Discordances between glycated hemoglobin (HbA1c) levels and other markers of glycemic control are common in clinical practice [1]. Mismatches of actual HbA1c levels (i.e., higher or lower) with the expected mean blood glucose (MBG)-based HbA1c levels can limit the accuracy of HbA1c measurements for diabetes diagnosis and management [1]. Regardless of the presence of type 2 diabetes mellitus (T2DM), HbA1c has been reported to have interindividual variations that are caused by factors other than MBG levels, including genetic factors and differences in erythrocyte lifespan, mean erythrocyte age, and hemoglobin glycation rates [2]. Most previous studies have calculated the hemoglobin glycation index (HGI) as the difference between the measured HbA1c level and that predicted using fasting blood glucose (FBG) levels [3-7]. Concerns have been raised that a high HGI may reflect hyperglycemia at times that cannot be captured by the FBG or self-monitored blood glucose [8]. Although FBG estimations correlate well with MBG levels, these can widely vary, and methodologies that use 6- or 8-point glucose profiles provide better representations of MBG levels. The availability of continuous glucose monitoring (CGM) with large data and better reflection of postprandial peaks could help in the calculation of MBG levels, but the potential of CGM for HGI calculation has not been explored [1].

Cohen et al. [9] suggested that the glycation gap could explain interindividual variations in HbA1c levels. The glycation gap is defined as the difference between actual HbA1c levels and those predicted based on the fructosamine concentration [10]. Moreover, we reported that the glycation gap determined using glycated albumin (GA) was consistent and reliable [11]. The time frame of glycemic control represented by fructosamine or GA is shorter than that represented by HbA1c. The 6- to 12-week time frame required for HbA1c to equilibrate is an important consideration when comparing it with the shorter-term measure of GA. Some researchers have argued that the glycation gap occurs due to differences in the time frame of glycemic control assessed between GA-based measures and HbA1c [12]. Therefore, unlike previous studies, which were mainly conducted at 3- to 4-month intervals, this study simultaneously measured GA and HbA1c on the same day and repeated the tests at baseline and 1 month later. We aimed to investigate the short-term consistency of the glycation gap.

The present study showed that the HGI and glycation gap were highly reproducible and the magnitudes of the repeated determinations were closely correlated. In previous studies, the HGI was calculated as the difference between measured and FBG-based predicted HbA1c levels [3-7]. Other investigators have hypothesized that biological variation in HGI might be an analytical artifact caused by person-to-person variation in postprandial glucose excursions that are not detected when FBG is used to calculate the HGI [8]. We performed 72-hour CGM at baseline and after 1 month and found that the sign and magnitude of the first and second MBG-based HGI measurements were closely correlated. Moreover, the FBG-based and MBG-based HGI measurements were positively correlated. Even in patients with similar MBG levels, there may be a significant difference in HbA1c levels. These observations suggest that variation in postprandial glucose levels is not a significant source of population variation in HGI. This is the first study to calculate the HGI using MBG levels derived from CGM.

Glucose-independent interpersonal variations in HbA1c levels relative to glucose levels have long been recognized. Among the participants in the Diabetes Control and Complication Trial, HbA1c showed substantial differences relative to the glucose levels that were measured by self-monitoring of blood glucose [13]. False-positive and -negative diagnoses based on HbA1c screening relative to the oral glucose tolerance test may be attributable to the contributions of high and low HGI values, respectively [14]. Discordances between HbA1c and glucose levels have clinical implications for T2DM management. When HbA1c levels are spuriously high relative to glucose levels, individuals will be at increased risk for hypoglycemia, because a high HbA1c can prompt treatment intensification. However, individuals with a low HbA1c relative to glucose levels may have a delayed diagnosis of T2DM and may not receive intense enough treatment to adequately reduce their risks for T2DM complications. In most individuals, the diagnosis and management of T2DM should be based on measurements of glucose levels, in addition to HbA1c [1].

