Circadian rhythm of glycemic control in patients with mellitus diabetes

This doctoral thesis is based on the publication of 2 studies that aim to determine if the variability of glycemia, evaluated with continuous glucose monitoring (CGM), presents a circadian rhythm in patients with diabetes mellitus (DM) type I and II. Study I. Daily glucose variability is higher in diabetic mellitus (DM) patients which has been related to the severity of the disease. However, it is unclear whether glycemic variability displays a specific pattem oscilation or if it is completeiy random. Thus, to determine glycemic variability pattern, we measured and analyzed continuous glucose monitoring (CGM) data, in control subjects and patients with DM type-1 (T1D). CGM data was assessed for 6 days (day: 08:00-20:00-h; and night: 20:00- 08:00-h). Participants (n=172; age= 18-80 years) were assigned to T1D (n= 144, females=65) and control (i.e., healthy; n=28, females=22) groups. Anthropometry, pharmacologic treatments, glycosylated hemoglobin (HbAlc) and years of evolution were determined. T1D females displayed a higher glycemia at 10:00-14:00-h vs. T1D males and control females. DM patients displays mainly stationary oscillations (deterministic), with circadian rhythm characteristics. The glycemia oscillated between 2 and 6 days. The predictive model of glycemia showed that it is possible to predict hyper and hypoglycemia (R2=0.94 and 0.98, respectively) in DM patients independent of their etiology. Our data showed that glycemic variability had a specific oscillation pattern with circadian characteristics, with episodes of hypoglycemia and hyperglycemia at day phases, which could help therapeutic action for this population. Study II. The objective of study 2 was to determine the characteristics of glycemic oscillations in T2D and to verify if they can be predicted over time in patients. Daily glucose variability is reported to be higher in patients with diabetes mellitus (DM) than in the general population. Specific oscillatory patterns of glycemic control are knovn to exist on patients with type 1 DM (T1D), but it is unclear whether the same is true for patients with type 2 DM (T2D). Here, we seek to determine patterns of glycemic variability in T2D patients using continuous glucose monitoring. Data were evaluated for 6 continuous days (day: 08:00-20:00; and night: 20:00---08:00). Participants were assigned to T2D (n=24, women= 10) and control (ie, healthy; n=28, women=22) groups. The results showed that glycosylated hemoglobin, blood glucose and body mass index were higher in T2D patients than in controls (all p<0.05). Furthermore, the time in hyperglycemia and euglycemia was markedly longer and shorter, respectively, in the T2D group (p<0.05) with no significant difference for time in hypoglycemia. The data on glycemic variability revealed that the values of the standard deviation, the coefficient of variation and the total power of glycemic variability were significantly higher in the T2D group than in the control group (p<0.05). In addition, oscillatory pattens were significantly different between groups (p=0.032): the control group was mainly distributed at 2-3 and >6 days, while the T2D group showed a more homogeneous distribution at 2-3 days. >6 days. The glycemia predictive model, previously used in DM1, demonstrated that it is possible to accurately predict hyperglycemic and hypoglycemie events (R2=0.97 and 0.98, respectively). Therefore, like what is observed in T1D, patients with T2D exhibit specific oscillatory pattens of glycemíc control, which are possible to predict. These findings may help improve the treatment of DM by considering the individual oscillatory patterns of patients.