Hemoglobin Glycation Rate Constant in Non-diabetic Individuals

Abstract

The objectives were as follows: (1) estimating mean value of the overall hemoglobin glycation rate constant (k); (2) analyzing inter-individual variability of k; (3) verifying ability of the hemoglobin A1c (HbA1c) formation model to predict changes of HbA1c during red blood cells cultivation in vitro and to reproduce the clinical data. The mean k estimated in a group of 10 non-diabetic subjects was equal to 1.257 ± 0.114 × 10(-9) L mmol(-1) s(-1). The mean k was not affected by a way of estimation of glycemia. The mean k differed less than 20% from values reported earlier and it was almost identical to the mean values calculated on basis of the selected published data. Analysis of variability of k suggests that inter-individual heterogeneity of HbA1c formation is limited or rare. The HbA1c mathematical model was able to predict changes of HbA1c in vitro resulting from different glucose levels and to reproduce a linear relationship of HbA1c and average glucose obtained in the A1C-Derived Average Glucose Study. This study demonstrates that the glycation model with the same k value might be used in majority of individuals as a tool supporting interpretation of HbA1c in different clinical situations.

Modulation of red blood cell population dynamics is a fundamental homeostatic response to disease

“…It is possible that the mild decrease in ferritin found in the low v c individuals leads to an iron‐restricted erythropoiesis which directly alters RBC morphology in a way that mimics a low v c without actually extending the RBC lifespan. HbA1c provides an estimate of mean RBC age in non‐diabetics . We measured hemoglobin A1c levels in the non‐diabetics among these individuals with decreased ferritin and low v c and found a statistically significant increase relative to the non‐diabetics in the group with normal ferritin and v c , supporting the conclusion that the decreased ferritin is in fact associated with delayed RBC clearance.…”

“…HbA1c is proportional to the mean plasma glucose concentration and to the mean RBC age . In non‐diabetic individuals, HbA1c is linearly dependent on mean RBC age . We can therefore test the prediction that elevated RDW is associated with elevated mean RBC age by measuring v c and HbA1c in non‐diabetics.…”

Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring

“…The age distribution of RBCs within an individual is assumed to be uniform, with cell ages between 0 and 2 · M RBC . We also assume that the glycation rate is essentially constant as has been demonstrated previously (3,21). See “Glycation rate and M RBC ” in Supplementary Methods for more detail.…”

“…The first component ([1 − HbA 1 c (0)]), as discussed above, varies too little overall (~0.994 – 1.00) to be a significant cause of glucose-independent variation in HbA1c. The second component ( k g ) is not currently possible to measure directly in vivo , but it does not appear to vary between patients (21), and there is no reason to expect that a first-order chemical reaction rate would vary systematically between patients. The third component (M RBC ) has been measured with demanding and sophisticated labeling methods and has a mean of about 58 days and a standard deviation of 4.5–6.5 days, for a coefficient of variation $[CVfalse({\mathrm{M}}_{\text{RBC}}false)=\frac{\mathrm{italicstd}false({\mathrm{M}}_{\text{RBC}}false)}{\mathrm{italicmean}false({\mathrm{M}}_{\text{RBC}}false)}]$ between 7.8% and 11.2% (3, 4).…”

Validation of a hemoglobin A1c model in patients with type 1 and type 2 diabetes and its use to go beyond the averaged relationship of hemoglobin A1c and mean glucose level

“…Neither can it be used to study the influence of different glycemia profiles on the HbA 1c level. For this purpose, mathematical modeling has been applied, among other methodologies [ 3 - 12 ].…”