Association between 1,5-Anhydroglucitol and Acute C Peptide Response to Arginine among Patients with Type 2 Diabetes

Relationship Between 1,5-Anhydroglucitol and Renal Function Assessed by Dynamic Renal Scintigraphy in Type 2 Diabetes

CONTEXT

The reliability of serum 1,5-anhydroglucitol (1,5-AG) in patients with type 2 diabetes and renal insufficiency remains controversial.

OBJECTIVE

To evaluate the relationship between renal function and serum 1,5-AG and to assess the extent to which renal function influences 1,5-AG.

METHODS

A total of 5337 participants with type 2 diabetes were enrolled. The measured glomerular filtration rate (mGFR) was assayed using 99mTc-DTPA dynamic renal scintigraphy. All subjects were stratified into 5 groups based on mGFR (≥120 [n = 507], 90-120 [n = 2015], 60-90 [n = 2178], 30-60 [n = 604], and <30 mL/min/1.73 m2 [n = 33]).

RESULTS

Overall, the serum 1,5-AG and mGFR levels were 3.3 (1.7-7.0) μg/mL and 88.6 ± 24.1 mL/min/1.73 m2, respectively. mGFR was found to be negatively correlated with 1,5-AG levels (r = -0.189, P < .001). Multiple linear regression revealed that mGFR was independently and negatively related to serum 1,5-AG after adjusting for covariates including hemoglobin A1c (HbA1c; P < .001). In subgroups with mGFR ≥ 30 mL/min/1.73 m2, the correlation coefficients between 1,5-AG and HbA1c, fasting plasma glucose, postprandial plasma glucose, and the differences between postprandial and fasting plasma glucose remained significant (range, -0.126 to -0.743, all P < .01). However, the link between 1,5-AG and traditional glycemic markers was attenuated in individuals with mGFR < 30 mL/min/1.73 m2. Sensitivity analysis after excluding anemic patients showed similar results regarding the relationship between serum 1,5-AG and HbA1c across the mGFR subgroups.

CONCLUSION

Although we observed a weak inverse correlation (r = -0.189) between mGFR and serum 1,5-AG in type 2 diabetes, 1,5-AG remains a valid marker for assessing glucose control in subjects with mild or moderate renal dysfunction.

Advanced Glycation End-Products Acting as Immunomodulators for Chronic Inflammation, Inflammaging and Carcinogenesis in Patients with Diabetes and Immune-Related Diseases

Increased production of advanced glycation end products (AGEs) among reducing sugars (glucose, fructose, galactose, or ribose) and amino acids/proteins via non-enzymatic Maillard reaction can be found in lifestyle-related disease (LSRD), metabolic syndrome (MetS), and obesity and immune-related diseases. Increased serum levels of AGEs may induce aging, diabetic complications, cardiovascular diseases (CVD), neurodegenerative diseases (NDD), cancer, and inflamm-aging (inflammation with immunosenescence). The Maillard reaction can also occur among reducing sugars and lipoproteins or DNAs to alter their structure and induce immunogenicity/genotoxicity for carcinogenesis. AGEs, as danger-associated molecular pattern molecules (DAMPs), operate via binding to receptor for AGE (RAGE) or other scavenger receptors on cell surface to activate PI3K-Akt-, P38-MAPK-, ERK1/2-JNK-, and MyD88-induced NF-κB signaling pathways to mediate various pathological effects. Recently, the concept of "inflamm-aging" became more defined, and we have unveiled some interesting findings in relation to it. The purpose of the present review is to dissect the potential molecular basis of inflamm-aging in patients with diabetes and immune-mediated diseases caused by different AGEs.

Advances in electrochemical biosensors employing carbon-based electrodes for detection of biomarkers in diabetes mellitus

Background and purpose

The increase in diabetes cases has become a major concern in the healthcare sector, necessitating the development of efficient and minimal diagnostic methods. This study aims to provide a comprehensive examination of electrochemical biosensors for detecting diabetes mellitus biomarkers, with a special focus on the utilization of carbon-based electrodes.

