Glycated albumin in diabetes mellitus: a meta-analysis of diagnostic test accuracy

Adjusted glycated albumin is a novel indicator of glycemic control in patients with macroalbuminuria in diabetic kidney disease

Glycated albumin (GA), a blood glucose monitoring biomarker, is impacted by variables such as albumin turnover and is not entirely relevant throughout diabetic kidney disease (DKD). There is insufficient data to routinely adjust GA measurements. We examined how albuminuria affected clinically measured GA (mGA) and adjusted GA (adjGA). We included 195 patients with DKD, 108 with non-macroalbuminuria and 87 with macroalbuminuria, and adjusted GA based on albumin, albuminuria, and body weight. Subgroups were divided to two groups according to albuminuria and serum albumin levels. The relationship between mGA, adjGA, and glucose was investigated. The optimum GA correction method based on albumin turnover metabolism was investigated: adjGA = mGA×[1+(8×K×UP) ÷ (11×V×SA)]. where K represents the standard metabolic days of albumin (15 days), UP is 24-hour urine protein excretion (g/24 h), V is plasma volume (calculated as 5% of body weight in liters), and SA is serum albumin concentration (g/L). In non-macroalbuminuria, mGA was 19.75% and adjGA was 22.32%, and in macroalbuminuria, mGA was 13.20% and adjGA was 22.45%, the mGA was substantially different across albuminuria categories (P < 0.001), but adjGA was not. HbA1c, 24-h urine protein(24hUP) and serum albumin (ALB) were influencing variables for mGA (P < 0.001), while 24hUP and ALB had no effect on adjGA (P > 0.05). The adjGA had stronger cor-relation with blood glucose than mGA, especially in the context of macroalbuminuria. Macroalbuminuria lowers mGA accuracy. In DKD patients with macroalbuminuria, adjusted GA is a novel indication of glucose monitoring.

Limitations of glycated albumin standardization when applied to the assessment of diabetes patients

OBJECTIVES

Glycated albumin (GA) has potential value in the management of people with diabetes; however, to draw meaningful conclusions between clinical studies it is important that the GA values are comparable. This study investigates the standardization of the Norudia Glycated Albumin and Lucica Glycated Albumin-L methods.

METHODS

The manufacturer reported imprecision was verified by performing CLSI-EP15-A3 protocol using manufacturer produced controls. The Japanese Clinical Chemistry Reference Material (JCCRM)611-1 was measured 20 times to evaluate the accuracy of both methods. GA was also measured in 1,167 patient samples and results were compared between the methods in mmol/mol and %.

RESULTS

Maximum CV for Lucica was ≤0.6 % and for Norudia ≤1.8 % for control material. Results in mmol/mol and % of the JCCRM611-1 were within the uncertainty of the assigned values for both methods. In patient samples the relative difference in mmol/mol between the two methods ranged from -10.4 % at a GA value of 183 mmol/mol to +8.7 % at a GA value of 538 mmol/mol. However, the relative difference expressed in percentage units ranged from of 0 % at a GA value of 9.9 % to +1.7 % at a GA value of 30 %.

CONCLUSIONS

The results in mmol/mol between the two methods for the patient samples were significantly different compared to the results in %. It is not clear why patient samples behave differently compared to JCCRM611-1 material. Valuable lessons can be learnt from comparing the standardization process of GA with that of HbA1c.

Reference Interval for Glycated Albumin, 1,5-AG/GA, and GA/HbA1c Ratios and Cut-Off Values for Type 1, Type 2, and Gestational Diabetes: A Cross-Sectional Study

Background/Objectives: Glycated albumin (GA) serves as a biomarker for short-term glycemic control (2-3 weeks), playing a role in diabetes management. Our goal was to establish reference intervals (RIs) for serum GA, and the ratios of 1,5-anhydroglucitol to GA (AGI) and GA to HbA1c in a Euro-Brazilian pediatric population (10 y, n = 299), adults (43.5 y; n = 290), and pregnant women (26 y, n = 406; 26.5 ± 3.1 gestation weeks). Methods: Receiver operating characteristic curve analysis was employed to determine RIs for type 1 diabetes (T1D) in children (n = 148) and adults (n = 81), type 2 diabetes (T2D, n = 283), and gestational diabetes mellitus (GDM, n = 177). Results: Both non-pregnant and pregnant women exhibited GA RIs of 10.0-13.3% and 10.6-14.7%, respectively. The AGI ratio varied from 1.2-4.3 in children, 0.9-3.6 in adults, and 0.8-3.1 in pregnant women. Meanwhile, the GA/HbA1c ratio ranged from 1.8-2.6 in children and adults to 2.3-3.6 in pregnant women. GA and AGI ratios accurately differentiated between T1D and T2D, demonstrating high sensitivity (>84%) and specificity (>97%), with AGI showing superior performance (AUC > 0.99). The GA/HbA1c ratio exhibited moderate discriminatory power (AUC > 0.733) but was less effective in distinguishing adult-onset T1D and T2D, suggesting its limited utility in certain groups. Conclusions: The proposed RIs are consistent with those of other Caucasian populations, affirming their relevance for Euro-Brazilian patients. The GA and AGI ratios emerge as valuable diagnostic tools for T1D and T2D, though their reduced sensitivity in diagnosing GDM warrants further investigation. Clinicians might leverage GA and AGI ratios for more tailored diabetes management, especially when HbA1c results are not optimal.

