Associations of serum glucagon levels with glycemic variability in type 1 diabetes with different disease durations

Glucagon receptor activation contributes to the development of kidney injury

The underlying causes of diabetic kidney disease are still largely unknown. New insights into the contributing causes of diabetic nephropathy are important to prevent this complication. Hyperglycemia and hypertension are some of the risk factors for diabetic nephropathy. However, the incidence of diabetic nephropathy is increasing despite efforts to normalize blood glucose levels and blood pressure. Therefore, other factors should be investigated as causes of diabetic nephropathy. We investigated whether long-term increased plasma levels of glucagon contribute to the development of pathophysiological changes in kidney function as seen in patients with diabetic nephropathy. Using mouse models of chronic activation and inactivation of glucagon receptor signaling, we investigated whether glucagon is involved in changes in renal function, renal structure, and transcriptional changes. We found several histopathological changes in the kidney, such as thickening of the parietal layer of Bowman's capsule, glomerular mesangial cell expansion, and significant albuminuria in the mice with activated glucagon receptor signaling. Opposite effects on mesangial area expansion and the development of albuminuria were demonstrated in mice with glucagon receptor inactivation. RNA sequencing data revealed that transcription of genes related to fatty acid metabolism, podocytes, Na+-K+-ATPase, and sodium/glucose transport was significantly changed in mice with activated glucagon receptor signaling. These data implicate that glucagon receptor signaling is involved in the development of kidney injury, as seen in type 2 diabetes, and that glucagon receptor is a potential therapeutic target in the treatment of diabetes. NEW & NOTEWORTHY This study suggests that the glucagon receptor is a potential therapeutic target in the treatment of diabetic kidney disease. We show, in mice, that long-term treatment with a glucagon analog showed not only pathophysiological changes and changes in renal function but also transcriptional changes in the kidneys, whereas opposite effects were demonstrated in mice with glucagon receptor inactivation. Therefore, the use of glucagon in a treatment regimen requires investigation of possible metabolic and renal abnormalities.

Abnormal late postprandial glucagon response in type 1 diabetes is a function of differences in stimulated C-peptide concentrations

Background

The functional changes in alpha cells in patients with type 1 diabetes (T1D) with different residual beta cell functions remain poorly elucidated. The study aimed to investigate the relationship between glucagon secretion and C-peptide levels and to explore the relationship between glucagon response and glucose increment in respond to a secretagogue in a steamed bread meal tolerance test (BMTT) in T1D.

Methods

The study enrolled 43 adult patients with T1D and 24 healthy control subjects. Patients with T1D who underwent BMTT were divided into two groups based on peak C-peptide levels: C peptide low (CPL; C-peptide < 200 pmol/L; n=14) and high (CPH; C peptide ≥ 200 pmol/L; n=29). Plasma glucose, C-peptide, glucagon levels at 0, 30, 60, 120, and 180 min were measured. The glucagon response to the BMTT was defined by areas under the curve (AUC) as early (AUC0-30), late (AUC30-180), or total (AUC0-180) glucagon.

Results

Compared to healthy individuals, fasting plasma glucagon was lower and postprandial plasma glucagon level was increased in patients with T1D. Glucagon levels after BMTT between the CPL and CPH group showed significant group by time interaction. Peak glucagon and glucagon at 60-180 min, total and late glucagon response were higher in CPL than CPH group, while fasting glucagon and early glucagon response adjusted for glucose were comparable between CPL and CPH group. The higher late glucagon response and late glucagon response adjusted for glucose were associated with lower peak C-peptide in T1D. The higher late glucagon response and lower peak C-peptide were associated with the higher value of ▵glucose at 180 min.

Conclusion

Stimulated C-peptide levels affect the paradoxical increase in postprandial glucagon secretion in patients with T1D, especially late glucagon response. The exaggerated postprandial glucagon secretion further stimulates the elevation of postprandial glucose in patients with T1D.

Advances in clinical research on glucagon

We are now celebrating the 100th anniversary of the discovery of an important pancreatic hormone, glucagon. Glucagon is historically described as a diabetogenic hormone elevating glucose levels via increases in insulin resistance and hepatic gluconeogenesis. The more recently identified actions of glucagon include not only its pathophysiologic effects on glucose metabolism but also its significant roles in amino-acid metabolism in the liver. The possibility that abnormalities in α-cells' secretion of glucagon in metabolic disorders are a compensatory adaptation for the maintenance of metabolic homeostasis is another current issue. However, the clinical research concerning glucagon has been considerably behind the advances in basic research due to the lack of suitable methodology for obtaining precise measurements of plasma glucagon levels in humans. The precise physiology of glucagon secretory dynamics in individuals with metabolic dysfunction (including diabetes) has been clarified since the development in 2014 of a quantitative measurement technique for glucagon. In this review, we summarize the advances in the clinical research concerning glucagon, including those of our studies and the relevant literature.

