Prof. Dr. Robert Wagner, University Hospital Tübingen (Universitätsklinikum Tübingen, Germany), conducts research on the early pathogenesis of type 2 diabetes. The current research results have recently been published in Nature Medicine. The specialist for internal medicine, endocrinology and diabetology will present them in concrete terms at the congress of the German Diabetes Society (Deutsche Diabetes Gesellschaft, DDG). In an advance interview with esanum, Prof. Wagner explains the findings relevant to practice.
esanum: Prof. Wagner, what do you bring from diabetes research to this year's DDG Congress?
Wagner: I am talking about our project in sub-phenotyping people at increased risk of diabetes. The concept of deep phenotyping of the metabolism before the onset of diabetes was started by Prof. Häring and Prof. Fritsche in Tübingen 25 years ago. At that time, it became increasingly clear that type 2 diabetes is not a uniform disease, but a conglomeration of different pathological mechanisms. For this reason, attempts have been made for some years to divide the disease into subgroups that are more consistent in terms of pathophysiology, treatability and complications. These different phenotypes are already evident in prediabetes. So one can recognise the different metabolic constellations long before the onset of diabetes.
esanum: Who took part in the study?
Wagner: We examined almost 900 test subjects who had an increased risk of diabetes. We divided them into subgroups using a clustering method. Six clusters were identified based on metabolic variables. They are based on body fat compartments, such as visceral fat or subcutaneous fat, liver fat, insulin sensitivity, insulin secretion, glycaemia and HDL cholesterol. In addition, there was a genetic risk score for type 2 diabetes. The average observation ran for about 4 years. In the replication cohort in England, there were more than 6,000 subjects and the observation ran for about 16 years.
esanum: What did you find?
Wagner: We tried to find similarities in the constellation of variables, i.e. to identify groups in which these variables are similar. It turned out that there are three groups that have a particular risk - two of them a generally high risk for diabetes. But the third, cluster 6, is the most interesting group. It does not have a particularly high risk of diabetes in the next ten years or so, but it does develop complications such as renal failure as it progresses. This group had the highest mortality in the English cohort with the long follow-up.
esanum: What are the benefits of your results for diabetes research and patients?
Wagner: In the future, we can use the study results to target preventive and prophylactic interventions so that those most in need receive appropriate treatments in a more focused way. People in this group more often have secondary diseases such as hypertension, but do not develop diabetes for a long time. This group would otherwise have remained "under the radar". But if we can identify them, then they can be cared for more intensively. The low-risk groups probably do not need special medical attention.
esanum: So do many obese people not need targeted health interventions, even though they have a very high risk for many diseases, including severe COVID-19 courses?
Wagner: You have to look at this in a differentiated way. Obesity not only causes metabolic diseases, but also other diseases. These include musculoskeletal diseases such as arthrosis, but also an increased risk of atherosclerosis and cancer. The risk of osteoarthritis can probably also be reduced by weight reduction in metabolically healthy obese people. The risk of heart attack and malignant diseases could have something to do with hyperinsulinaemia, which applies well to cluster 6. Whether the increased risk for a severe COVID course is generally obesity-related or only has to do with the aspects of metabolically unhealthy obesity, we do not yet know for sure.
esanum: Maybe a topic at the next DDG congress?
Wagner: Quite possibly. It would be an interesting question to examine in our clusters, to what extent they have an increased risk for severe COVID courses.