Usefulness of fetuin-A to predict risk for cardiovascular disease among patients with obstructive sleep apnea

Level of Serum Fetuin-A Correlates with Heart Rate in Obstructive Sleep Apnea Patients without Metabolic and Cardiovascular Comorbidities

Obstructive sleep apnea (OSA) is the most common type of sleep-induced breathing disorder in the adult population and significantly affects the condition of the cardiovascular system. Fetuin-A (Fet-A) is a hepato- and adipokine, which prevents vessel calcification, and its level correlates with atherogenesis and metabolic disorders. The associations of cardiovascular diseases (CVD) both with OSA, which increases CVD risk, and Fet-A, which prevents CVD, justify the question of their mutual interactions in patients with OSA. Therefore, we sought to analyze Fet-A as an early biomarker of CVD risk in OSA patients without metabolic and cardiovascular comorbidities except for properly controlled arterial hypertension. We have found that in these patients, OSA does not appear to directly affect Fet-A levels. However, high Fet-A levels were more common in the group of patients with OSA, and the hypopnea index was significantly higher among subjects with the highest Fet-A levels. The level of Fet-A in OSA patients positively correlates with pulse rate, and it does not correlate with pulse pressure in this group unlike in the control group, where such a relationship exists. To our best knowledge, this is the first study to analyze this relationship in OSA patients without any significant cardiovascular comorbidities.

Low Levels of Serum Fetuin-A and Retinol-Binding Protein 4 Correlate with Lipoprotein Subfractions in Morbid Obese and Lean Non-Diabetic Subjects

Background: Fetuin-A and retinol-binding protein 4 (RBP4) are secreted as both hepatokine and adipokine. These are involved in insulin resistance, obesity-related dyslipidemia, and atherosclerosis. To date, correlations of circulating fetuin-A and RBP4 with lipoprotein subfractions as well as high-density lipoprotein (HDL)-linked proteins have not been entirely investigated in morbid obese and lean non-diabetic subjects. Methods: One-hundred obese non-diabetic patients (body mass index, BMI: 42.5 ± 8.1 kg/m²) along with 32 gender and age-matched normal weight controls (BMI: 24.5 ± 2.5 kg/m²) were enrolled in our study. Serum fetuin-A and RBP4 were measured by ELISA. Lipoprotein subfractions were distributed by Lipoprint gelelectrophoresis. Results: Serum fetuin-A and RBP4 were unexpectedly lower in obese patients (p < 0.01 and p < 0.01, respectively) compared to controls and correlated with each other (r = 0.37; p < 0.001). Fetuin-A had positive correlations with HDL-C (r = 0.22; p = 0.02), apolipoprotein AI (apoAI) (r = 0.33; p < 0.001), very-low density lipoprotein (VLDL) subfraction (r = 0.18; p = 0.05), and large HDL subfraction levels (r = 0.3; p = 0.001) but did not show correlation with carbohydrate parameters in all subjects. RBP4 correlated positively with HDL-C (r = 0.2; p = 0.025), apoAI (r = 0.23; p = 0.01), VLDL subfraction (r = 0.37; p < 0.001), intermediate HDL subfraction (r = 0.23; p = 0.01), and small HDL subfraction (r = 0.21; p = 0.02) concentrations, as well as C-peptide levels in overall participants. Backward stepwise multiple regression analysis showed that serum fetuin-A concentration is best predicted by RBP4 and large HDL subfraction. In model 2, VLDL subfraction was the independent predictor of serum RBP4 level. Conclusions: Our data may indicate a potential role of fetuin-A and RBP4 in impaired lipoprotein metabolism associated with obesity.

Circulating Anti-Sorting Nexins 16 Antibodies as an Emerging Biomarker of Coronary Artery Disease in Patients with Obstructive Sleep Apnea

Biomarkers are not available for monitoring the onset and progression of coronary artery disease (CAD) in patients with obstructive sleep apnea (OSA), a major risk factor for arteriosclerotic cardiovascular diseases. This study aimed to test for correlation between circulating anti-Sorting Nexins 16 antibody (SNX16-Ab) levels, CAD history and clinical parameters of patients with OSA. Sixty-four healthy donors, 82 adults with OSA, and 96 with acute coronary syndrome (ACS) were studied. Serum samples were collected at diagnostic polysomnography in the OSA group or at the disease onset in the ACS group. Serum SNX16-Ab levels were measured by amplified luminescence proximity homogeneous assay (AlphaLISA), and correlation between SNX16-Ab levels and clinical parameters was analyzed. SNX16-Ab levels and apnea-hypopnea index (AHI) were weakly correlated. Additionally, logistic regression analyses of OSA group identified that elevated SNX16-Ab level associated with the history of CAD. Circulating SNX16-Ab could increase during CAD pathogenesis in patients with OSA. Further prospective studies are required to prove the predictive potential of SNX16-Ab level in CAD onset of patients with OSA.

Metabolic Profile in Patients with Mild Obstructive Sleep Apnea

BACKGROUND

Mild obstructive sleep apnea (OSA) is a highly prevalent disorder in adults. However, it is not clear whether mild OSA has significant metabolic complications. This study examined the prevalence of metabolic syndrome (MS) in patients with mild OSA compared to control group.

METHODS

Adults (18-65 years of age) of both genders with a body mass index (BMI) ≤35 kg/m² were included. The mild OSA group comprised of patients with an apnea-hypopnea index (AHI) score of ≥5 but ≤15 events/hr of sleep, independent of other symptoms. The control group (CG) comprised individuals with an AHI of <5 events/hr of sleep and an Epworth Sleepiness Scale score of <10. The following were used for both groups: two questionnaires on sleepiness, the maintenance of wakefulness test, and full-night polysomnography. Anthropometric measurements and fasting blood samples were obtained, including fasting glucose and insulin, total cholesterol and its subfractions [low-density lipoprotein, very low-density lipoprotein, and low-density lipoprotein cholesterol (HDL-c)], triglycerides (TG), and the TG/HDL-c ratio. In addition, the quantitative insulin sensitivity check index and homeostasis model assessment indices were calculated.

RESULTS

Thirty-two percent of mild OSA patients had MS, 43.5% of mild OSA patients had hypertension, 14% showed dyslipidemia, and 56% had prediabetes. The OSA group showed increased TG (CG: 90.0 ± 51.9 vs. OSA: 140.3 ± 78.2 mg/dL, P = 0.004), and TG/HDL-c (CG: 1.9 ± 1.4 vs. OSA: 3.1 ± 2.0, P = 0.05), independent of adjustments. Independent of obesity (BMI <30 kg/m²), there was a negative correlation between total cholesterol and TG with mean oxygen saturation, independent of obesity (BMI <30 kg/m²).

CONCLUSIONS

Our findings showed dysregulation in lipid profiles after adjustments for confounders in the mild OSA group, and there was a correlation between these parameters and sleep hypoxemia. The TG/HDL-c ratio in particular was high, suggesting that it might be investigated as a marker of a detrimental metabolic profile in these patients.