Polyester Nanoparticles with Controlled Topography for Peroral Drug Delivery Using Insulin as a Model Protein

Receptor-mediated polyester drug delivery systems have tremendous potential for improving the clinical performance of existing pharmaceutical drugs. Despite significant progress made in this area, it remains unclear how and to what extent the polyester nanoparticle surface topography would affect the in vitro, ex vivo and in vivo performance of a drug, and if there exists a correlation between in vitro and in vivo, as well as healthy versus pathophysiological states. Herein, we report a systematic investigation of the interactions between ligands and receptors as a function of the linker length, two-carbon (2C) versus four-carbon (4C). The in vitro, ex vivo and in vivo in healthy models validate the hypothesis that 4C has better reach and binding to the receptors. The results indicate that 4C offered better performance over 2C in vivo in improving the oral bioavailability of insulin (INS) by 1.1-fold (3.5-fold compared to unfunctionalized nanoparticles) in a healthy rat model. Similar observations were made in pathophysiological models; however, the effects were less prominent compared to those in healthy models. Throughout, ligand decorated nanoparticles outperformed unfunctionalized nanoparticles. Finally, a semimechanistic pharmacokinetic and pharmacodynamic (PKPD) model was developed using the experimental data sets to quantitatively evaluate the effect of P2Ns-GA on oral bioavailability and efficacy of insulin. The study presents a sophisticated oral delivery system for INS or hydrophilic therapeutic cargo, highlighting the significant impact on bioavailability that minor adjustments to the surface chemistry can have.

Association between hemoglobin glycation index and diabetic kidney disease in type 2 diabetes mellitus in China: A cross- sectional inpatient study

Objective

To investigate the association between Hemoglobin Glycation Index (HGI) and Diabetic Kidney Disease (DKD) in Chinese type 2 diabetic individuals and to construct a risk score based on HGI to predict a person's risk of DKD.

Methods

We retrospectively analyzed 1622 patients with type 2 diabetes mellitus (T2DM). HGI was obtained by calculating the fasting plasma glucose (FPG) level into the formula, and they were grouped into low HGI group (L-HGI), medium HGI group (H-HGI) and high HGI group (H-HGI) according to tri-sectional quantile of HGI. The occurrence of DKD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of DKD in patients with T2DM.

Results

A total of 1622 patients with T2DM were enrolled in the study. Among them, 390 cases were DKD. The prevalence of DKD among the three groups was 16.6%, 24.2% and 31.3%. The difference was statistically significant (P = 0.000). There were significant differences in age (P=0.033), T2DM duration (P=0.005), systolic blood pressure (SBP) (P=0.003), glycosylated hemoglobin (HbA1c) (P=0.000), FPG (P=0.032), 2-hour postprandial plasma glucose (2h-PPG) (P=0.000), fasting C-peptide FCP (P=0.000), 2-hour postprandial C-peptide (2h-CP) (P=0.000), total cholesterol (TC) (P=0.003), low density lipoprotein cholesterol (LDL-C) (P=0.000), serum creatinine (sCr) (P=0.001), estimated glomerular filtration rate (eGFR) (P=0.000) among the three groups. Mantel-Haenszel chi-square test showed that there was a linear relationship between HGI and DKD (x2=177.469, p < 0.001). Pearson correlation analysis showed that with the increase of HGI level the prevalence of DKD was increasing (R= 0.445, P=0.000). It was indicated by univariate logistic regression analysis that individuals in H-HGI was more likely to develop DKD (OR: 2.283, 95% CI: 1.708~ 3.052) when compared with L-HGI. Adjusted to multiple factors, this trend still remained significant (OR: 2.660, 95% CI: 1.935~ 3.657). The combined DKD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.702.

Conclusions

High HGI is associated with an increased risk of DKD. DKD risk score may be used as one of the risk predictors of DKD in type 2 diabetic population.

Association between hemoglobin glycation index and non-alcoholic fatty liver disease

OBJECTIVE

The hemoglobin glycation index (HGI) reflects biological variability in hemoglobin A1c. Even so, studies on the relationship between HGI and non-alcoholic fatty liver disease (NAFLD) are limited. Therefore, this study aimed to explore the relationship between HGI and NAFLD. In addition, the study also aimed to provide new methods to identify patients with a high risk for the development of NAFLD.

