Clinical impact of variability in HbA1c as assessed by simultaneously measuring fructosamine and use of error grid analysis

The Correlation Between Glycation Gap and Renal Complications in Patients with Type 2 Diabetes Mellitus

Purpose

The aim of this study was to investigate the correlations between the glycation gap (GG) and renal complications such as urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) in type 2 diabetes mellitus patients.

Materials and Methods

A cross-sectional study was conducted on 104 individuals (52 males and 52 females), aged 36-93 years old. Fasting blood glucose (FBG), HbA1c, and serum fructosamine were measured simultaneously. GG was calculated as the difference between the measured and fructosamine-based predicted HbA1c levels (FHbA1c).

Results

There was a moderately positive correlation between HbA1c and fructosamine concentration (r = 0.488; p < 0.001). GG was positively correlated with UACR (r = 0.3275; p = 0.0007), negatively correlated with eGFR (r = -0.3400; p = 0.0004). HbA1c was positively correlated with UACR (r = 0.2437; p = 0.0127) but not correlated with eGFR (r = -0.444; p = 0.6542). Fructosamine has a positive correlation with eGFR (r = 0.2426; p = 0.0131) but not with UACR (r = -0.1021; p = 0.3025).

Conclusion

GG was positively correlated with UACR and inversely correlated with eGFR in type 2 Diabetes mellitus patients. This suggests that GG is a valuable index for predicting kidney complications due to diabetes.

Serum fructosamine and glycemic status in the presence of the sickle cell mutation

AIMS

The glycated hemoglobin (HbA1c) test can be unreliable in the presence of hemoglobinopathies. The co-existence of type 2 diabetes (T2D) with sickle cell anemia calls for alternative tests. Therefore, we established a reference interval for serum fructosamine and evaluated its utility as a potential glycemic biomarker that is not affected by abnormal hemoglobin.

METHODS

The accuracies of serum fructosamine in monitoring and diagnosing T2D were evaluated using the Area under the Receiver Operating Characteristics and other measures in 618 Nigerians with or without sickle cell trait. The estimated diagnostic cut-off for serum fructosamine was then validated in an independent multi-ethnic cohort of 634 West Africans.

RESULTS

Serum fructosamine was similar between individuals with or without sickle cell trait (median: 287 vs 275 umol/L, p = 0·11, respectively) despite statistically different HbA1c. Fructosamine was highly correlated with both HbA1c and fasting glucose independently of sickle cell trait. The areas under the curve (AUC) of serum fructosamine in identifying individuals with uncontrolled glycemia and individuals with T2D were similar and independent of sickle cell trait: 0·92 (95% confidence interval [95% CI ], 0·88-0·95 and 0.92 (95% CI, (0.89-0.95) respectively.

CONCLUSIONS

Serum fructosamine is a good alternative to HbA1c for monitoring and diagnosing T2D in the presence of sickle cell trait.

Increased body fat mass reduces the association between fructosamine and glycated hemoglobin in obese type 2 diabetes patients

Obesity is increasing in patients with type 2 diabetes. A possible reduced association between fructosamine and glycated hemoglobin (HbA1c) in obese individuals has been previously discussed, but this has never been specifically evaluated in type 2 diabetes, and the potential influence of body fat mass and fat distribution has never been studied. We studied 112 type 2 diabetes patients with assessment of fat mass, liver fat and fat distribution. Patients with body mass index (BMI) above the median (34.9 kg/m² ), versus BMI below the median, had a correlation coefficient between fructosamine and HbA1c significantly reduced (r = 0.358 vs r = 0.765). In the whole population, fructosamine was correlated negatively with BMI and fat mass. In multivariate analysis, fructosamine was associated with HbA1c (positively) and fat mass (negatively), but not with BMI, liver fat or fat distribution. The association between fructosamine and HbA1c is significantly reduced in the most obese type 2 diabetes patients, and this is mostly driven by increased fat mass.

Role of fructosamine-3-kinase in protecting against the onset of microvascular and macrovascular complications in patients with T2DM

INTRODUCTION

Microangiopathic and macroangiopathic complications are the main cause of morbidity and mortality in the diabetic population. Numerous publications have highlighted the role of glycation in the onset of complications of diabetes. In this context, the detection of fructosamine-3-kinase (FN3K)-an enzyme capable of counteracting the effect of hyperglycemia by intervening in protein glycation-has attracted great interest. Several studies have linked FN3K genetic variability to its enzymatic activity and glycated hemoglobin (HbA1c) levels. Here, we investigated the role of FN3K polymorphisms in the development of microvascular and macrovascular complications of diabetes.

