The relative contribution of diurnal and nocturnal glucose exposures to HbA1c in type 1 diabetes males: a pooled analysis

Purpose

The exact contribution of daily glucose exposure to HbA1c in people with type 1 diabetes (T1D) remains controversial. We examined the contribution of pre- and postprandial glycaemia, nocturnal and early-morning glycaemia, and glycaemic variability to HbA1c levels in T1D. In this analysis, we used clinical data, namely age, BMI and HbA1c, as well as glycaemic metrics (24-h glycaemia, postprandial, nocturnal, early-morning glycaemia, wake-up glucose, and glycaemic variability) obtained over a four-week period of continuous glucose monitoring (CGM) wear in thirty-two males with T1D.

Methods

The trapezoid method was used estimate the incremental area under the glucose curve (iAUC) for 24-h, postprandial (3-h period following breakfast, lunch, and dinner, respectively), nocturnal (between 24:00–04:00 AM), and early-morning (2-h period 2-h prior to wake-up) glycaemia. Linear regression analysis was employed whereby CGM-derived glycaemic metrics were explanatory variables and HbA1c was the outcome.

Results

Thirty-two T1D males (mean ± SD: age 29 ± 4 years; HbA1c 7.3 ± 0.9% [56 ± 13 mmol/mol]; BMI 25.80 ± 5.01 kg/m²) were included in this analysis. In linear models adjusted for age and BMI, HbA1c was associated with 24-h mean glucose (r² = 0.735, p < 0.001), SD (r² = 0.643, p = 0.039), and dinner iAUC (r² = 0.711, p = 0.001). CGM-derived metrics and non-glycaemic factors explained 77% of the variance in HbA1c, in which postprandial glucose accounted for 32% of the variance explained. The single greatest contributor to HbA1c was dinner iAUC resulting in 0.6%-point (~7 mmol/mol) increase in HbA1c per SD increase in dinner iAUC.

Conclusions

Using comprehensive CGM profiling, we show that postprandial glucose, specifically evening-time postprandial glucose, is the single largest contributing factor to HbA1c in T1D.

Trial registration number

NCT02204839 (July 30th 2014); NCT02595658 (November 3rd 2015).

Glucose variability is associated with an adverse vascular profile but only in the presence of insulin resistance in individuals with type 1 diabetes: An observational study

AIMS/HYPOTHESIS

We hypothesised that the detrimental effect of high glucose variability (GV) in people with type 1 diabetes is mainly evident in those with concomitant insulin resistance.

METHODS

We conducted secondary analyses on continuous glucose monitoring (CGM) using baseline observational data from three randomised controlled trials and assessed the relationship with established vascular markers. We used standard CGM summary statistics and principal component analysis to generate individual glucose variability signatures for each participant. Cluster analysis was then employed to establish three GV clusters (low, intermediate, or high GV, respectively). The relationship with thrombotic biomarkers was then investigated according to insulin resistance, assessed as estimated glucose disposal rate (eGDR).

RESULTS

Of 107 patients, 45%, 37%, and 18% of patients were assigned into low, intermediate, and high GV clusters, respectively. Thrombosis biomarkers (including fibrinogen, plasminogen activator inhibitor-1, tissue factor activity, and tumour necrosis factor-alpha) increased in a stepwise fashion across all three GV clusters; this increase in thrombosis markers was evident in the presence of low but not high eGDR and at a threshold of eGDR <5.1 mg/kg/min.

CONCLUSION

Higher GV is associated with increased thrombotic biomarkers in type 1 diabetes but only in those with concomitant insulin resistance.