METHODS

This was a retrospective study based on physical examination data from Japan. Patients were divided into quartiles (Q1-Q4) according to their HGI level; the lowest quartile (Q1) was used as the reference group. Patents were also classified into two subgroups based on the presence or absence of NAFLD. Baseline characteristics between the groups were compared. Multivariate logistic regression analysis was used to investigate the association between the HGI and NAFLD. A mediation analysis examined the mediation relationship between HGI and NAFLD. Subgroup analyses were performed to the reliability of the results.

RESULTS

A total of 14280 patients were eligible for inclusion in this study; 2515 had NAFLD. Patients in the NAFLD group had higher levels of HGI than patients in the non-NAFLD group. Increases in HGI correlated with an increased risk of NAFLD. After adjusting for confounding factors, the multivariate logistic regression analysis revealed that HGI was positively related to the prevalence of NAFLD. In addition, mediation analysis showed that body mass index (BMI) partly mediated the indirect impact of HGI on NAFLD preference. Subgroup analyses were performed according to age, sex, smoking status, and waist circumference. Our results indicated that HGI significantly correlated with NAFLD in patients with one of the following factors: age ≤60 years, BMI >28 kg/m², female sex, a history of smoking, and abdominal obesity.

CONCLUSIONS

HGI was an independent risk factor for NAFLD, and BMI partly mediated the association between HGI and NAFLD.

Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts

BACKGROUND

Excess carbohydrate intake during hypoglycemia can lead to rebound hyperglycemia (RH). We investigated associations between RH and use of real-time continuous glucose monitoring (rtCGM) and an rtCGM system's predictive alert.

METHODS

RH events were series of sensor glucose values (SGVs) >180 mg/dL starting within two hours of an antecedent SGV <70 mg/dL. Events were characterized by their frequency, duration (consecutive SGVs >180 mg/dL × five minutes), and severity (area under the glucose concentration-time curve). To assess the impact of rtCGM, data gathered during the four-week baseline phase (without rtCGM) and four-week follow-up phase (with rtCGM) from 75 participants in the HypoDE clinical trial (NCT02671968) of hypoglycemia-unaware individuals were compared. To assess the impact of predictive alerts, we identified a convenience sample of 24 518 users of an rtCGM system without predictive alerts who transitioned to a system whose predictive alert signals an SGV ≤55 mg/dL within 20 minutes (Dexcom G5 and G6, respectively). RH events from periods of blinded versus unblinded rtCGM wear and from periods of G5 and G6 wear were compared with paired t tests.

RESULTS

Compared to RH events in the HypoDE baseline phase, the mean frequency, duration, and severity of events fell by 14%, 12%, and 23%, respectively, in the follow-up phase (all P < .05). Compared to RH events during G5 use, the mean frequency, duration, and severity of events fell by 7%, 8%, and 13%, respectively, during G6 use (all P < .001).

CONCLUSIONS

Rebound hypreglycemia can be objectively quantified and mitigated with rtCGM and rtCGM-based predictive alerts.

The Role of Glucagon in Glycemic Variability in Type 1 Diabetes: A Narrative Review

Type 1 diabetes mellitus (T1DM) is a progressive disease as a result of the severe destruction of islet β-cell function, which leads to high glucose variability in patients. However, α-cell function is also compromised in patients with T1DM, characterized by aberrant fasting and postprandial glucagon secretion. According to recent studies, this aberrant glucagon secretion plays an increasing role in hyperglycemia, insulin-induced hypoglycemia and exercise-associated hypoglycemia in patients with T1DM. With application of continuous glucose monitoring system, dozens of metrics enable the assessment of glycemic variability, which is an integral component of glycemic control for patients with T1DM. There is growing evidences to illustrate the contribution of glucagon secretion to the glycemic variability in patients with T1DM, which may promote the development of new treatment strategies aiming to mitigate glycemic variability associated with aberrant glucagon secretion.

Association of sleep quality with glycemic variability assessed by flash glucose monitoring in patients with type 2 diabetes

BACKGROUND

Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).

METHODS

We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR_3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.

RESULTS

HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR_3.9-10 was decreased (p for trend  <  0.05), but not MODD (p for trend  =  0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r =  0.322, 0.361, 0.308 and 0.354, respectively, p  <  0.001) and were inversely correlated with TIR_3.9-10 (r  =  - 0.386, p  <  0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β  =  0.251, t  =  2.112, p  =  0.041), CV (β  =  0.286, t  =  2.207, p  =  0.033), MAGE (β  =  0.323, t  =  2.489, p  =  0.018), and TIR_3.9-10 (β  =  - 0.401, t  =  - 3.930, p  <  0.001) but not for MODD (β  =  0.188, t  =  1.374, p  =  0.177).

