differently to interventions, or whether we can identify these subgroups without a 5-point OGTT? To facilitate further research, we launched the online application (https://steno.shinyapps.io/grc2h) supplementing the article to enhance knowledge dissemination,” Adam Hulman says.

Adam Hulman’s and his group’s study has recently been published in an article in Diabetes Care (http://care.diabetesjournals.org/content/41/8/1740).

Kurt Højlund, Head of Research, Clinical Professor in Diabetes at Steno Diabetes Center Odense, Odense University Hospital, congratulates the authors and finds the study very interesting.

“The study shows that the 2-hour oral glucose tolerance test (OGTT) provides much more information about pathophysiological risk markers of type 2 diabetes development than previously thought.  It will be exciting to follow future application of their published on-line tool by other research groups, and to what extent this can improve prediction, prevention and treatment of type 2 diabetes and associated complications,” Kurt Højlund says.

The work has been carried out in strong collaboration between Aarhus University, Steno Diabetes Center Copenhagen and international partners.