Review approach

A detailed analysis of electrochemical biosensors incorporating various carbon electrodes, including screen-printed carbon electrodes, glassy carbon electrodes, and carbon paste electrodes, is presented. The advantages of carbon-based electrodes in biosensor design are highlighted. The review covers the detection of several key diabetes biomarkers, such as glucose, glycated hemoglobin (HbA1c), glycated human serum albumin (GHSA), insulin, and novel biomarkers.

Key results

Recent developments in electrochemical biosensor technology over the last decade are summarized, emphasizing their potential in clinical applications, particularly in point-of-care settings. The utilization of carbon-based electrodes in biosensors is shown to offer significant advantages, including enhanced sensitivity, selectivity, and cost-effectiveness.

Conclusion

This review underscores the importance of carbon-based electrodes in the design of electrochemical biosensors and raises awareness for the detection of novel biomarkers for more specific and personalized diabetes mellitus cases. The advancements in this field highlight the potential of these biosensors in future clinical applications, especially in point-of-care diagnostics.

The progress of clinical research on the detection of 1,5-anhydroglucitol in diabetes and its complications

1,5-Anhydroglucitol (1,5-AG) is sensitive to short-term glucose fluctuations and postprandial hyperglycemia, which has great potential in the clinical application of diabetes as a nontraditional blood glucose monitoring indicator. A large number of studies have found that 1,5-AG can be used to screen for diabetes, manage diabetes, and predict the perils of diabetes complications (diabetic nephropathy, diabetic cardiovascular disease, diabetic retinopathy, diabetic pregnancy complications, diabetic peripheral neuropathy, etc.). Additionally, 1,5-AG and β cells are also associated with each other. As a noninvasive blood glucose monitoring indicator, salivary 1,5-AG has much more benefit for clinical application; however, it cannot be ignored that its detection methods are not perfect. Thus, a considerable stack of research is still needed to establish an accurate and simple enzyme assay for the detection of salivary 1,5-AG. More clinical studies will also be required in the future to confirm the normal reference range of 1,5-AG and its role in diabetes complications to further enhance the blood glucose monitoring system for diabetes.

Visceral fat correlates with insulin secretion and sensitivity independent of BMI and subcutaneous fat in Chinese with type 2 diabetes

AIM

Clinical heterogeneity exists in overall obesity and abdominal obesity in terms of insulin secretion and sensitivity. Further, the impact of visceral fat (VF) on the first- and second-phase insulin secretion (FPIS and SPIS) is controversial. We aim to investigate insulin secretion and sensitivity in Chinese patients with T2DM according to different BMI and VF levels.

METHODS

This study enrolled 300 participants. A dual bioelectrical impedance analyzer was used to assess the visceral and subcutaneous fat area (VFA and SFA). VF levels were categorized as normal or high, with the cutoff value of 100 cm². FPIS and SPIS were evaluated by arginine stimulation test and standardized steamed bread meal tolerance test, respectively. β-cell function (HOMA2-β), insulin resistance (HOMA2-IR), and Gutt's insulin sensitivity index (Gutt-ISI) were also calculated. Spearman's correlation analysis and multivariate linear regression analysis were adopted for statistical analysis.

RESULTS

Participants were categorized into four groups: normal weight-normal VF, normal weight-high VF, overweight/obese-normal VF and overweight/obese-high VF. Multivariate linear regression showed that both VFA and SFA were correlated with FPIS, HOMA2-IR and Gutt-ISI after controlling for gender and diabetes duration. After further adjustment for BMI and VFA, some associations of SFA with insulin secretion and sensitivity disappeared. After adjustment for gender, diabetes duration, BMI and SFA, VFA was positively correlated with FPIS, SPIS and HOMA2-IR. Subjects with overweight/obese-high VF were more likely to have higher FPIS, HOMA2-IR and lower Gutt-ISI (all p < 0.05).

CONCLUSION

VF affects both FPIS and SPIS, and worsens insulin sensitivity independent of BMI and subcutaneous fat in Chinese patients with T2DM.

CLINICAL TRIAL REGISTRATION

http://www.chictr.org.cn, identifier ChiCTR2200062884.