CONCLUSIONS

Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Association between time in range, a novel measurement of glycemic control and islet secretory function in chinese patients with type 2 diabetes mellitus-An observational study

AIMS

To explore the association between dynamic islet secretory function and TIR (time in range), a new valuable metric of glycemic control in type 2 diabetes (T2D).

METHODS

In this observational study 256 patients with type 2 diabetes were included and continuous glucose monitoring system (CGMS) were applied to monitor blood glucose and also the calculation of TIR [the time spent in an individual's target glucose range (usually 3.9-10 mmol/L)]. The participants were divided into 3 groups according to the tertiles of TIR, 85 cases with TIR ≥ 65.05% (T1 group), 86 cases with 41.84 < TIR ≤ 65.05% (T2 group) and 85 cases with TIR < 41.84% (T3 group). Serum glucagon (GLA0h, GLA0.5h, GLA1h, GLA2h, GLA3h), C-peptide (Cp0h, Cp0.5h, Cp1h, Cp2h, Cp3h) concentration at different time points were measured after a 100 g standard steamed buns meal test to assess the pancreatic alpha cell and beta cell function. Spearman correlation analysis and multivariate linear stepwise regression analysis were adopted for statistical analysis.

RESULTS

The average age and diabetes duration of all the participants were separately 56.09 ± 13.8 years and 8.0 (4.0,15.0) years. Compared with patients in T1 group, participants in group T2 and T3 tend to have a lower concentration of C-peptide at all time points, as well as GLA0h, GLA2h and GLA3h (p < 0.05). TIR was positively correlated with C-peptide at different time points, area under the curve of C-peptide in half an hour (AUCCp0.5h), GLA0h, GLA3h, area under the curve of glucagon in half an hour (AUCGLA0.5h)(rs = 0.263, 0.414, 0.510, 0.587, 0.528, 0.360, 0.259, 0.144 and 0.208, respectively, p < 0.05) and was negatively correlated with the increment of serum glucagon from baseline at 0.5 h, 1 h and 2 h after the standard energy loaded(△GLA0.5h, △GLA1h, △GLA2h)(rs = -0.152,-0.172 and -0.203, respectively, p < 0.05). Cp2h, Cp0h and GLA0h were independent factors for TIR (β = 6.558,-6.930, 0.247, respectively, p < 0.01).

CONCLUSION

Both islet alpha cell and beta cell secretory function have important influence on TIR, a novel vital index of glycemic fluctuation.

HbA1C as a Biomarker of Non-alcoholic Fatty Liver Disease: Comparison with Anthropometric Parameters

BACKGROUND AND AIMS

Multiple non-invasive methods including radiological, anthropometric and biochemical markers have been reported with variable performance. The present study assessed glycosylated hemoglobin (HbA_1C) as a biomarker to predict non-alcoholic fatty liver disease (NAFLD) and its severity, compared with body mass index (BMI), waist to hip ratio (WHR) and waist circumference (WC).

METHODS

This case control study included 450 individuals, including 150 cases and 300 age- and gender-matched controls recruited from the Dow Radiology Institute on the basis of radiological findings of fatty infiltration on abdominal ultrasound through convenient sampling. BMI, WHR and WC were measured according to standard protocols. HbA_1C was determined by turbidimetric inhibition immunoassay.

RESULTS

Among the cases and controls, 66% and 32% had HbA_1C levels higher than 5.7% respectively. HbA_1C and BMI were significantly associated with NAFLD [crude odds ratio (cOR)=4.12, 2.88, 2.25 (overweight) and 4.32 (obese)]. WC was found to be significantly associated with NAFLD for both genders (cOR in males=5.50 and females=5.79, p<0.01). After adjustment for other parameters, HbA_1C and WC were found to be significantly associated with NAFLD (aOR=3.40, p<0.001) along with WC in males (aOR=2.91, p<0.05) and in females (aOR=4.28, p<0.05). A significant rise in severity of hepatic steatosis was noted with increases in HbA_1C, BMI and WC. HbA_1C possessed a positive predictive value of 76% for the study population [0.76, confidence interval (CI): 0.715-0.809], 70.6% for males (0.706, CI: 0.629-0.783) and 80% for females (0.80, CI: 0.741-0.858).