RESEARCH DESIGN AND METHODS

The anthropometric and biochemical parameters, and any medical history of microangiopathic and macroangiopathic complications, were documented in a sample of 80 subjects with type 2 diabetes. All subjects were screened for FN3K gene and analyzed for the combination of three polymorphisms known to be associated with its enzymatic activity (rs3859206 and rs2256339 in the promoter region and rs1056534 in exon 6).

RESULTS

The combination of allelic variants of FN3K polymorphisms resulted in 13 distinct genotypic variants within the cohort. Comparison between genotypes showed no significant differences in terms of demographic, anthropometric and biochemical parameters, risk markers and long-term complications, except for a higher age and vitamin E levels associated with the genotype presenting GG at position -385, TT at position -232, and CC at c.900 A. Evaluating the microangiopathic and macroangiopathic complications as a whole, we found that they appeared significantly less present in this genotype compared with all other genotypes (p=0.0306).

CONCLUSIONS

The group of patients carrying the favorable allele for the three polymorphisms of the FN3K gene revealed less severe microangiopathy and macroangiopathy, suggesting a protective role of this genotype against the onset of the complications of diabetes.

Potential Clinical Error Arising From Use of HbA1c in Diabetes: Effects of the Glycation Gap

The glycation gap (GGap) and the similar hemoglobin glycation index (HGI) define consistent differences between glycated hemoglobin and actual glycemia derived from fructosamine or mean blood glucose, respectively. Such a disparity may be found in a substantial proportion of people with diabetes, being >1 U of glycated HbA1c% or 7.2 mmol/mol in almost 40% of estimations. In this review we define these indices and explain how they can be calculated and that they are not spurious, being consistent in individuals over time. We evaluate the evidence that GGap and HGI are associated with variation in risk of complications and mortality and demonstrate the potential for clinical error in the unquestioning use of HbA1c. We explore the underlying etiology of the variation of HbA1c from mean glucose in blood plasma, including the potential role of enzymatic deglycation of hemoglobin by fructosamine-3-kinase. We conclude that measurement of GGap and HGI are important to diabetes clinicians and their patients in individualization of therapy and the avoidance of harm arising from consequent inappropriate assessment of glycemia and use of therapies.

Evaluation of agreement between hemoglobin A1c, fasting glucose, and fructosamine in Senegalese individuals with and without sickle-cell trait

Fasting glucose (FG) and glycated hemoglobin A1c (HbA1c) perform sub-optimally in people of African origin, especially in individuals with sickle-cell trait (SCT). The purpose of this study was to compare the relationships between HbA1c, FG, and fructosamine in individuals from Senegal with and without SCT. HbA1c, FG, and fructosamine were measured in 203 adults from Senegal (100 control: 45 with type 2 diabetes (T2D); 103 SCT: 51 with T2D). Significant, positive correlations were observed between HbA1c and FG, fructosamine and FG, and fructosamine and HbA1c in both groups. The limits of agreement were inappropriately large in both groups for the Bland-Altman plots of HbA1c and FG (control: -95.97 to 83.97%; SCT: -115.9 to 91.52%), fructosamine and FG (control: -100.6 to 99.89%; SCT: -105.6 to 100.6%), and fructosamine and HbA1c (control: -52.03 to 38.98%; SCT: -88.04 to 71.41%). In both groups, the greatest proportion of subjects were considered above the clinical cut-point for hyperglycemia when fructosamine was used as the criterion (control: 33%; SCT: 44.6%), and the lowest percentage of subjects were classified as over the clinical cut-point when HbA1c was used as the criterion (control: 21%; SCT: 27.7%).Substantial disparities between HbA1c, FG, and fructosamine were observed in both groups, and these differences were exaggerated in the SCT group. Therefore, these three biomarkers should not be considered to be interchangeable measures of glycemic control. These biomarkers should be used thoughtfully, and special care should be taken when using them in individuals with SCT.

Evidence That Differences in Fructosamine-3-Kinase Activity May Be Associated With the Glycation Gap in Human Diabetes

The phenomenon of a discrepancy between glycated hemoglobin levels and other indicators of average glycemia may be due to many factors but can be measured as the glycation gap (GGap). This GGap is associated with differences in complications in patients with diabetes and may possibly be explained by dissimilarities in deglycation in turn leading to altered production of advanced glycation end products (AGEs). We hypothesized that variations in the level of the deglycating enzyme fructosamine-3-kinase (FN3K) might be associated with the GGap. We measured erythrocyte FN3K concentrations and enzyme activity in a population dichotomized for a large positive or negative GGap. FN3K protein was higher and we found a striking threefold greater activity (323%) at any given FN3K protein level in the erythrocytes of the negative-GGap group compared with the positive-GGap group. This was associated with lower AGE levels in the negative-GGap group (79%), lower proinflammatory adipokines (leptin-to-adiponectin ratio) (73%), and much lower prothrombotic PAI-1 levels (19%). We conclude that FN3K may play a key role in the GGap and thus diabetes complications such that FN3K may be a potential predictor of the risk of diabetes complications. Pharmacological modifications of its activity may provide a novel approach to their prevention.

