Interactions of Sleep Apnea, the Autonomic Nervous System, and Its Impact on Cardiac Arrhythmias

New frontiers in pharmacologic obstructive sleep apnea treatment: A narrative review

Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing characterized by intermittent partial or complete closure of the upper airway during sleep. If left untreated, OSA is associated with adverse cardiovascular outcomes such as hypertension, coronary heart disease, heart failure, cardiac arrhythmia, stroke, and death. Positive airway pressure (PAP) is often considered the first-line treatment for OSA. While PAP can be very effective in reducing the number of obstructive apneas and hypopneas, its impact on prevention of adverse cardiovascular consequences remains controversial, and treatment adherence is often poor. Hence, the necessity for novel treatment options to help those who cannot adhere to positive airway pressure treatment. Different classes of medications have been tested with regards to their effect on OSA severity. This review 1) provides an update on the epidemiology and pathophysiology of OSA, 2) outlines the mechanistic rationale for medication classes tested as OSA treatment and 3) discusses the effects of these medications on OSA. Several wake-promoting medications are approved for management of persistent sleepiness despite OSA treatment; discussion of these symptomatic treatments is outside the scope of this review. Herein, the authors review the current evidence for pharmacological management of OSA and provide future directions.

Obstructive sleep apnoea increases lipolysis and deteriorates glucose homeostasis in patients with type 2 diabetes mellitus

Obstructive sleep apnoea (OSA) is associated with type 2 diabetes mellitus (T2DM). However, mechanisms mediating association between these two conditions remain unclear. This study investigated, whether the OSA-associated changes in adipose tissue lipolysis might contribute to impaired glucose homeostasis in patient with T2DM. Thirty-five matched subjects were recruited into three groups: T2DM + severe OSA (T2DM + OSA, n = 11), T2DM with mild/no OSA (T2DM, n = 10) and healthy controls (n = 14). Subcutaneous abdominal adipose tissue microdialysis assessed spontaneous, epinephrine- and isoprenaline-stimulated lipolysis. Glucose metabolism was assessed by intravenous glucose tolerance test. Spontaneous lipolysis was higher in the T2DM + OSA compared with the T2DM (60.34 ± 23.40 vs. 42.53 ± 10.16 μmol/L, p = 0.013), as well as epinephrine-stimulated lipolysis (236.84 ± 103.90 vs. 167.39 ± 52.17 µmol/L, p < 0.001). Isoprenaline-stimulated lipolysis was unaffected by the presence of OSA (p = 0.750). The α₂ anti-lipolytic effect was decreased in T2DM + OSA by 59% and 315% compared with T2DM and controls (p = 0.045 and p = 0.007, respectively). The severity of OSA (AHI) was positively associated with spontaneous (p = 0.037) and epinephrine-stimulated (p = 0.026) lipolysis. The α₂-adrenergic anti-lipolytic effect (p = 0.043) decreased with increasing AHI. Spontaneous lipolysis was positively associated with Insulin resistance (r = 0.50, p = 0.002). Epinephrine-stimulated lipolysis was negatively associated with the Disposition index (r =  - 0.34, p = 0.048). AHI was positively associated with Insulin resistance (p = 0.017) and negatively with the Disposition index (p = 0.038). Severe OSA in patients with T2DM increased adipose tissue lipolysis, probably due to inhibition of the α₂-adrenergic anti-lipolytic effect. We suggest that dysregulated lipolysis might contribute to OSA-associated impairments in insulin secretion and sensitivity.

Simulating Dynamics of Circulation in the Awake State and Different Stages of Sleep Using Non-autonomous Mathematical Model With Time Delay

We propose a mathematical model of the human cardiovascular system. The model allows one to simulate the main heart rate, its variability under the influence of the autonomic nervous system, breathing process, and oscillations of blood pressure. For the first time, the model takes into account the activity of the cerebral cortex structures that modulate the autonomic control loops of blood circulation in the awake state and in various stages of sleep. The adequacy of the model is demonstrated by comparing its time series with experimental records of healthy subjects in the SIESTA database. The proposed model can become a useful tool for studying the characteristics of the cardiovascular system dynamics during sleep.