Glycaemic patterns in healthy elderly individuals and in those with impaired glucose metabolism - exploring the relationship with nonglycaemic variables.

Medina Escobar, Pedro; Sakem, Benjamin; Risch, Lorenz; Risch, Martin; Grebhardt, Chris; Nydegger, Urs E; Stanga, Zeno (2019). Glycaemic patterns in healthy elderly individuals and in those with impaired glucose metabolism - exploring the relationship with nonglycaemic variables. Swiss medical weekly, 149, w20163. EMH Media 10.4414/smw.2019.20163

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OBJECTIVE

The SENIORLABOR study data were explored (i) to examine the evolution during senescence of the differences between measured glycated haemoglobin (HbA1c) values and the values predicted by using regression to extrapolate from measured fructosamine levels; (ii) to scrutinise the relationship between the glycation gap and insulin resistance using a homeostasis model assessment, and between the glycation gap and a low-grade inflammation marker (C-reactive protein serum concentration); and (iii) to investigate the glycation gap ranges in relation to triglyceride levels and kidney function.

SUBJECTS AND METHODS

A total of 1432 Swiss individuals aged >60 years and classified as healthy (547), prediabetic (701) or diabetic (184) based on their fasting plasma glucose and HbA1c values were included in the study. The glycation gap was evaluated and assigned to one of four categories: <−0.5; −0.5 to <0.0; 0.0 to ≤0.5; >0.5.

RESULTS

In healthy and prediabetic participants, the homeostasis model assessment for estimation of insulin resistance (p <0.01), high-sensitivity C-reactive protein (p <0.001) and triglyceride (p = 0.02) values tended to increase with increasing glycation gap category and were highest in the glycation gap category >0.5. Homeostasis model assessment for estimation of insulin resistance, high-sensitivity C-reactive protein and triglyceride levels tended to increase with increasing glycation gap category and were highest in the glycation gap category >0.5. Significant differences (p <0.01) between glycation gap categories were seen among different high-sensitivity C-reactive protein concentration groups. Interestingly, in diabetic participants, homeostasis model assessment for estimation of insulin resistance values, triglyceride concentrations and estimation of glomerular filtration values all decreased with decreasing glycation gap category. In the group of participants with a glycation gap >0.5, high-sensitivity C-reactive protein values tended to increase with increasing glycation gap, whereas for participants with type 2 diabetes and in the glycation gap group >0.5, high-sensitivity C-reactive protein levels tended to decrease as the glycation gap increased. The percentage of participants with type 2 diabetes mellitus increased from 2% in the glycation gap category <−0.5 to 76% in the glycation gap category >0.5. In contrast, the percentage of healthy participants fell from 85% to 7%.

CONCLUSION

This is the first time that a direct comparison of healthy, prediabetic and diabetic participants, all assessed under identical conditions and using identical methodology, has clearly demonstrated a different glycation gap pattern. Thus, we contribute evidence that the glycation gap might be of interest in the care of diabetic patients and their prophylaxis, while acknowledging that more studies are needed to confirm our findings. (Trial registration number ISRCTN53778569).

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