Institute of Diabetes Gerhardt Katsch

Karlsburg, Germany

Institute of Diabetes Gerhardt Katsch

Karlsburg, Germany
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Becker A.,Ingenium GmbH | Eichentopf R.,Probiodrug | Sedlmeier R.,Ingenium GmbH | Waniek A.,University of Leipzig | And 17 more authors.
Biological Chemistry | Year: 2016

Secretory peptides and proteins are frequently modified by pyroglutamic acid (pE, pGlu) at their N-terminus. This modification is catalyzed by the glutaminyl cyclases QC and isoQC. Here, we decipher the roles of the isoenzymes by characterization of IsoQC-/- mice. These mice show a significant reduction of glutaminyl cyclase activity in brain and peripheral tissue, suggesting ubiquitous expression of the isoQC enzyme. An assay of substrate conversion in vivo reveals impaired generation of the pGlu-modified C-C chemokine ligand 2 (CCL2, MCP-1) in isoQC-/- mice. The pGlu-formation was also impaired in primary neurons, which express significant levels of QC. Interestingly, however, the formation of the neuropeptide hormone thyrotropin-releasing hormone (TRH), assessed by immunohistochemistry and hormonal analysis of hypothalamic-pituitary-thyroid axis, was not affected in isoQC-/-, which contrasts to QC-/-. Thus, the results reveal differential functions of isoQC and QC in the formation of the pGlu-peptides CCL2 and TRH. Substrates requiring extensive prohormone processing in secretory granules, such as TRH, are primarily converted by QC. In contrast, protein substrates such as CCL2 appear to be primarily converted by isoQC. The results provide a new example, how subtle differences in subcellular localization of enzymes and substrate precursor maturation might influence pGlu-product formation. © 2016 by De Gruyter 2016.

Schilling S.,Probiodrug | Kohlmann S.,Ingenium GmbH | Bauscher C.,Ingenium GmbH | Sedlmeier R.,Ingenium GmbH | And 12 more authors.
Journal of Biological Chemistry | Year: 2011

Glutaminyl cyclases (QCs) catalyze the formation of pyroglutamate (pGlu) residues at the N terminus of peptides and proteins. Hypothalamic pGlu hormones, such as thyrotropin-releasing hormone and gonadotropin-releasing hormone are essential for regulation of metabolism and fertility in the hypothalamic pituitary thyroid and gonadal axes, respectively. Here, we analyzed the consequences of constitutive genetic QC ablation on endocrine functions and on the behavior of adult mice. Adult homozygous QC knock-out mice are fertile and behave indistinguishably from wild type mice in tests of motor function, cognition, general activity, and ingestion behavior. The QC knock-out results in a dramatic drop of enzyme activity in the brain, especially in hypothalamus and in plasma. Other peripheral organs like liver and spleen still contain QC activity, which is most likely caused by its homolog isoQC. The serum gonadotropin-releasing hormone, TSH, and testosterone concentrations were not changed by QC depletion. The serum thyroxine was decreased by 24% in homozygous QC knock-out animals, suggesting a mild hypothyroidism. QC knock-out mice were indistinguishable from wild type with regard to blood glucose and glucose tolerance, thus differing from reports of thyrotropin-releasing hormone knock-out mice significantly. The results suggest a significant formation of the hypothalamic pGlu hormones by alternative mechanisms, like spontaneous cyclization or conversion by is oQC. The different effects of QC depletion on the hypothalamic pituitary thyroid and gonadal axes might indicate slightly different modes of substrate conversion of both enzymes. The absence of significant abnormalities in QC knock-out mice suggests the presence of a therapeutic window for suppression of QC activity in current drug development. © 2011 by The American Society for Biochemistry and Molecular Biology, Inc.

Fritzsche G.,Diabetes Service Center | Kohnert K.-D.,Institute of Diabetes Gerhardt Katsch | Heinke P.,Institute of Diabetes Gerhardt Katsch | Vogt L.,Diabetes Service Center | Salzsieder E.,Institute of Diabetes Gerhardt Katsch
Diabetes Technology and Therapeutics | Year: 2011

Background: The mean amplitude of glycemic excursions (MAGE), traditionally estimated with a graphical approach, is often used to characterize glycemic variability. Here, we tested a proposed software program for calculating MAGE. Methods: Development and testing of the software was based on retrospective analyses of 72-h continuous glucose monitoring profile data collected during two different clinical studies involving 474 outpatients (458 with type 2 and 16 with type 1 diabetes) in three cohorts (two type 2 diabetes and one type 1 diabetes), using the CGMS® Gold™ (Medtronic MiniMed, Northridge, CA). Correlation analyses and a Bland-Altman procedure were used to compare the results of MAGE calculations performed using the developed computer program (MAGEC) and the original method (MAGEO). Results: Close linear correlations between MAGEC and MAGEO were documented in the two type 2 and the type 1 diabetes cohorts (r=0.954, 0.962, and 0.951, respectively; P<0.00001 for all), as was the absence of any systematic error between the two calculation methods. Comparison of the two indices revealed no within-group differences but did show differences among the various antihyperglycemic treatments (P<0.0001). In each of the study cohorts, MAGEC correlated strongly with the SD (r=0.914-0.943), moderately with the mean of daily differences (r=0.688-0.757), and weakly with glycosylated hemoglobin A1c and mean sensor glucose (r=0.285 and r=0.473, respectively). Conclusions: The proposed computerized calculation of MAGE is a practicable method that may provide an efficient tool for assessing glycemic variability. © Copyright 2011, Mary Ann Liebert, Inc. 2011.

