BackgroundDiabetic complications may be associated with impaired time-dependent glycemic control. Therefore, long-term glycemic variability, assessed by variations in haemoglobin A1c (HbA1c), may be a potential risk factor for microvascular complications, such as diabetic peripheral neuropathy (DPN). We investigated the association of HbA1c variability with DPN in patients with type 2 diabetes.MethodsIn this cross-sectional study, 563 type 2 diabetic patients who had been screened for DPN and undergone quarterly HbA1c measurements during the year preceding enrolment were recruited. DPN was confirmed in patients displaying both clinical manifestations of neuropathy and abnormalities in a nerve conduction evaluation. HbA1c variability was assessed by the coefficient of variation of HbA1c (CV-HbA1c), and the mean of HbA1c (M-HbA1c) was calculated. In addition, medical history and clinical data were collected.ResultsAmong the recruited patients, 18.1% (n = 102) were found to have DPN, and these patients also presented with a higher CV-HbA1c than the patients without DPN (p < 0.001). The proportion of patients with DPN increased significantly from 6.9% in the first to 19.1% in the second and 28.5% in the third tertile of CV-HbA1c (p for trend < 0.001). After adjusting for initial HbA1c, M-HbA1c and other clinical factors via multiple logistic regression analysis, the odds ratios (ORs) for DPN in the second and third versus those in the first CV-HbA1c tertile were 3.61 (95% CI 1.62–8.04) and 6.48 (2.86–14.72), respectively. The area under the receiver operating characteristic (ROC) curve of CV-HbA1c was larger than that of M-HbA1c, at 0.711 (95% CI 0.659–0.763) and 0.662 (0.604–0.721), respectively. ROC analysis also revealed that the optimal cutoff value of CV-HbA1c to indicate DPN was 15.15%, and its corresponding sensitivity and specificity were 66.67% and 65.73%, respectively.ConclusionsIncreased HbA1c variability is closely associated with DPN in type 2 diabetic patients and could be considered as a potent indicator for DPN in these patients.
These authors contributed equally to this work. SUMMARYHeterotrimeric G proteins function as key players in hydrogen peroxide (H 2 O 2 ) production in plant cells, but whether G proteins mediate ethylene-induced H 2 O 2 production and stomatal closure are not clear. Here, evidences are provided to show the Ga subunit GPA1 as a missing link between ethylene and H 2 O 2 in guard cell ethylene signalling. In wild-type leaves, ethylene-triggered H 2 O 2 synthesis and stomatal closure were dependent on activation of Ga. GPA1 mutants showed the defect of ethylene-induced H 2 O 2 production and stomatal closure, whereas wGa and cGa overexpression lines showed faster stomatal closure and H 2 O 2 production in response to ethylene. Ethylene-triggered H 2 O 2 generation and stomatal closure were impaired in RAN1, ETR1, ERS1 and EIN4 mutants but not impaired in ETR2 and ERS2 mutants. Ga activator and H 2 O 2 rescued the defect of RAN1 and EIN4 mutants or etr1-3 in ethylene-induced H 2 O 2 production and stomatal closure, but only rescued the defect of ERS1 mutants or etr1-1 and etr1-9 in ethylene-induced H 2 O 2 production. Stomata of CTR1 mutants showed constitutive H 2 O 2 production and stomatal closure, but which could be abolished by Ga inhibitor. Stomata of EIN2, EIN3 and ARR2 mutants did not close in responses to ethylene, Ga activator or H 2 O 2 , but do generate H 2 O 2 following challenge of ethylene or Ga activator. The data indicate that Ga mediates ethylene-induced stomatal closure via H 2 O 2 production, and acts downstream of RAN1, ETR1, ERS1, EIN4 and CTR1 and upstream of EIN2, EIN3 and ARR2. The data also show that ETR1 and ERS1 mediate both ethylene and H 2 O 2 signalling in guard cells.
In addition to conventional risks including diabetic duration, HOMA-IR and HbA1c, increased glycaemic variability assessed by MAGE is a significant independent contributor to DPN in type 2 diabetic patients.
