BACKGROUND: Evidence linking chronic kidney disease (CKD) with the increased risk of cardiovascular (CV) complications is firm. It is becoming clear that testing functions of the vascular endothelium in conjunction with various biomarkers may better the definition of CV risk profile in CKD patients. METHODS: Using Multiplexed analysis of 16 markers reflecting pro-inflammatory, anti-inflammatory, angiogenic, metabolic and anti-fibrinolytic factors in a series of 75 patients with CKD, who underwent echo-coloured Doppler study of carotid arteries, we analysed the contribution of each parameter to the characterization of atherosclerotic burden. As control group we enrolled 33 healthy individuals. RESULTS: On univariate analysis, intima-media thickness, number of atherosclerotic plaques and internal diameter of carotid arteries were strongly interrelated. Starting with these indicators of carotid atherosclerosis, we extracted by principal component analysis a single composite atherosclerosis severity score that accounted for 68% of the total variance of original variables. Biomarkers significantly related to severity of carotid atherosclerosis were MMP9, t-PAI-1, IL-6, NT-proBNP, IL-8 and VEGF. In multiple linear regression models adjusting for clinical variables the gain in prediction power was achieved when we added MMP9 and t-PAI-1 to the basic model. IL-6 produced the highest increase in the multiple R2 of the basic model. The combination of MMP9, t-PAI-1, IL-6, NT-proBNP, IL-8 and VEGF added to the basic model achieved gain in prediction power of + 7.5%. In this expanded model, IL-6 was the only biomarker that significantly predicted the severity of atherosclerosis. CONCLUSION: Multiplexed screening revealed that IL-6, MMP-9, tPAI-1 and VEGF showed a tight correlation with carotid atherosclerotic burden in patients with CKD.
BACKGROUND: Evidence linking chronic kidney disease (CKD) with the increased risk of cardiovascular (CV) complications is firm. It is becoming clear that testing functions of the vascular endothelium in conjunction with various biomarkers may better the definition of CV risk profile in CKDpatients. METHODS: Using Multiplexed analysis of 16 markers reflecting pro-inflammatory, anti-inflammatory, angiogenic, metabolic and anti-fibrinolytic factors in a series of 75 patients with CKD, who underwent echo-coloured Doppler study of carotid arteries, we analysed the contribution of each parameter to the characterization of atherosclerotic burden. As control group we enrolled 33 healthy individuals. RESULTS: On univariate analysis, intima-media thickness, number of atherosclerotic plaques and internal diameter of carotid arteries were strongly interrelated. Starting with these indicators of carotid atherosclerosis, we extracted by principal component analysis a single composite atherosclerosis severity score that accounted for 68% of the total variance of original variables. Biomarkers significantly related to severity of carotid atherosclerosis were MMP9, t-PAI-1, IL-6, NT-proBNP, IL-8 and VEGF. In multiple linear regression models adjusting for clinical variables the gain in prediction power was achieved when we added MMP9 and t-PAI-1 to the basic model. IL-6 produced the highest increase in the multiple R2 of the basic model. The combination of MMP9, t-PAI-1, IL-6, NT-proBNP, IL-8 and VEGF added to the basic model achieved gain in prediction power of + 7.5%. In this expanded model, IL-6 was the only biomarker that significantly predicted the severity of atherosclerosis. CONCLUSION: Multiplexed screening revealed that IL-6, MMP-9, tPAI-1 and VEGF showed a tight correlation with carotid atherosclerotic burden in patients with CKD.
Authors: Fen Wu; Farzana Jasmine; Muhammad G Kibriya; Mengling Liu; Oktawia Wójcik; Faruque Parvez; Ronald Rahaman; Shantanu Roy; Rachelle Paul-Brutus; Stephanie Segers; Vesna Slavkovich; Tariqul Islam; Diane Levy; Jacob L Mey; Alexander van Geen; Joseph H Graziano; Habibul Ahsan; Yu Chen Journal: Am J Epidemiol Date: 2012-04-24 Impact factor: 4.897
Authors: Sai Ram Keithi-Reddy; Francesco Addabbo; Tejas V Patel; Bharati V Mittal; Michael S Goligorsky; Ajay K Singh Journal: Kidney Int Date: 2008-06-11 Impact factor: 10.612