No abstract

The association between atherosclerosis and gut microbiota has been attracting increased attention. We previously demonstrated a possible link between gut microbiota and coronary artery disease. Our aim of this study was to clarify the gut microbiota profiles in coronary artery disease patients using data mining analysis of terminal restriction fragment length polymorphism (T-RFLP). This study included 39 coronary artery disease (CAD) patients and 30 age- and sex- matched no-CAD controls (Ctrls) with coronary risk factors. Bacterial DNA was extracted from their fecal samples and analyzed by T-RFLP and data mining analysis using the classification and regression algorithm. Five additional CAD patients were newly recruited to confirm the reliability of this analysis. Data mining analysis could divide the composition of gut microbiota into 2 characteristic nodes. The CAD group was classified into 4 CAD pattern nodes (35/39 = 90 %), while the Ctrl group was classified into 3 Ctrl pattern nodes (28/30 = 93 %). Five additional CAD samples were applied to the same dividing model, which could validate the accuracy to predict the risk of CAD by data mining analysis. We could demonstrate that operational taxonomic unit 853 (OTU853), OTU657, and OTU990 were determined important both by the data mining method and by the usual statistical comparison. We classified the gut microbiota profiles in coronary artery disease patients using data mining analysis of T-RFLP data and demonstrated the possibility that gut microbiota is a diagnostic marker of suffering from CAD.

To compare the effects of insulin degludec (IDeg) and insulin glargine U300 (IGlarU300) on glycaemic stability in subjects with type 1 diabetes. Materials and methods: In this multicentre, crossover trial, 46 individuals with type 1 diabetes and essentially undetectable circulating C-peptide were randomly assigned to either the IDeg-first/IGlarU300-second group or the IGlarU300-first/IDeg-second group, and were treated with the respective basal insulins for 4-week periods. Data were collected in the last week of each treatment period. The primary aim was to examine the potential non-inferiority of IDeg relative to IGlarU300 with regard to dayto-day variability, as evaluated by the standard deviation (SD) of fasting blood glucose (FBG) levels. Intra-day glycaemic variability and other variables were also determined by continuous glucose monitoring (CGM). Results: The SD of FBG for IDeg was non-inferior to that for IGlarU300. The mean of FBG, coefficient of variation of FBG, and various glycaemic variability indexes determined by CGM did not differ between the two insulins. Whereas the administered doses of the insulins also did not differ, the mean glycaemic value was lower for IDeg than IGlarU300; the time above the target range (>180 mg/dL [10.0 mmol/L]) and the time below the target range (<70 mg/dL [3.9 mmol/L]) were shorter and longer, respectively, for IDeg than IGlarU300. Conclusions: Our data suggest that IDeg and IGlarU300 have comparable glucosestabilizing effects in individuals with type 1 diabetes. However, the glucose-lowering effect of IDeg may be greater than that of IGlarU300 when titrated with a unit-based protocol. K E Y W O R D S basal insulin, clinical trial, continuous glucose monitoring, insulin therapy, type 1 diabetes 1 | INTRODUCTION Evidence suggests that, not only hyperglycaemia, but also the fluctuation and variability of glycaemia are related to the development of complications of diabetes. 1-8 Increased glycaemic variability is associated with a risk of hypoglycaemia, 9 which also contributes to the development of various health problems related to diabetes. 10,11 Minimization of glycaemic variability is thus an important issue in the choice of treatment for diabetes.

These results suggest pheochromocytoma and paraganglioma impair glucose tolerance primarily through impairment of insulin secretion-in particular, that of the early phase of the insulin secretory response. A prospective study with more patients is warranted to further confirm these results.

Aims/hypothesisWe compared the effects of insulin degludec (IDeg; Des(B30)LysB29(γ-Glu Nε-hexadecandioyl) human insulin) and insulin glargine (IGlar; A21Gly,B31Arg,B32Arg human insulin) on the day-to-day variability of fasting plasma glucose (FPG) levels in individuals with type 1 diabetes treated with basal-bolus insulin injections.MethodsThe effects of basal-bolus insulin therapy for 4 weeks with either IDeg or IGlar as the basal insulin in adult C-peptide-negative outpatients with type 1 diabetes were investigated in an open-label, multicentre, randomised, crossover trial. Randomisation was conducted using a centralised allocation process. The primary endpoints were the SD and CV of FPG during the final week of each treatment period. Secondary endpoints included serum glycoalbumin level, daily dose of insulin, intraday glycaemic variability and frequency of severe hypoglycaemia.ResultsThirty-six randomised participants (17 in the IDeg/IGlar and 19 in the IGlar/IDeg groups) were recruited, and data for 32 participants who completed the trial were analysed. The mean (7.74 ± 1.76 vs 8.56 ± 2.06 mmol/l; p = 0.04) and SD (2.60 ± 0.97 vs 3.19 ± 1.36 mmol/l; p = 0.03) of FPG were lower during IDeg treatment than during IGlar treatment, whereas the CV did not differ between the two treatments. The dose of IDeg was smaller than that of IGlar (11.0 ± 5.2 vs 11.8 ± 5.6 U/day; p < 0.01), but other secondary endpoints did not differ between the treatments.Conclusions/interpretationIDeg yielded a lower FPG level and smaller day-to-day variability of FPG at a lower daily dose compared with IGlar in participants with type 1 diabetes. IDeg serves as a good option for basal insulin in the treatment of type 1 diabetes.Trial registration: University Hospital Medical Information Network 000009965.Funding: This research recieved no specific grant from any funding agency in the public, commercial or not-for-profit sectors.