Physiol. Genomics 31: 402-409, 2007.
First published August 14, 2007; doi:10.1152/physiolgenomics.00104.2007
1094-8341/07 $8.00
Received 7 May 2007;
accepted in final form 7 August 2007.
Physiological Genomics 31:402-409 (2007)
1094-8341/06 $8.00 © 2007 American Physiological Society
Circulating chemokines accurately identify individuals with clinically significant atherosclerotic heart disease
Diego Ardigo1,2,*,
Themistocles L. Assimes1,*,
Stephen P. Fortmann3,
Alan S. Go4,5,
Mark Hlatky1,
Evangelos Hytopoulos6,
Carlos Iribarren4,
Philip S. Tsao1,
Raymond Tabibiazar1,6,
Thomas Quertermous1 for the ADVANCE Investigators
1 Division of Cardiovascular Medicine, Stanford University, Stanford, California
2 Department of Internal Medicine and Biomedical Sciences, Parma University, Parma, Italy
3 Stanford Prevention Research Center, Stanford University, Stanford
4 Division of Research, Kaiser Permanente of Northern California, Oakland
5 Department of Epidemiology, Biostatistics, & Medicine, University of California at San Francisco, San Francisco, California
6 Aviir, Incorporated, Palo Alto, California
Serum inflammatory markers correlate with outcome and response to therapy in subjects with cardiovascular disease. However, current individual markers lack specificity for the diagnosis of coronary artery disease (CAD). We hypothesize that a multimarker proteomic approach measuring serum levels of vascular derived inflammatory biomarkers could reveal a "signature of disease" that can serve as a highly accurate method to assess for the presence of coronary atherosclerosis. We simultaneously measured serum levels of seven chemokines [CXCL10 (IP-10), CCL11 (eotaxin), CCL3 (MIP1
), CCL2 (MCP1), CCL8 (MCP2), CCL7 (MCP3), and CCL13 (MCP4)] in 48 subjects with clinically significant CAD ("cases") and 44 controls from the ADVANCE Study. We applied three classification algorithms to identify the combination of variables that would best predict case-control status and assessed the diagnostic performance of these models with receiver operating characteristic (ROC) curves. The serum levels of six chemokines were significantly higher in cases compared with controls (P < 0.05). All three classification algorithms entered three chemokines in their final model, and only logistic regression selected clinical variables. Logistic regression produced the highest ROC of the three algorithms (AUC = 0.95; SE = 0.03), which was markedly better than the AUC for the logistic regression model of traditional risk factors of CAD without (AUC = 0.67; SE = 0.06) or with CRP (AUC = 0.68; SE = 0.06). A combination of serum levels of multiple chemokines identifies subjects with clinically significant atherosclerotic heart disease with a very high degree of accuracy. These results need to be replicated in larger cross-sectional studies and their prognostic value explored.
coronary artery disease; multimarker; biomarkers; atherosclerosis; protein microarray; proteomic; inflammation; chemokines
Copyright © 2007 by the American Physiological Society.