2023-05-11 03:20:25
Why do lean, metabolically diseased people have a higher risk of cardiovascular disease than obese, metabolically healthy people? German researchers are now investigating this question. Read more here.
New, computer-aided cluster analyzes point to a large heterogeneity of the risk for Typ-2-Diabetes and cardiovascular diseases and response to treatment. The results indicate that there may be a vast untapped treasure in the field of cardiometabolic research.
In her current review article in Lancet Diabetes & Endocrinology the DZD researchers Norbert Stefan from Helmholtz Munich and the University of Tübingen and Matthias Schulze from the German Institute for Human Nutrition Potsdam-Rehbrücke show how these novel concepts for assessing the risk of complications can help to better implement precision medicine in clinical practice.
Who is particularly at risk?
Become among the top 20 global risk factors for losing years of life in 2040 high blood pressure, obesity and an elevated fasting blood sugar level are of the greatest importance. Along with other established risk factors, such as a low HDL cholesterol– and high Triglyzerid-Wert, they feed into the assessment of metabolic health. In most of the more than a thousand studies published to date, people are considered to be metabolically healthy if they have fewer than two of these risk factors or pharmacological treatment for these diseases. Subphenotypes such as people with metabolically unhealthy normal weight (MUHNW) and metabolically healthy obesity (MHO) were identified, which differ greatly in their risk of cardiovascular disease.
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In a previous 2016 meta-analysis, the research team compared these two groups to metabolically healthy normal weight (MHNW) individuals. They found that the risk of cardiovascular disease increased by 45 percent in people with MHO and by as much as 100 percent in people with MUHNW.
Body fat distribution is relevant
In their current review article, the researchers not only summarize what is known about these relationships, but also highlight their new definition of metabolic health. Taking into account the risk factors of high blood pressure, type 2 diabetes and a high waist-to-hip ratio – the Waist Hip Index – When they analyzed data from the US National Health and Nutrition Examination Survey III and UK Biobank study, they found that the risk of death from cardiovascular disease was 100 percent increased in people with MUHNW, in people but not with MHO. “These data show the importance of considering the effects of body fat distribution when defining metabolic health,” emphasizes Schulze.
Norbert Stefan, Professor of Clinical and Experimental Diabetology at the University Hospital Tübingen, adds: “It is of great interest whether the new cardiometabolic risk clusters also help to identify subgroups of people with a pronounced risk for cardiometabolic diseases.” To answer this question , the authors of this review article discuss the results of the most important approaches to reducing complex data sets.
Cluster analyzes bring new insights
Most of the research was done in people with type 2 diabetes or those at risk of developing type 2 diabetes. The cluster approaches are also based on routinely available clinical variables, but can also include more complex data, such as e.g. e.g. genetic data. The subgroups that emerge from these cluster analyzes include people who predominantly have a low Insulin secretionone insulin resistanceone fatty liverhave visceral obesity, mild age-related type 2 diabetes or mild obesity-related type 2 diabetes.
The authors come to the conclusion that neither the concept of metabolic health nor the cluster approach are superior to the already established risk prediction models. However, both approaches could be informative to better predict cardiometabolic risk in subgroups, e.g. B. in people in different BMI categories or in people with type 2 diabetes. They also emphasize that the applicability of the concepts by the treating physicians and the communication of the cardiometabolic risk with the patients could be easier for the concept of metabolic health.
The authors caution that classification as metabolically healthy or unhealthy, or assignment to a specific cardiometabolic risk cluster, will in most cases be a temporary assignment. However, the approaches to identifying cardiometabolic risk clusters are useful for assigning people to specific pathophysiological risk groups. To what extent this association could improve risk assessment and treatment response remains to be investigated.
This article is based on a press release of the German Center for Diabetes Research. We have the original publication for you here and linked in the text.
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