Untargeted metabolomics reveals gender- and age- independent metabolic changes of type 1 diabetes in Chinese children

INTRODUCTION

Type 1 diabetes (T1D) is a chronic condition associated with multiple complications that substantially affect both the quality of life and the life-span of children. Untargeted Metabolomics has provided new insights into disease pathogenesis and risk assessment.

METHODS

In this study, we characterized the serum metabolic profiles of 76 children with T1D and 65 gender- and age- matched healthy controls using gas chromatography coupled with timeof-flight mass spectrometry. In parallel, we comprehensively evaluated the clinical phenome of T1D patients, including routine blood and urine tests, and concentrations of cytokines, hormones, proteins, and trace elements.

RESULTS

A total of 70 differential metabolites covering 11 metabolic pathways associated with T1D were identified, which were mainly carbohydrates, indoles, unsaturated fatty acids, amino acids, and organic acids. Subgroup analysis revealed that the metabolic changes were consistent among pediatric patients at different ages or gender but were closely associated with the duration of the disease.

DISCUSSION

Carbohydrate metabolism, unsaturated fatty acid biosynthesis, and gut microbial metabolism were identified as distinct metabolic features of pediatric T1D. These metabolic changes were also associated with T1D, which may provide important insights into the pathogenesis of the complications associated with diabetes.

Effect of Metabolite Levels on Type 2 Diabetes Mellitus and Glycemic Traits: A Mendelian Randomization Study

OBJECTIVE

To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits.

METHODS

Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P < 5 × 10-8) were selected from public genome-wide association studies, and single-nucleotide polymorphisms of outcomes were obtained from the Diabetes Genetics Replication and Meta-analysis consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related Traits Consortium for fasting glucose, insulin, and glycated hemoglobin (HbA1c). The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis.

RESULTS

The β estimates per 1-SD increase of arachidonic acid (AA) level was 0.16 (95% CI, 0.078-0.242; P < 0.001). Genetic predisposition to higher plasma AA levels were associated with higher fasting glucose levels (β 0.10 [95% CI, 0.064-0.134], P < 0.001), higher HbA1c levels (β 0.04 [95% CI, 0.027-0.061]), and lower fasting insulin levels (β -0.025 [95% CI, -0.047 to -0.002], P = 0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have a positive causal effect on glycemic traits.

CONCLUSIONS

Our findings suggest that AA and 2-HBA may have causal associations on T2DM and glycemic traits. This is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM.

Multilevel clustering approach driven by continuous glucose monitoring data for further classification of type 2 diabetes

INTRODUCTION

Mining knowledge from continuous glucose monitoring (CGM) data to classify highly heterogeneous patients with type 2 diabetes according to their characteristics remains unaddressed. A refined clustering method that retrieves hidden information from CGM data could provide a viable method to identify patients with different degrees of dysglycemia and clinical phenotypes.

RESEARCH DESIGN AND METHODS

From Shanghai Jiao Tong University Affiliated Sixth People's Hospital, we selected 908 patients with type 2 diabetes (18-83 years) who wore blinded CGM sensors (iPro2, Medtronic, California, USA). Participants were clustered based on CGM data during a 24-hour period by our method. The first level extracted the knowledge-based and statistics-based features to describe CGM signals from multiple perspectives. The Fisher score and variables cluster analysis were applied to fuse features into low dimensions at the second level. The third level divided subjects into subgroups with different clinical phenotypes. The four subgroups of patients were determined by clinical phenotypes.

RESULTS

Four subgroups of patients with type 2 diabetes with significantly different statistical features and clinical phenotypes were identified by our method. In particular, individuals in cluster 1 were characterized by the lowest glucose level factor and glucose fluctuation factor, and the highest negative glucose factor and C peptide index. By contrast, cluster 2 had the highest glucose level factor and the lowest C peptide index. Cluster 4 was characterized by the greatest degree of glucose fluctuation factor, was the most insulin-sensitive, and had the lowest insulin resistance. Cluster 3 ranked in the middle concerning the CGM-derived metrics and clinical phenotypes compared with those of the other three groups.

CONCLUSION

A novel multilevel clustering approach for knowledge mining from CGM data in type 2 diabetes is presented. The results demonstrate that subgroups are adequately distinguished with notable statistical and clinical differences.