Alterations in heart rate variability during everyday life are linked to insulin resistance. A role of dominating sympathetic over parasympathetic nerve activity?

Abstract

Aims: To evaluate the role of the autonomic nervous system (ANS) in the development of insulin resistance (IR) and assess the relationship between IR and activity of ANS using power spectrum analysis of heart rate variability (HRV).

Subjects and methods: Twenty-three healthy first-degree relatives of patients with type 2 diabetes (R) and 24 control subjects without family history of diabetes (C) group-matched for age, BMI and sex were included. Insulin sensitivity (M value) was assessed by hyperinsulinemic (56 mU/m(2)/min) euglycemic clamp. Activity of the ANS was assessed using power spectrum analysis of HRV in long-term recordings, i.e., 24-h ECG monitoring, and in short-term recordings during manoeuvres activating the ANS. Computed tomography was performed to estimate the amount and distribution of abdominal adipose tissue.

Results: Insulin sensitivity (M value, mg/kg lbm/min) did not differ significantly between the R and C groups. Total spectral power (Ptot) and very low-frequency (PVLF) power was lower in R than C during 24 h ECG-recordings (p = 0.02 and p = 0.03). The best fit multiple variable linear regression model (r(2) = 0.37, p < 0.001 for model) indicated that body composition (BMI) and long-term low to high frequency (LF/HF) power ratio (std β = -0.46, p = 0.001 and std β = -0.28, p = 0.003, respectively) were significantly and independently associated with the M value.

Conclusion: Altered heart rate variability, assessed by power spectrum analysis, during everyday life is linked to insulin resistance. The data suggest that an increased ratio of sympathetic to parasympathetic nerve activity, occurring via both inherited and acquired mechanisms, could potentially contribute to the development of type 2 diabetes.

Keywords: Autonomic nervous system; Heart rate variability; Insulin sensitivity; Spectral analysis; Type 2 diabetes.

Fig. 1

Long-term heart rate variability (HRV) using 24-h ECG recordings in two subjects where the subject to the right (a control) presented higher heart rate variability compared to the subject shown to the left (b). Top panels show the total average power spectrum and the bottom panels show Poincaré plots where each point shows the relation between two subsequent RR intervals. 24 h PSD = average power spectral density over 24-h, RR(x) = “current” RRinterval, RR(x−1) = previous RR-interval

Fig. 2

Long-term heart rate variability (HRV) assessed by 24-h ECG recordings. LF to HF power ratio was negatively and significantly associated with M value (mg/kg lbm/min) inrelatives (R = blue circles) and controls (C = green triangles) taken together