Salzsieder E.,Institute of Diabetes Gerhardt Katsch | Salzsieder E.,Diabetes Service Center | Vogt L.,Diabetes Service Center | Augstein P.,Institute of Diabetes Gerhardt Katsch | Augstein P.,Diabetes Service Center
IFMBE Proceedings | Year: 2011

The model-based Karlsburg Diabetes Management System (KADIS ®) has been developed as a personalized decision support (PDS) program to assist physicians in their efforts to achieve optimal metabolic control in each individual patient. For this purpose, KADIS® was evaluated in combination with continuous glucose monitoring (CGM) under different conditions and, last but not least, applied in routine diabetes care. The outcomes of running of PDS for nearly 4 years in routine outpatient diabetes care has convincingly demonstrated that the recommendations provided to the physicians by KADIS® lead to significant improvement of individual metabolic control. It is concluded that this kind of model-based PDS provides an excellent tool to effectively guide physicians in decision making to achieve optimal metabolic control for their patients. © 2011 Springer-Verlag Berlin Heidelberg.

Kohnert K.-D.,Institute of Diabetes Gerhardt Katsch | Heinke P.,Institute of Diabetes Gerhardt Katsch | Vogt L.,Diabetes Service Center | Augstein P.,Institute of Diabetes Gerhardt Katsch | And 2 more authors.
Journal of Clinical and Translational Endocrinology | Year: 2014

Objective To determine whether characteristics of glucose dynamics are reflections of β-cell function or rather of inadequate diabetes control. Materials/methods We analyzed historical liquid meal tolerance test (LMTT) and continuous glucose monitoring (CGM) data, which had been obtained from 56 non-insulin treated type 2 diabetic outpatients during withdrawal of antidiabetic drugs. Computed CGM parameters included detrended fluctuation analysis (DFA)-based indices, autocorrelation function exponent, mean amplitude of glycemic excursions (MAGE), glucose SD, and measures of glycemic exposure. The LMTT-based disposition index (LMTT-DI) calculated from the ratio of the area-under-the-insulin-curve to the area-under-the-glucose-curve and Matsuda index was used to assess relationships among β-cell function, glucose profile complexity, autocorrelation function, and glycemic variability.Results The LMTT-DI was inverse linearly correlated with the short-range α1 and long-range scaling exponent α2 (r = -0.275 and -0.441, respectively, p < 0.01) such that lower glucose complexity was associated with better preserved insulin reserve, but it did not correlate with the autocorrelation decay exponent γ. By contrast, the LMTT-DI was strongly correlated with MAGE and SD (r = 0.625 and 0.646, both p < 0.001), demonstrating a curvilinear relationship between β-cell function and glycemic variability. On stepwise regression analyses, the LMTT-DI emerged as an independent contributor, explaining 20, 38, and 47% (all p < 0.001) of the variance in the long-range DFA scaling exponent, MAGE, and hemoglobin A1C, respectively, whereas insulin sensitivity failed to contribute independently.Conclusions Loss of complexity and increased variability in glucose profiles are associated with declining β-cell reserve and worsening glycemic control. © 2014 The Authors.

PubMed | Institute of Diabetes Gerhardt Katsch
Type: Journal Article | Journal: World journal of diabetes | Year: 2015

The benchmark for assessing quality of long-term glycemic control and adjustment of therapy is currently glycated hemoglobin (HbA1c). Despite its importance as an indicator for the development of diabetic complications, recent studies have revealed that this metric has some limitations; it conveys a rather complex message, which has to be taken into consideration for diabetes screening and treatment. On the basis of recent clinical trials, the relationship between HbA1c and cardiovascular outcomes in long-standing diabetes has been called into question. It becomes obvious that other surrogate and biomarkers are needed to better predict cardiovascular diabetes complications and assess efficiency of therapy. Glycated albumin, fructosamin, and 1,5-anhydroglucitol have received growing interest as alternative markers of glycemic control. In addition to measures of hyperglycemia, advanced glucose monitoring methods became available. An indispensible adjunct to HbA1c in routine diabetes care is self-monitoring of blood glucose. This monitoring method is now widely used, as it provides immediate feedback to patients on short-term changes, involving fasting, preprandial, and postprandial glucose levels. Beyond the traditional metrics, glycemic variability has been identified as a predictor of hypoglycemia, and it might also be implicated in the pathogenesis of vascular diabetes complications. Assessment of glycemic variability is thus important, but exact quantification requires frequently sampled glucose measurements. In order to optimize diabetes treatment, there is a need for both key metrics of glycemic control on a day-to-day basis and for more advanced, user-friendly monitoring methods. In addition to traditional discontinuous glucose testing, continuous glucose sensing has become a useful tool to reveal insufficient glycemic management. This new technology is particularly effective in patients with complicated diabetes and provides the opportunity to characterize glucose dynamics. Several continuous glucose monitoring (CGM) systems, which have shown usefulness in clinical practice, are presently on the market. They can broadly be divided into systems providing retrospective or real-time information on glucose patterns. The widespread clinical application of CGM is still hampered by the lack of generally accepted measures for assessment of glucose profiles and standardized reporting of glucose data. In this article, we will discuss advantages and limitations of various metrics for glycemic control as well as possibilities for evaluation of glucose data with the special focus on glycemic variability and application of CGM to improve individual diabetes management.

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