Importance of Glycemic Control in Cancer Patients with Diabetes: Treatment through End of Life

Cancer patients with diabetes are at increased risk for developing infections, being hospitalized, and requiring chemotherapy reductions or stoppages. While it has been hypothesized that glycemic control increases the risk for these adverse events, few studies have explored this hypothesis. The purpose of this paper is to discuss the importance of glycemic control in patients with diabetes and cancer during treatment through end of life. Glycemic control was found to play a role; the overall level of health-related quality of life experienced by patients with cancer and diabetes, level of symptom severity experienced and can impact the overall survival of the individual. Evidence-based policies and practice guidelines also need to be developed to help clinicians manage these patients during all phases of care. Using diabetes educators and advance practice, nurses to provide management and care coordination services need to be considered. Survivorship care plans should address both cancer and diabetes management. Finally, glycemic control should continue through end of life, with the main goal of avoiding hypoglycemic events.

Serum fructosamine a better indicator than glycated hemoglobin for monitoring gestational diabetes mellitus

Gestational Diabetes mellitus is the condition of glucose intolerance that begins during pregnancy which is associated with both fetal and maternal complications. The measurement of serum fructosamine and glycated hemoglobin in normal and diabetic pregnancy used to investigate the influence of maternal and gestational age on concentrations of glycated proteins in serum and used to evaluate the patient's treatment. This study was done to measure the level of serum fructosamine and Glycated hemoglobin (HbA1c) in Gestational Diabetes mellitus (GDM) patients and to compare with pregnant women without diabetes and healthy non-pregnant adults, to determine the pattern of change in serum fructosamine, influence of serum fructosamine and HbA1c values and to evaluate the efficacy of patient's treatment. In this study the level of fructosamine was positively correlated to HbA1c during 2^nd trimesters of gestational period, implying that the level of fructosamine can be used to screen Gestational diabetes mellitus. Correlation of glycated hemoglobin values with serum fructosamine measurements in the accurate determination of glycaemic control provides confirmation of the utility of fructosamine measurement.

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

The glycation gap (G-gap: difference between measured hemoglobin A1c [A1C] and the value predicted by its regression on the fructosamine level) is stable and associated with diabetic complications. Measuring A1C level in International Federation of Clinical Chemistry (IFCC) units (A1C-SI; mmol/mol) and National Glycohemoglobin Standardization Program units (A1C-NGSP; %) and using glycated albumin (GA) level instead of fructosamine level for calculating the G-gap, we investigated whether the G-gap is better represented by GA/A1C ratio if expressed in SI units (GA/A1C-SI ratio) rather than in NGSP units (GA/A1C-% ratio). We examined 749 Japanese children with type 1 diabetes using simultaneous GA and A1C measurements. Of these, 369 patients were examined more than five times to assess the consistency of the G-gap and the GA/A1C ratio within individuals. The relationship of GA/A1C-% ratio to the corresponding A1C-NGSP was stronger than that of GA/A1C-SI ratio to A1C-IFCC. At enrollment, the inverse relationship between the GA/A1C-SI ratio and G-gap was highly significant (R(2) = 0.95) compared with that between the GA/A1C-% ratio and G-gap (R(2) = 0.69). A highly significant inverse relationship was also observed between the mean GA/A1C-SI ratio and the mean G-gaps obtained individually over time (R(2) = 0.95) compared with that using the corresponding A1C-NGSP (R(2) = 0.67). We conclude that the G-gap is better represented by the GA/A1C-SI ratio. We propose the use of mean GA/A1C-SI ratios easily obtained individually over time as reference values in Japanese children with type 1 diabetes (6.75 ± 0.60 [means ± SD]).

Association of glycation gap with mortality and vascular complications in diabetes

OBJECTIVE

The "glycation gap" (G-gap), an essentially unproven concept, is an empiric measure of disagreement between HbA1c and fructosamine, the two indirect estimates of glycemic control. Its association with demographic features and key clinical outcomes in individuals with diabetes is uncertain.

RESEARCH DESIGN AND METHODS

The G-gap was calculated as the difference between measured HbA1c and a fructosamine-derived standardized predicted HbA1c in 3,182 individuals with diabetes. The G-gap's associations with demographics and clinical outcomes (retinopathy, nephropathy, macrovascular disease, and mortality) were determined.

