How to Detect Diabetes Early Enough To Reverse It
August 17, 2022
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Diabetes is a severe and growing metabolic disorder. It already affects hundreds of thousands of people in Switzerland. A sedentary lifestyle and an excessively rich diet damage the beta cells of the pancreas, promoting the onset of this disease. If detected early enough, its progression could be reversed, but diagnostic tools that allow for early detection are lacking. A team from the University of Geneva (UNIGE) in collaboration with several other scientists, including teams from the HUG, has discovered that a low level of the sugar 1,5-anhydroglucitol in the blood is a sign of a loss in functional beta cells. This molecule, easily identified by a blood test, could be used to identify the development of diabetes in people at risk, before the situation becomes irreversible. These results can be found in the Journal of Clinical Endocrinology & Metabolism.
In Switzerland, almost 500,000 people suffer from diabetes. This serious metabolic disorder is constantly increasing due to the combined effect of a lack of physical activity and an unbalanced diet. If detected early enough at the pre-diabetes stage, progression to an established diabetes can be counteracted by adopting an appropriate lifestyle. Unfortunately, one third of patients already have cardiovascular, renal or neuronal complications at the time of diagnosis, which impacts their life expectancy.
When diabetes starts to develop but no symptoms are yet detectable, part of the beta cells of the pancreas (in green) disappear (right image) compared to a healthy individual (left image). This previously undetectable decrease could be identified by measuring the level of 1,5-anhydroglucitol in the blood
‘‘Identifying the transition from pre-diabetes to diabetes is complex, because the status of the affected cells, which are scattered in very small quantities in the core of an organ located under the liver, the pancreas, is impossible to assess quantitatively by non-invasive investigations. We therefore opted for an alternative strategy: to find a molecule whose levels in the blood would be associated with the functional mass of these beta cells in order to indirectly detect their alteration at the pre-diabetes stage, before the appearance of any symptoms,’’ explains Pierre Maechler, a Professor in the Department of Cell Physiology and Metabolism and in the Diabetes Centre of the UNIGE Faculty of Medicine, who led this work.
Several years ago, scientists embarked on the identification of such a molecule able to detect pre-diabetes. The first step was to analyse thousands of molecules in healthy, pre-diabetic and diabetic mouse models. By combining powerful molecular biology techniques with a machine learning system (artificial intelligence), the research team was able to identify, from among thousands of molecules, the one that best reflects a loss of beta cells at the pre-diabetic stage: namely 1,5-anhydroglucitol, a small sugar, whose decrease in blood would indicate a deficit in beta cells.
Source: https://www.unige.ch/
Categories: Uncategorized
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Tags: 1, 5-anhydroglucitol, Artificial Intelligence, beta cells, blood, cardiovascular, diabetes, diet, HUG, identification, life expectancy, machine-learning, metabolic disorder, molecule, neuronal, pre-diabetes, renal, sugar, UNIGE, University of Geneva
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