Hemoglobin glycation index predicts renal function deterioration in patients with type 2 diabetes and a low risk of chronic kidney disease

Hemoglobin Glycation Index: A Novel Risk Factor for Incident Chronic Kidney Disease in an Apparently Healthy Population

CONTEXT

Chronic kidney disease (CKD) is a worldwide health problem. Recent literature has shown an association of hemoglobin glycation index (HGI) and CKD in patients with dysglycemia.

OBJECTIVE

The aim of this study was to reveal the impact of HGI as a predictor for incident CKD in the general population.

METHODS

CKD was defined as dipstick proteinuria or estimated glomerular rate (eGFR) < 60 mL/min/1.73 m2. Impact of HGI on incident CKD was assessed using the data from CKD-free health examinees (N = 23 467, 4.1% with diabetes) followed for a mean of 5.1 years: Cox proportional hazards model was employed with multivariate adjustment for age, systolic blood pressure, eGFR, fasting plasma glucose, body mass index, log[alanine aminotransferase], log[triglycerides], high-density lipoprotein cholesterol, platelet counts, smoking, and sex. Elevated level of HGI in subjects with CKD was ascertained after propensity score matching of another group of health examinees (N = 2580, 7.6% with diabetes).

RESULTS

In the former group, CKD developed in 2540 subjects and HGI was the second most robust predictor for CKD, following low eGFR. With adjustment for the 11 covariates, the hazard ratio of HGI (95% CI) for CKD was 1.293 (1.238 to 1.349) (P < .0001). The population attributable risk of HGI for CKD was 4.2%. In the latter group, among 708 subjects matched 1:1 for 9 covariates, HGI was significantly elevated in subjects with CKD (median [interquartile range] -0.208 [-0.504 to -0.156] vs -0.284 [-0.582 to 0.052], P = .03).

CONCLUSION

HGI was a novel risk factor for CKD in the general population.

Communal interaction of glycation and gut microbes in diabetes mellitus, Alzheimer's disease, and Parkinson's disease pathogenesis

Diabetes and its complications, Alzheimer's disease (AD), and Parkinson's disease (PD) are increasing gradually, reflecting a global threat vis-à-vis expressing the essentiality of a substantial paradigm shift in research and remedial actions. Protein glycation is influenced by several factors, like time, temperature, pH, metal ions, and the half-life of the protein. Surprisingly, most proteins associated with metabolic and neurodegenerative disorders are generally long-lived and hence susceptible to glycation. Remarkably, proteins linked with diabetes, AD, and PD share this characteristic. This modulates protein's structure, aggregation tendency, and toxicity, highlighting renovated attention. Gut microbes and microbial metabolites marked their importance in human health and diseases. Though many scientific shreds of evidence are proposed for possible change and dysbiosis in gut flora in these diseases, very little is known about the mechanisms. Screening and unfolding their functionality in metabolic and neurodegenerative disorders is essential in hunting the gut treasure. Therefore, it is imperative to evaluate the role of glycation as a common link in diabetes and neurodegenerative diseases, which helps to clarify if modulation of nonenzymatic glycation may act as a beneficial therapeutic strategy and gut microbes/metabolites may answer some of the crucial questions. This review briefly emphasizes the common functional attributes of glycation and gut microbes, the possible linkages, and discusses current treatment options and therapeutic challenges.

The Association Between Hemoglobin Glycation Index and Carotid Artery Plaque in Patients With Coronary Heart Disease

This study aimed to examine the association between the hemoglobin glycation index (HGI) and carotid artery plaque (CAP) in patients with coronary heart disease (CHD). We conducted a cross-sectional analysis of 10,778 patients with CHD. The participants were divided into three groups by HGI tertiles (T1 HGI<-0.44, T2 -0.44 ≤ HGI ≤ 0.15, T3 HGI>0.15). The presence of CAP was used to diagnose by carotid ultrasonography. Logistic regression analysis was used to analyze the association between the HGI and CAP. The association between HGI and CAP was also assessed according to sex, age, smoking status, and drinking status. We further assessed the association between HGI and the ultrasound characteristics of CAP. The baseline analysis showed substantial differences in relevant parameters between the three groups of patients with CHD according to the tertiles of the HGI. Multivariate logistic regression analysis showed that HGI was significantly associated with CAP (odds ratio [OR] 1.32; 95% confidence interval [CI] 1.26-1.39). The association between HGI and CAP exists among different sex, age, smoking, and drinking status. Furthermore, there was a significant and positive association between HGI and all four different echogenicities of the CAP.

Modified Graphite Pencil Electrode Based on Graphene Oxide-Modified Fe3O4 for Ferrocene-Mediated Electrochemical Detection of Hemoglobin

This study describes the synthesis of graphene oxide-modified magnetite (rGO/Fe₃O₄) and its use as an electrochemical sensor for the quantitative detection of hemoglobin (Hb). rGO is characterized by a 2θ peak at 10.03° in its X-ray diffraction, 1353 and 1586 cm^-1 vibrations in Raman spectroscopy, while scanning electron microscopy coupled with energy-dispersive spectroscopy of rGO and rGO/Fe₃O₄ revealed the presence of microplate structures in both materials and high presence of iron in rGO/Fe₃O₄ with 50 wt %. The modified graphite pencil electrode, GPE/rGO/Fe₃O₄, is characterized using cyclic voltammetry. Higher electrochemical surface area is obtained when the GPE is modified with rGO/Fe₃O₄. Linear scan voltammetry is used to quantify Hb at the surface of the sensor using ferrocene (FC) as an electrochemical amplifier. Linear response for Hb is obtained in the 0.1-1.8 μM range with a regression coefficient of 0.995, a lower limit of detection of 0.090 μM, and a limit of quantitation of 0.28 μM. The sensor was free from interferents and successfully used to sense Hb in human urine. Due to the above-stated qualities, the GPE/rGO/Fe₃O₄ electrode could be a potential competitive sensor for trace quantities of Hb in physiological media.

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.