Recent studies provide evidence for an updated diabetes classification reflecting different risks for diabetes-related complications. Researchers at the German Diabetes Center (DDZ) and their partners from the German Center for Diabetes Research (DZD) and the University of Lund in Sweden have now identified clusters allowing for the separation of different diabetes subtypes. Two of these subtypes are at higher risk of fatty liver disease and diabetic neuropathy. In line with the concept of precision medicine, these findings illustrate the need for targeted diagnosis and treatment for these patients’ subgroups in order to delay or even prevent diabetes-related complications.
The traditional classification of diabetes, mainly in type 1 and type 2 diabetes, has been challenged by studies from Scandinavia.
In the current issue of The Lancet Diabetes & Endocrinology, researchers from DDZ together with colleagues from DZD and University of Lund published a cluster analysis of diabetes allowing for phenotyping into subgroups, which extended the findings by showing that risks of certain diabetes-related complications segregated between diabetes subgroups already during the first five years after diagnosis.
These results come from the prospective observational multicenter German Diabetes Study (GDS), which follows people with newly diagnosed diabetes for more than 10 years.
"The new subgroups will help to develop precise prevention and tailored treatment strategies for the respective high-risk groups," said Professor Michael Roden, principal investigator of GDS and director of DDZ and of the Division of Endocrinology and Diabetology at University Clinics of Düsseldorf. "This is an important step into precision medicine for diabetes and its comorbidities."
Analysis and results
The GDS is conducted at eight locations throughout Germany within DZD, led by DDZ (www.deutsche-diabetes-studie.de). For this analysis, 1105 participants underwent cluster analyses based on the predictive marker GADA (glutamate decarboxylase antibody), age at diagnosis, body mass index (BMI), HbA1c level and HOMA indices (homeostasis model assessment) for insulin sensitivity and insulin secretion.
The researchers tested whether comprehensive phenotyping validates and further characterizes these clusters at diagnosis and during follow-up. They also analysed whether relevant complications and comorbidities associated with diabetes, including non-alcoholic fatty liver disease (NAFLD), liver fibrosis and diabetic neuropathy, differ among these clusters during the five-year follow-up period.
Based on the cluster algorithm, different subgroups with differing risks of complications could be identified: mild age-related diabetes (MARD, 35%), mild obesity-related diabetes (MOD, 29%), severe autoimmune diabetes (SAID, 22%), severe insulin-resistant diabetes (SIRD, 11%) and severe insulin-deficient diabetes (SIDD, 3%). The results show that two subgroups in particular have a high risk of complications. The highest risk of developing non-alcoholic fatty liver was in the cluster of "severe insulin-resistant diabetes" (SIRD); for diabetic neuropathy, the highest risk was in the subgroup "severe insulin-deficient diabetes" (SIDD).
Using the new diabetes classification, people with type 2 diabetes can be assigned to specific subgroups that exhibit significant metabolic changes and differing risk patterns for the development of diabetes-related complications. Individually targeted prevention and early treatment of specific subgroups of people with diabetes is a step towards precision medicine to delay or even prevent secondary diseases.
German Diabetes Study (GDS)
The aim of the German Diabetes Study is to identify markers for different forms of diabetes at an early stage in order to develop and apply new concepts for the prevention and treatment of secondary diseases. In this way, early warning signs of diabetes complications can be detected, and approved therapy methods can be compared in parallel.
This study will also investigate the influence of genes on the course of the disease. Participants in the German Diabetes Study receive free screenings for early detection of diabetes-associated diseases such as nerve, vascular and retinal damage. If you are interested in taking part in the study, please contact the Clinical Study Center at the German Diabetes Center (DDZ) at +49 (0)211/3382 209 or send an e-mail to firstname.lastname@example.org.
Zaharia OP, Strassburger K, Strom A, Bönhof GJ, Karusheva Y, Antoniou S, Bódis K, Markgraf DF, Burkart V, Müssig K, Hwang J-H, Asplund O, Groop L, Ahlqvist E, Seissler J, Nawroth P, Kopf S, Schmid SM, Stumvoll M, Pfeiffer AFH, Kabisch S, Tselmin S, Häring HU, Ziegler D, Kuss O, Szendroedi J, Roden M: Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study. The Lancet Diabetes & Endocrinology. DOI: https://doi.org/10.1016/S2213-8587(19)30187-1
Christina Becker | idw - Informationsdienst Wissenschaft
A new view of microscopic interactions
02.07.2020 | University of Missouri-Columbia
02.07.2020 | Max Delbrück Center for Molecular Medicine in the Helmholtz Association
A promising operating mode for the plasma of a future power plant has been developed at the ASDEX Upgrade fusion device at Max Planck Institute for Plasma...
Live event – July 1, 2020 - 11:00 to 11:45 (CET)
"Automation in Aerospace Industry @ Fraunhofer IFAM"
The Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM l Stade is presenting its forward-looking R&D portfolio for the first time at...
With an X-ray experiment at the European Synchrotron ESRF in Grenoble (France), Empa researchers were able to demonstrate how well their real-time acoustic monitoring of laser weld seams works. With almost 90 percent reliability, they detected the formation of unwanted pores that impair the quality of weld seams. Thanks to a special evaluation method based on artificial intelligence (AI), the detection process is completed in just 70 milliseconds.
Laser welding is a process suitable for joining metals and thermoplastics. It has become particularly well established in highly automated production, for...
A research team from the Max Planck Institute for the Structure of Dynamics (MPSD) and the University of Oxford has managed to drive a prototypical antiferromagnet into a new magnetic state using terahertz frequency light. Their groundbreaking method produced an effect orders of magnitude larger than previously achieved, and on ultrafast time scales. The team’s work has just been published in Nature Physics.
Magnetic materials have been a mainstay in computing technology due to their ability to permanently store information in their magnetic state. Current...
The Venus flytrap (Dionaea muscipula) takes only 100 milliseconds to trap its prey. Once their leaves, which have been transformed into snap traps, have...
19.05.2020 | Event News
07.04.2020 | Event News
06.04.2020 | Event News
02.07.2020 | Life Sciences
02.07.2020 | Life Sciences
02.07.2020 | Physics and Astronomy