Elevated Circulating PCSK9 Concentrations Predict Subclinical Atherosclerotic Changes in Low Risk Obese and Non-Obese Patients

循环 PCSK9 浓度升高可预测低风险肥胖和非肥胖患者的亚临床动脉粥样硬化变化

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作者:Štefan Tóth, Ján Fedačko, Tímea Pekárová, Zdenka Hertelyová, Matan Katz, Adil Mughees, Jozef Kuzma, Peter Štefanič, Ivan Kopolovets, Daniel Pella

Conclusion

PCSK9 plasma levels significantly correlated with subclinical vascular changes and their values were significantly elevated in obese subjects. We assume that PCSK9 could be used as a predictor of early vascular involvement, prior to the existence of manifest atherosclerosis. These results also highlight the role of anti-PCSK9 treatment in primary prevention.

Methods

In this study, 120 healthy patients, free of manifest cardiovascular diseases, diabetes mellitus, and without lipid-lowering therapy, were divided into three groups based on BMI: normal weight (N = 50), overweight (N = 30), and obese (N = 40). Biochemical parameters, including basic lipid and non-lipid ones, were analyzed. PCSK9 levels were measured by ELISA, vascular changes were quantified by carotid ultrasound (carotid artery intima-media thickness, cIMT), and arterial stiffness parameters (pulse wave velocity, PWV; augmentation index, AI; stiffness parameter, β) were measured by an echo-tracking method.

Results

Plasma levels of PCSK9 significantly increased in obese (172.78 ± 51.67 ng/mL) in comparison with overweight (120.14 ± 37.64, p < 0.001) and normal weight groups (114.92 ± 35.87, p < 0.001). Differences between the overweight and normal weight groups were not significant (p = 0.85). The level of PCSK9 significantly correlated with values of BMI (p < 0.001, r = 0.38). In addition to increase in laboratory parameters associated with moderate metabolic changes, significant increase in cIMT and parameters of vascular changes (β, AI, PWV) were detected in groups with elevated BMI. Significant positive linear correlation of PCSK9 concentrations and cIMT (p < 0.001, r = 0.39), PWV (p < 0.001, r = 0.31), and β (p < 0.001, r = 0.3) were found. In multivariable regression analysis after adjusting for gender, age, BMI, and LDL, the impact of PCSK9 on cIMT, β, and PWV remained significant (p = 0.006, 0.03, and 0.002, respectively).

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