Prevalence of poor glycemic control and the monitoring utility of glycated albumin among diabetic patients attending clinic in tertiary hospitals in Dodoma, Tanzania: A cross-sectional study protocol

The burden of diabetes is rising in developing countries, and this is significantly linked to the increasing prevalence of poor glycemic control. The cost of glycated haemoglobin (HbA1c) testing is a barrier to timely glycemic assessments, but newer tests such as glycated albumin may be cheaper and tempting alternatives. Additional research must ascertain if glycated albumin (GA) can act as a viable supplement or alternative to conventional HbA1c measurements for glycemic control in diabetic individuals. GA as a biomarker is an emerging area of interest, particularly for those who display unreliable HbA1c levels or cannot afford the test. This study aims to investigate the prevalence of poor glycemic control in outpatient diabetic patients and the utility of glycated albumin in this population's monitoring of glycemic control. Method. A cross-sectional study of 203 diabetic patients will be conducted at the Dodoma Regional Referral Hospital and Benjamin Mkapa Hospital from August 1st, 2023, to August 31st, 2024. Patients diagnosed with diabetes mellitus for over six months will be screened for eligibility. Informed consent, history, clinical examination, and voluntary blood sample collection will be obtained from all eligible patients. Glycated Albumin levels will be obtained from the same blood samples collected. The glycemic status of all patients will be defined as per HbA1c, and a level of greater than 7% will considered as a poor control. The analysis will be computed with SPSS version 28.0, and a predictor variable, P<0.05, will be regarded as statistically significant, with the utility of GA determined by plotting the area under the ROC curve and the confusion matrix.

Glycated albumin in the detection of diabetes during COVID-19 hospitalization

BACKGROUND

Diabetes has emerged as an important risk factor for COVID-19 adverse outcomes during hospitalization. We investigated whether the measurement of glycated albumin (GA) may be useful in detecting newly diagnosed diabetes during COVID-19 hospitalization.

METHODS

In this cross-sectional test accuracy study we evaluated HCPA Biobank data and samples from consecutive in-patients, from 30 March 2020 to 20 December 2020. ROC curves were used to analyse the performance of GA to detect newly diagnosed diabetes (patients without a previous diagnosis of diabetes and admission HbA1c ≥6.5%).

RESULTS

A total of 184 adults (age 58.6 ± 16.6years) were enrolled, including 31 with newly diagnosed diabetes. GA presented AUCs of 0.739 (95% CI 0.642-0.948) to detect newly diagnosed diabetes. The GA cut-offs of 19.0% was adequate to identify newly diagnosed diabetes with high specificity (85.0%) but low sensitivity (48.4%).

CONCLUSIONS

GA showed good performance to identify newly diagnosed diabetes and may be useful for identifying adults with the condition in COVID-19-related hospitalization.

Interrelationship of hemoglobin A1c level lipid profile, uric acid, C-reactive protein levels and age in a large hospital database

INTRODUCTION

Hemoglobin A1c (HbA1c) is used to monitor glucose homeostasis and to identify risk for diabetes. As diabetic patients are frequently present with dyslipidaemia, low-grade inflammation and hyperuricemia, we tested whether HbA1c levels can be estimated having the information about lipid profile, uric acid (UA) and C-reactive protein (CRP) levels. We developed formulas to describe the association of these parameters with HbA1c levels.

METHODS

Data of 9599 male and 10,817 female patients, measured between 2008 and 2018, were analysed. Patients represented a general hospital patient population with overrepresentation of those with elevated HbA1c over 5.6%. The impact of gender, age, CRP, lipid profile and UA levels on HbA1c % on HbA1c levels was tested with multiple linear regression model. The magnitude of effects of individual factors was used to develop formulas to describe the association between HbA1c and other cardiometabolic parameters. With these formulas we estimated median HbA1c values in each age in both gender and compared them to measured HbA1c levels.