CONCLUSIONS

Higher than normal HbA_1C and WC measurements possess a more than 70% potential to predict NAFLD. It is the single risk factor that is strongly associated with NAFLD after adjustment for indices of body measurements. HbA_1C may be presented as a potential biomarker for NAFLD in examination with other anthropometric measures in the adult population.

Correlation Between Hemoglobin Glycosylation Index and Nerve Conduction Velocity in Patients with Type 2 Diabetes Mellitus

OBJECTIVE

This study aimed to investigate the relationship between hemoglobin glycation variation index (HGI) and peripheral nerve conduction velocity (NCV) in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This is a cross-sectional study, including 324 patients with T2DM were included in this study. Basic information and blood indicators were collected. The motor conduction velocities (MCV) of the bilateral ulnar nerve, median nerve, and common peroneal nerve, and the sensory conduction velocities (SCV) of the ulnar nerve, median nerve, and superficial peroneal nerve were measured. The patients were divided into two groups according to the NCV: normal nerve conduction group (NCVN group) and abnormal nerve conduction group (NCVA group). When the NCV is less than the specific normal value, the patients were divided into the NCVA group. HGI was calculated as the difference between the measured and predicted values of glycosylated hemoglobin (HbA1c) using the linear relationship between HbA1c level and fasting plasma glucose levels. At last, all study participants were divided into High HGI and Low HGI groups using the median of HGI as the boundary. The study also analyzed the correlation between HGI and NCV.

RESULTS

Compared to the NCVN group, the HGI levels of the NCVA group were higher (P < 0.001). The prevalence of NCVA in the high HGI group was higher than that in the low HGI group (P = 0.004). HGI was negatively correlated with bilateral ulnar nerve MCV, bilateral median nerve MCV, bilateral common peroneal nerve MCV, bilateral median nerve SCV and left superficial peroneal nerve SCV, and the correlation still existed after adjusting for confounding factors.

CONCLUSION

This study found that HGI is inversely associated with NCV in patients with T2DM, and this correlation is higher between HGI and MCV of peripheral nerve.

Pasireotide-induced hyperglycemia in a patient with Cushing's disease: Potential use of sodium-glucose cotransporter 2 inhibitor and glucagon-like peptide-1 receptor agonist for treatment

Pasireotide improves hypercortisolemia and induces hyperglycemia via somatostatin receptor type-5 stimulation. GLP-1RA and SGLT2 inhibitor potentially help regulate hyperglycemia in patients with Cushing's disease, especially after pasireotide administration.

Association between Hemoglobin Glycation Index and NAFLD in Chinese Nondiabetic Individuals

PURPOSE

Limited studies have preliminarily identified a positive association between nonalcoholic fatty liver disease (NAFLD) and hemoglobin glycation index (HGI). However, this association has not been fully established. We aim to investigate the association between NAFLD and HGI in Chinese nondiabetic individuals and to construct a risk score based on HGI to predict a person's risk of NAFLD.

METHODS

After strict exclusion criteria, 5,903 individuals were included in this retrospective cross-sectional study. We randomly selected 1,967 subjects in the enrollment to obtain an equation of linear regression, which was used to calculate predicted HbA1c and drive HGI. The other subjects were classified into four categories according to HGI level (≤-0.22, -0.21∼0.02, 0.03∼0.28, and ≥0.29). All subjects retrospectively reviewed the baseline characteristics, laboratory examinations, and abdominal ultrasonography.

RESULTS

The prevalence of NAFLD in this population was 20.7%, which increases along with the growth of HGI levels (P < 0.001). Adjusted to multiple factors, this trend still remained significant (OR: 1.172 (95% CI, 1.074-1.279)). The combined NAFLD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.85 provided sensitivity, specificity, positive predictive value, and a negative predictive value for NAFLD of 84.4%, 71.3%, 65.0%, and 88.0%, respectively.

CONCLUSIONS

NAFLD is independently associated with HGI levels in Chinese nondiabetic individuals. And, NAFLD risk score may be used as one of the risk predictors of NAFLD in nondiabetic population.

Molecular Mechanisms of Glucose Fluctuations on Diabetic Complications

Accumulating evidence indicates the occurrence and development of diabetic complications relates to not only constant high plasma glucose, but also glucose fluctuations which affect various kinds of molecular mechanisms in various target cells and tissues. In this review, we detail reactive oxygen species and their potentially damaging effects upon glucose fluctuations and resultant downstream regulation of protein signaling pathways, including protein kinase C, protein kinase B, nuclear factor-κB, and the mitogen-activated protein kinase signaling pathway. A deeper understanding of glucose-fluctuation-related molecular mechanisms in the development of diabetic complications may enable more potential target therapies in future.