ORCID Profile
0000-0003-4376-6973
Current Organisation
The University of Edinburgh
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Publisher: SAGE Publications
Date: 29-03-2022
DOI: 10.1177/19322968221085273
Abstract: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia very high–glucose and high-glucose hyperglycemia time in range mean glucose and coefficient of variation. The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines ide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an in idual over time and compare groups of in iduals. The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.
Publisher: American Diabetes Association
Date: 14-03-2012
DOI: 10.2337/DB11-0931
Abstract: Recent trials show salicylates improve glycemic control in type 2 diabetes, but the mechanism is poorly understood. Expression of the glucocorticoid-generating enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) in adipose tissue is increased in vitro by proinflammatory cytokines and upregulated in obesity. 11β-HSD1 inhibition enhances insulin sensitivity. We hypothesized that salicylates downregulate 11β-HSD1 expression, contributing to their metabolic efficacy. We treated diet-induced obese (DIO) 11β-HSD1–deficient mice and C57Bl/6 mice with sodium salicylate for 4 weeks. Glucose tolerance was assessed in vivo. Tissue transcript levels were assessed by quantitative PCR and enzyme activity by incubation with 3H-steroid. Two weeks’ administration of salsalate was also investigated in a randomized double-blind placebo-controlled crossover study in 16 men, with measurement of liver 11β-HSD1 activity in vivo and adipose tissue 11β-HSD1 transcript levels ex vivo. In C57Bl/6 DIO mice, salicylate improved glucose tolerance and downregulated 11β-HSD1 mRNA and activity selectively in visceral adipose. DIO 11β-HSD1–deficient mice were resistant to these metabolic effects of salicylate. In men, salsalate reduced 11β-HSD1 expression in subcutaneous adipose, and in vitro salicylate treatment reduced adipocyte 11β-HSD1 expression and induced adiponectin expression only in the presence of 11β-HSD1 substrate. Reduced intra-adipose glucocorticoid regeneration by 11β-HSD1 is a novel mechanism that contributes to the metabolic efficacy of salicylates.
Publisher: Wiley
Date: 09-2006
DOI: 10.1038/OBY.2006.175
Abstract: Increased mRNA and activity levels of 11beta-hydroxysteroid dehydrogenase type 1 (11betaHSD1) in human adipose tissue (AT) are associated with obesity and insulin resistance. The aim of our study was to investigate whether 11betaHSD1 expression or activity in abdominal subcutaneous AT of non-diabetic subjects are associated with subsequent changes in body weight and insulin resistance [homeostasis model assessment of insulin resistance (HOMA-IR)]. Prospective analyses were performed in 20 subjects (two whites and 18 Pima Indians) who had baseline measurements of 11betaHSD1 mRNA and activity in whole AT (follow-up, 0.3 to 4.9 years) and in 47 Pima Indians who had baseline assessments of 11betaHSD1 mRNA in isolated adipocytes (follow-up, 0.8 to 5.3 years). In whole AT, although 11betaHSD1 mRNA levels showed positive associations with changes in weight and HOMA-IR, 11betaHSD1 activity was associated with changes in HOMA-IR but not in body weight. 11betaHSD1 mRNA levels in isolated adipocytes were not associated with follow-up changes in any of the anthropometric or metabolic variables. Our results indicate that increased expression of 11betaHSD1 in subcutaneous abdominal AT may contribute to risk of worsening obesity and insulin resistance. This prospective relationship does not seem to be mediated by increased 11betaHSD1 expression in adipocytes.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Deborah Wake.