RESULTS

The developed formulas are as follow: HbA1c (estimated) in women = 0.752 + 0.237*log10(HDL/cholesterol) + 0.156*log10 (cholesterol) + 0.077*log10 (triglyceride) + 0.025*log10(CRP) +0.001*log10 (age) -0.026*log10(HDL/LDL) -0.063*log10 (uric acid)-0.075*log10 (LDL)-0.199*log10(HDL); HbA1c (estimated) in men = 1.146 + 0.08*log10 (triglyceride) + 0.046*log10(CRP) + 0.01*log10 (cholesterol) + 0.001*log10 (age) -0.014*log10(HDL)-0.018*log10(HDL/LDL)-0.025*log10(HDL/cholesterol) -0.068*log10 (LDL)-0.159*log10 (uric acid) Between 20 and 70 years of age, estimated HbA1c matched perfectly to measured HbA1c in.

CONCLUSION

At population level, HbA1c levels can be estimated almost exactly based on lipid profile, CRP and uric acid levels in female patients between 20 and 70 years.

Early detection of type 2 diabetes risk: limitations of current diagnostic criteria

Type 2 diabetes (T2D) is the leading cause of diabetes worldwide and is increasing rapidly, especially in youth. It accounts for most diabetes deaths in adults ≥20 years old in the Americas, with type 2 diabetes responsible for most of the disease burden. The incidence and burden of type 2 diabetes in adolescents and young adults have risen in recent decades globally. Countries with lower socioeconomic status had the highest incidence and burden, and females generally had higher mortality and disease burden than males at ages <30 years. Early diagnosis and management are crucial to delaying progression, but current diagnostic criteria based on glucose thresholds and glycated hemoglobin have limitations. Recent analyses show that prediabetes increases cancer risk. Better diagnostic criteria are urgently needed to identify high-risk individuals earlier. This article discusses the limitations of current criteria and explores alternative approaches and future research directions.

Discovery of age-related early-stage glycated proteins based on deep quantitative serum glycated proteome analysis

Aging is a pressing global health issue that is linked to various diseases, such as diabetes and Alzheimer's disease. It is well known that glycation plays a pathological role in the aging process and age-related diseases. Thus, it is of great significance to discover protein glycation at an early stage for monitoring and intervention in the aging process. However, the endogenous age-related early-stage glycated proteome remains insufficiently profiled. To address this research gap, our study focuses on assessing glycated proteomics profiles in the serum of mice. We employ a robust and quantitative strategy previously developed by our team, to analyze endogenous glycated proteome in serum samples of 4 age groups of mice (10 weeks, 16 weeks, 48 weeks and 80 weeks). In total, 2959 endogenous glycated peptides corresponding to 296 serum proteins are identified from 48 runs of serum samples from 16 mice across the four age groups. By comparing these glycated peptides between adjacent age groups, we discover 49 glycated peptides from 35 proteins that show significant upregulation between the 48-week and 80-week age groups. Furthermore, we identify 10 glycated proteins (or protein groups) that are significantly upregulated only between the 48-week and 80-week age groups, including lecithin-cholesterol acyltransferase (LCAT) and apolipoprotein A-II (Apo A-II). These novel findings provide unique signatures for understanding the aging process and age-related diseases. By shedding light on the early-stage glycated proteome, our study contributes valuable insights that may have implications for future interventions and therapeutic approaches.

Evaluation of salivary glycated albumin in periodontitis patients with and without type 2 diabetes mellitus and its changes with non-surgical periodontal therapy

Background

Bidirectional relationship exists between diabetes mellitus and periodontitis. Glycated albumin is an emerging biomarker to assess intermediate glycemic control. Salivary glycated albumin has not been evaluated in periodontitis.

Aim

The aim of the study was to compare salivary glycated albumin in periodontitis patients with and without diabetes mellitus before and after periodontal therapy.

Materials and Methods

This comparative cross-sectional study was conducted in the Department of Periodontics. Ninety subjects (mean age 41.8 ± 6.82) were categorized into three groups. Clinical examination and saliva sample collection were done at baseline and 4 weeks after scaling and root debridement. Salivary glycated albumin levels were estimated using an enzyme-linked immunosorbent assay. One-way analysis of variance with post hoc test and paired t-test was done for inter- and intra-group comparison. The optimal cut-off value was calculated using the receiver operating characteristic curve and by maximization of the Youden index.

Results

Mean salivary glycated albumin was the highest in diabetic patients followed by non-diabetic periodontitis patients and least in healthy controls. All the intergroup comparisons were significant. A cut-off value of 72.19 ng/ml of salivary glycated albumin could predict diabetic status with a sensitivity and specificity of 75%. Salivary glycated albumin was significantly reduced in a similar manner in both groups after periodontal therapy (19.4% and 18.5%).

Conclusion

Periodontitis patients with diabetes mellitus were presented with the highest salivary glycated albumin. Non-surgical periodontal therapy resulted in a similar reduction of salivary glycated albumin in periodontitis with and without diabetes mellitus.