RESULTS

Demographics varied significantly with G-gap for age, sex, ethnic status, smoking status, type and duration of diabetes, insulin use, and obesity. A positive G-gap was associated with retinopathy (odds ratio 1.24 [95% CI 1.01-1.52], P=0.039), nephropathy (1.55 [1.23-1.95], P<0.001), and, in a subset, macrovascular disease (1.91 [1.18-3.09], P=0.008). In Cox regression analysis, the G-gap had a "U"-shaped quadratic relationship with mortality, with both negative G-gap (1.96 [1.50-2.55], P<0.001) and positive G-gap (2.02 [1.57-2.60], P<0.001) being associated with a significantly higher mortality.

CONCLUSIONS

We confirm published associations of G-gap with retinopathy and nephropathy. We newly demonstrate a relationship with macrovascular and mortality outcomes and potential links to distinct subpopulations of diabetes.

Evaluation of glycemic variability in well-controlled type 2 diabetes mellitus

AIMS

It is necessary to evaluate glucose variability and postprandial hyperglycemia in patients with well-controlled type 2 diabetes mellitus because of the limitations associated with hemoglobin A1c (HbA1c) measurements. We evaluated parameters reflecting postprandial hyperglycemia and glycemic variability in patients with optimal HbA1c.

PATIENTS AND METHODS

Thirty-nine patients with HbA1c levels below 7% were recruited to the study. A continuous glucose monitoring system (CGMS) was applied for two 72-h periods. 1,5-Anhydroglucitol (1,5-AG) and fructosamine (FA) were measured as parameters for postprandial hyperglycemia and glucose variability. Using CGMS data, the following postprandial hyperglycemia parameters were calculated: mean postprandial maximum glucose (MPMG) and area under the curve for glucose above 180 mg/dL (AUC-180). To measure glycemic variability, we calculated mean amplitude of glucose excursion (MAGE) using a classical (MAGEc) and new method (MAGE group of sign [MAGEgos]).

RESULTS

The baseline HbA1c level was 6.3±0.3%. The mean MPMG was 10.34±1.84 mmol/L, and the mean AUC-180 was 0.17±0.23 mmol/L/day. The mean MAGEgos was 3.27±1.29 mmol/L, and MAGEc was 4.30±1.43 mmol/L, indicating glycemic variability in our patients. The mean levels of 1,5-AG and FA were 16.7±7.4 μg/mL and 273.0±22.5 μmol/L, respectively. In a correlation analysis, FA was significantly correlated with MPMG, AUC-180, MAGEgos, and MAGEc. In contrast, 1,5-AG was only correlated with AUC-180.

CONCLUSIONS

This study demonstrated postprandial hyperglycemia and glycemic variability in subjects with well-controlled diabetes. FA may reflect postprandial hyperglycemia and glycemic variability, but 1,5-AG may be of limited value for assessing glucose variability in patients with well-controlled type 2 diabetes mellitus.

Evidence for consistency of the glycation gap in diabetes

OBJECTIVE

Discordance between HbA(1c) and fructosamine estimations in the assessment of glycemia is often encountered. A number of mechanisms might explain such discordance, but whether it is consistent is uncertain. This study aims to coanalyze paired glycosylated hemoglobin (HbA(1c))-fructosamine estimations by using fructosamine to determine a predicted HbA(1c), to calculate a glycation gap (G-gap) and to determine whether the G-gap is consistent over time.

RESEARCH DESIGN AND METHODS

We included 2,263 individuals with diabetes who had at least two paired HbA(1c)-fructosamine estimations that were separated by 10 ± 8 months. Of these, 1,217 individuals had a third pair. The G-gap was calculated as G-gap = HbA(1c) minus the standardized fructosamine-derived HbA(1c) equivalent (FHbA(1c)). The hypothesis that the G-gap would remain consistent in individuals over time was tested.

RESULTS

The G-gaps were similar in the first, second, and third paired samples (0.0 ± 1.2, 0.0 ± 1.3, and 0.0 ± 1.3, respectively). Despite significant changes in the HbA(1c) and fructosamine, the G-gap did not differ in absolute or relative terms and showed no significant within-subject variability. The direction of the G-gap remained consistent.

CONCLUSIONS

The G-gap appears consistent over time; thus, by inference any key underlying mechanisms are likely to be consistent. G-gap calculation may be a method of exploring and evaluating any such underlying mechanisms.

A case of discordant HbA(1c): a method-dependent error

Although glycated haemoglobin (HbA(1c)) has become the key biochemical marker of long-term glycaemic control, analytical method-dependent differences in results can occur when haemoglobin variants are present or HbA(1c) is reduced by decreased red cell survival. When the measured HbA(1c) level is discordant with the patient's blood glucose measurements and clinical status, fructosamine is an alternative biochemical marker that can provide a more accurate estimate of the glycaemic control and enable clinicians to appropriately manage patients.