If an individual has a measured HbA1c that is higher than expected from MBG levels (i.e., a high HGI), higher measured HbA1c levels than would be expected from MBG levels is likely to continue during repeated comparisons over time. Such individuals likely have a relatively long red blood cell (RBC) life span (i.e., a slow RBC turnover rate), a relatively high RBC glycation rate, or a variation in another yet undefined biological or genetic factor [15,16]. Genetic variations could influence HbA1c levels through nonglycemic pathways and contribute to HbA1c/glycemia discordance. A previous study confirmed that the glycation gap may be partly genetically determined, accounting for one-third of the heritability of HbA1c levels [9]. Another study reported racial differences in the relationship between HbA1c levels and glycemia, confirming that HbA1c levels overestimated in black people relative to white people [17]. Factors that affect RBC survival or those that regulate intracellular glucose concentrations, such as glucose permeability across the RBC membrane, have been shown to contribute to the extent of hemoglobin glycation [2,18].

Most previous studies calculated the HGI as the difference between the measured value of HbA1c and the HbA1c level predicted on the basis of FBG values [3-7]. Concerns have been raised that a high HGI could be attributed to hyperglycemia at times that cannot be captured by FBG levels. In our study, the HGI calculated using MBG levels was found to be consistent in individuals over time, indicating a constant variation in intracellular glycation compared with extracellular glycation or glycemia as measured by MBG levels. A potential mechanism for variation in glycation may be a fructosamine-3-kinase (FN3K)-related glycation/deglycation shift through the deglycation of intracellular proteins, such as hemoglobin. FN3K is highly expressed in erythrocytes with a documented role in HbA1c variation independent of glucose levels [16]. It was reported that FN3K enzyme activity and protein levels were both significantly higher in patients with a negative glycation gap (lower HbA1c levels than would be expected from average glycemia) [16]. The HGI calculated using MBG levels was strongly correlated with the HGI calculated using only pre-breakfast glucose (r=0.867) or FBG (r=0.687) levels. This suggests that individual differences in the relationship between HbA1c and blood glucose can be assessed using MBG or fasting glucose measurements. Common variations as small as 1% in HbA1c from MBG levels or FBG-predicted HbA1c can result in significant clinical errors. Therefore, clinicians should consider using an alternative index of glycemic control, such as blood glucose, GA, fructosamine, or CGM. Both approaches serve to avoid potentially inappropriate treatment intensification, thereby minimizing the risk of hypoglycemia.

We have previously reported that the glycation gap and FBG-based HGI were mostly consistent [3]. In this study, we also found that the glycation gap and MBG-based HGI were highly correlated in patients with T2DM. The discrepancy between HbA1c levels and other measures of glycemia, as calculated by the glycation gap or HGI, respectively, can be substantial in magnitude and is consistent over time [1]. Determining the glycation gap or HGI has the additional benefit of providing a prognostic indicator of patients’ risk of diabetic complications. A high HGI was independently associated with cardiovascular disease in patients with T2DM [5]. Moreover, a higher HGI in people without diabetes has been associated with increased coronary artery calcification [6], carotid atherosclerosis [19], insulin resistance [19], hepatic steatosis [20], and inflammation [21].

Our study was limited by the small number of patients. Future studies with larger patient populations will be required to confirm our findings. We performed 72-hour CGM at baseline and after 1 month. Frequent CGM can be burdensome for patients with T2DM due to the need for constant calibration and skin irritation. Second, there was a lack of data on factors that could explain the HGI or glycation gap. Third, although we did not change the medications of the study population during this study, HbA1c and GA values decreased after 1 month. Since this study was not conducted with real-time CGM devices, CGM provided glucose profiles retrospectively. During CGM use, the patients were instructed to obtain a minimum of three or four self-monitored blood glucose measurements per day. Frequent glucose measurements may be associated with improvements of glucose control, which in turn could affect HGI and glycation gap calculations. Nevertheless, the consistency and reproducibility of the HGI and glycation gap were maintained.

Our study had some strengths when compared with previous studies. First, we used CGM data to calculate the HGI. Compared with serial blood glucose measurements, CGM can provide more data and allows a more comprehensive glycemic assessment. Second, to overcome differences in the time frame of glycemic markers, we measured HbA1c and GA simultaneously at 1-month intervals, rather than at 3-month intervals. Our study only examined outpatients with stable glycemic control. In a previous study [11], we examined inpatients with poor glycemic control at admission and found large differences in HbA1c values between the first and second visits. Therefore, the glycation gap does not mean a difference in the time frame of glycemic markers.

In conclusion, the HGI, which indicates whether measured HbA1c levels are low, similar, or high relative to MBG levels, remained relatively stable in individuals over time. Patients with similar MBG levels may have significant differences in HbA1c levels due to interindividual variations in glucose metabolism and the hemoglobin glycation rate.