Acute glycemic changes in brain and subcutaneous tissue measured by continuous glucose monitoring system in hereditary hypertriglyceridemic rat.

Parallel glucose measurements in blood and other different tissues give us knowledge about dynamics of glycemia changes, which depend on vascularization, distribution space and local utilization by tissues. Such information is important for the understanding of glucose homeostasis and regulation. The aim of our study was to determine the time-lag between blood, brain, and adipose tissue during rapid glucose changes in a male hHTG rat (n=15). The CGMS sensor Guardian RT (Minimed/Medtronic, USA) was inserted into the brain and into the abdominal subcutaneous tissue. Fixed insulin and variable rate of glucose infusion was used to maintain euglycemia during sensor calibration period. At 0 min, 0.5 g/kg of bolus of glucose was administered, and at 50 min, 5 IU/kg of bolus of insulin was administered. Further glucose and insulin infusion was stopped at this time. The experiment was finished at 130 min and animals were euthanized. The time-shift between glycemia changes in blood, brain, and subcutaneous tissue was calculated by identification of the ideal correlation function. Moreover, the time to achieve 90 % of the maximum glucose excursion after intervention (T90) was measured to compare our data with the literature. The time-lag blood vs. brain and blood vs. subcutaneous tissue was 10 (10; 15) min and 15 (15; 25) min, respectively. The difference was statistically significant (P=0.01). T90 after glucose bolus in brain and subcutaneous tissue was 10 min (8.75; 15) and 15 min (13.75; 21.25), respectively. T90 after insulin bolus in brain and subcutaneous tissue was 10 min (10; 15) and 20 min (20; 27.5), respectively. To the contrary, with literature, our results showed earlier glucose level changes in brain in comparison with subcutaneous tissue after glucose and insulin boluses. Our results suggest that glucose dynamics is different within monitored tissues under rapid changing glucose level and we can expect similar behavior in humans. Improved knowledge about glucose distribution and dynamics is important for avoiding hypoglycemia.