ObjectivesProlonged heart rate-corrected QT(QTc) interval is related to ventricular arrhythmia and cardiovascular mortality, with considerably high prevalence of type 2 diabetes. Additionally, long-term glycaemic variability could be a significant risk factor for diabetic complications in addition to chronic hyperglycaemia. We compared the associations of long-term glycaemic variability versus sustained chronic hyperglycaemia with the QTc interval among type 2 diabetes patients.MethodsIn this cross-sectional study, 2904 type 2 diabetes patients were recruited who had undergone at least four fasting plasma glucose (FPG) and 2-hour postprandial plasma glucose (PPG) measurements (at least once for every 3 months, respectively) during the preceding year. Long-term glycaemic variabilities of FPG and 2-hour PPG were assessed by their standard deviations (SD-FPG and SD-PPG, respectively), and chronic fasting and postprandial hyperglycaemia were assessed by their means (M-FPG and M-PPG, respectively). HbA1c was also determined upon enrolment to assess current overall glycaemic control. QTc interval was estimated from resting 12-lead electrocardiograms, and more than 440 ms was considered abnormally prolonged.ResultsPatients with prolonged QTc interval (≥440 ms) had greater M-FPG, M-PPG, SD-PPG and HbA1c than those with normal QTc interval but comparable SD-FPG. QTc interval was correlated with M-FPG, M-PPG, SD-PPG and HbA1c (r = 0.133, 0.153, 0.245 and 0.207, respectively, p = 0.000) but not with SD-FPG (r = 0.024, p = 0.189). After adjusting for metabolic risk factors via multiple linear regression analysis, SD-PPG, M-PPG and HbA1c (t = 12.16, 2.69 and 10.16, respectively, p = 0.000) were the major independent contributors to the increased QTc interval. The proportion of prolonged QTc interval increased significantly from 10.9% to 14.2% to 26.6% for the first (T1) to second (T2) to third (T3) tertiles of SD-PPG. After adjusting via multiple logistic regression analysis, the odd ratios of prolonged QTc interval of the T2 and T3 versus the T1 of SD-PPG were 1.15 (95% CI, 0.82–1.60) and 2.62 (1.92–3.57), respectively.ConclusionsIncreased long-term variability of PPG is a strong independent risk factor for prolonged QTc interval in type 2 diabetes patients, in addition to long-term postprandial hyperglycaemia and current HbA1c.
Type 2 diabetes (T2D) is characterized by islet β-cell dysfunction and impaired suppression of glucagon secretion of α-cells in response to oral hyperglycaemia. Bile acid (BA) metabolism plays a dominant role in maintaining glucose homeostasis. So we evaluated the association of fasting serum total bile acids (S-TBAs) with insulin sensitivity, islet β-cell function and glucagon levels in T2D. Total 2,952 T2D patients with fasting S-TBAs in the normal range were recruited and received oral glucose tolerance tests for determination of fasting and postchallenge glucose, C-peptide and glucagon. Fasting and systemic insulin sensitivity were assessed by homeostasis model assessment (HOMA) and Matsuda index using Cpeptide, i.e., IS HOMA-cp and ISI M-cp , respectively. Islet β-cell function was assessed by the insulin-secretion-sensitivity-index-2 using C-peptide (ISSI2 cp ). The area under the glucagon curve (AUC gla ) was used to assess postchallenge glucagon. The results showed IS HOMA-cp , ISI M-cp and ISSI2 cp decreased, while AUC gla notably increased, across ascending quartiles of S-TBAs but not fasting glucagon. Moreover, S-TBAs were inversely correlated with IS HOMA-cp , ISI M-cp and ISSI2 cp (r = -0.21, -0.15 and -0.25, respectively, p < 0.001) and positively correlated with AUC gla (r = 0.32, p < 0.001) but not with fasting glucagon (r = 0.033, p = 0.070). Furthermore, after adjusting for other clinical covariates by multiple linear regression analyses, the S-TBAs were independently associated with IS HOMA-cp (β = -0.04, t = -2.82, p = 0.005), ISI M-cp (β = -0.11, t = -7.05, p < 0.001), ISSI2 cp (β = -0.15, t = -10.26, p < 0.001) and AUC gla (β = 0.29, t = 19.08, p < 0.001). Increased fasting S-TBAs are associated with blunted fasting and systemic insulin sensitivity, impaired islet β-cell function and increased glucagon levels in response to glucose challenge in T2D.
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