Paracrinology of islets and the paracrinopathy of diabetes
Autor: | Lelio Orci, Roger H Unger |
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Rok vydání: | 2010 |
Předmět: |
Blood Glucose
medicine.medical_specialty medicine.medical_treatment Biology Glucagon Insulin-Secreting Cells Diabetes mellitus Internal medicine Paracrine Communication medicine Animals Humans Glucose homeostasis Type 1 diabetes Multidisciplinary Insulin Pancreatic islets medicine.disease Insulin oscillation Diabetes Mellitus Type 1 Endocrinology medicine.anatomical_structure Glucagon-Secreting Cells Perspective Blood sugar regulation |
Zdroj: | Proceedings of the National Academy of Sciences. 107:16009-16012 |
ISSN: | 1091-6490 0027-8424 |
Popis: | New results have brought to light the importance of the regulation of glucagon by β-cells in the development of diabetes. In this perspective, we examine the normal paracrinology of α- and β-cells in nondiabetic pancreatic islets. We propose a Sherringtonian model of coordinated reciprocal secretory responses of these juxtaposed cells that secrete glucagon and insulin, hormones with opposing actions on the liver. As insulin is a powerful inhibitor of glucagon, we propose that within-islet inhibition of α-cells by β-cells creates an insulin-to-glucagon ratio that maintains glycemic stability even in extremes of glucose influx or efflux. By contrast, in type 1 diabetes mellitus, α-cells lack constant action of high insulin levels from juxtaposed β-cells. Replacement with exogenous insulin does not approach paracrine levels of secreted insulin except with high doses that “overinsulinize” the peripheral insulin targets, thereby promoting glycemic volatility. Based on the stable normoglycemia of mice with type 1 diabetes during suppression of glucagon with leptin, we conclude that, in the absence of paracrine regulation of α-cells, tonic inhibition of α-cells improves the dysregulated glucose homeostasis. These results have considerable medical implications, as they suggest new approaches to normalize the extreme volatility of glycemia in diabetic patients. |
Databáze: | OpenAIRE |
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