摘要
目的探讨血清前蛋白转化酶枯草溶菌素-9(PCSK9)在系统性红斑狼疮(SLE)患者心血管疾病(CVD)发生风险中的预测价值。方法选取2023年4月至2024年1月兰州大学第二医院风湿免疫科收治的75例SLE患者作为SLE组,另选取同期在兰州大学第二医院体检的30例健康体检者作为对照组。并将SLE患者按照CVD发生风险等级分为中高危组和低危组。比较SLE组与对照组血清PCSK9水平,比较低危组、中高危组一般资料和血清学指标[总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白(LDL)、高密度脂蛋白(HDL)、PSCK9]。采用Pearson/Spearman相关分析SLE患者血清PCSK9水平与年龄、体质量指数(BMI)、腰围、TC、TG、HDL、LDL水平的相关性。采用多因素Logistic回归分析SLE患者有中高危CVD风险的独立危险因素。绘制受试者工作特征(ROC)曲线分析血清PCSK9对SLE患者有中高危CVD风险的预测价值。结果SLE组血清PCSK9水平明显高于对照组,差异有统计学意义(P<0.05)。中高危组有30例患者,低危组有45例患者。中高危组年龄大于低危组,动脉粥样硬化患者比例、血清PCSK9水平高于低危组,差异均有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,血清PCSK9水平升高、年龄增大是SLE患者有中高危CVD风险的危险因素(P<0.05)。Pearson/Spearman相关分析结果显示,SLE患者血清PCSK9水平与年龄(r=0.228,P=0.053)、BMI(r=-0.005,P=0.963)、腰围(r=0.202,P=0.083)、TC(r_(s)=0.217,P=0.061)、TG(r_(s)=0.087,P=0.460)、HDL(r_(s)=0.495,P=0.080)、LDL(r_(s)=0.135,P=0.248)水平无相关性。ROC曲线分析结果显示,血清PCSK9预测SLE患者有中高危CVD风险的曲线下面积为0.729。结论血清PCSK9对SLE患者CVD发生风险具有一定预测价值,是潜在预测SLE患者CVD发生风险的生物标志物。
Objective To investigate the predictive value of serum proprotein converting enzyme subtilysin-9(PCSK9)in cardiovascular disease(CVD)risk in patients with systemic lupus erythematosus(SLE).Methods A total of 75 SLE patients admitted to the Department of Rheumatology and Immunology in the Second Hospital of Lanzhou University from April 2023 to January 2024 were selected as SLE group,and 30 healthy subjects who underwent physical examination in the Second Hospital of Lanzhou University during the same period were selected as control group.SLE patients were divided into middle high risk group and low risk group according to the risk of CVD.Serum PCSK9 levels were compared between SLE group and control group,and general data and serological indexes[total cholesterol(TC),triglyceride(TG),low density lipoprotein(LDL),high density lipoprotein(HDL),PCSK9]of low risk group and medium high risk group were compared.Pearson/Spearman correlation was used to analyze the correlation between serum PCSK9 level and age,body mass index(BMI),waist circumference,TC,TG,HDL and LDL levels in SLE patients.Multivariate Logistic regression was used to analyze the risk factors of moderate to high risk CVD in SLE patients.Receiver operating characteristic(ROC)curve was drawn to analyze the predictive value of serum PCSK9 in SLE patients with moderate to high risk of CVD.Results The serum PCSK9 level in SLE group was significantly higher than that in control group,and the difference was statistically significant(P<0.05).There were 30 patients in the medium high risk group and 45 patients in the low risk group.The age of middle high risk group was higher than that of low risk group,and the proportion of atherosclerosis and serum PCSK9 level of middle high risk group were higher than those of low risk group,and the differences were statistically significant(P<0.05).Multivariate Logistic regression analysis results showed that the increase of serum PCSK9 level and age were risk factors for moderate to high risk CVD in SLE patients(P<0.05).Pearson/Spearman correlation analysis showed that the serum PCSK9 level in SLE patients was correlated with age(r=0.228,P=0.053),BMI(r=-0.005,P=0.963),waist circumference(r=0.202,P=0.083),TC(r_(s)=0.217,P=0.061),TG(r_(s)=0.087,P=0.460),HDL(r_(s)=0.495,P=0.080),LDL(r_(s)=0.135,P=0.248)had no correlation.ROC curve analysis results showed that the area under the curve of serum PCSK9 in predicting moderate to high risk CVD risk in SLE patients was 0.729.Conclusion Serum PCSK9 has a certain predictive value for CVD risk in SLE patients,and which is a potential biomarker for predicting CVD risk in SLE patients.
作者
李文花
郝佳瑶
谭敏
毛婧
张瑞
张宪萌
沈海丽
LI Wenhua;HAO Jiayao;TAN Min;MAO Jing;ZHANG Rui;ZHANG Xianmeng;SHEN Haili(The Second Clinical College of Medicine,Lanzhou University,Lanzhou,Gansu 730000,China;Department of Rheumatology and Immunology,the Second Hospital of Lanzhou University,Lanzhou,Gansu 730030,China)
出处
《检验医学与临床》
CAS
2024年第11期1533-1537,共5页
Laboratory Medicine and Clinic
基金
甘肃省创新基地和人才计划项目(21JR7RA437)。
关键词
系统性红斑狼疮
心血管疾病
前蛋白转化酶枯草溶菌素-9
预测
炎症
systemic lupus erythematosus
cardiovascular diseases
proprotein converting enzyme subtilysin-9
prediction
inflammation