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 HbA_1c 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 HbA_1c and a fructosamine-derived standardized predicted HbA_1c 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.The glycation gap (G-gap) refers to the potential deviation of glycated HbA_1c away from the other indirect estimate of blood glucose attainment such that it might read substantially lower or higher than expected (1–3). Glycated HbA_1c represents the net effect of several mechanisms, which may shift its direct glycation relationship with overall levels of glycemia (4–6). Many factors are known to influence HbA_1c, including various erythrocytic processes (6–9). Protein glycation is a nonenzymatic reaction dependent on glucose concentrations, but intracellular enzymatic deglycation of proteins has also been identified (10). The key deglycating enzyme, fructosamine-3-kinase, has isoforms and a genetic polymorphism suggested to influence HbA_1c variability, but any impact on HbA_1c glycation is unknown; although it seems unlikely that glycated HbA_1c is a substrate for this enzyme since it has been shown that there is no evidence that it plays any role in HbA_1c deglycation at the relevant glycation site (11,12). To add to the potential for a spurious generation of a G-gap, many factors, including variability in protein turnover and obesity, may affect fructosamine estimation (1,13,14). The evidence concerning the effects of urinary protein loss are mixed (1,13). Even then, fructosamine reflects blood glucose attainment over a much shorter time frame than HbA_1c and may more readily be influenced by very short-term changes in blood glucose levels. It may simply be that the G-gap is no more than an empiric and potentially spurious measure of disagreement between the two indirect estimates of glycemic control, with each having a number of confounders to the direct relationship with blood glucose.Although we have demonstrated that the G-gap is a consistent phenomenon within individuals over time (1), there remains doubt as to whether the G-gap is a real phenomenon or if it has any significant sequelae (15). Hypothesizing that the G-gap is an inconsequential nonsystematic event, irrelevant to diabetes outcomes, it would not then be expected to be associated with distinct subpopulations of human diabetes or to have any sequelae in clinical outcomes. This article explores the association of the G-gap with diabetic population demographic factors and with crucial clinical outcomes to determine if such associations exist.