BACKGROUND: In patients with coronary artery disease (CAD), a well grown collateral circulation has been shown to be important. The aim of this prospective study using peripheral blood monocytes was to identify marker genes for an extensively grown coronary collateral circulation. METHODS: Collateral flow index (CFI) was obtained invasively by angioplasty pressure sensor guidewire in 160 individuals (110 patients with CAD, and 50 individuals without CAD). RNA was extracted from monocytes followed by microarray-based gene-expression analysis. 76 selected genes were analysed by real-time polymerase chain reaction (PCR). A receiver operating characteristics analysis based on differential gene expression was then performed to separate individuals with poor (CFI<0.21) and well-developed collaterals (CFI>or=0.21) Thereafter, the influence of the chemokine MCP-1 on the expression of six selected genes was tested by PCR. RESULTS: The expression of 203 genes significantly correlated with CFI (p = 0.000002-0.00267) in patients with CAD and 56 genes in individuals without CAD (p = 00079-0.0430). Biological pathway analysis revealed 76 of those genes belonging to four different pathways: angiogenesis, integrin-, platelet-derived growth factor-, and transforming growth factor beta-signalling. Three genes in each subgroup differentiated with high specificity among individuals with low and high CFI (>or=0.21). Two out of these genes showed pronounced differential expression between the two groups after cell stimulation with MCP-1. CONCLUSIONS: Genetic factors play a role in the formation and the preformation of the coronary collateral circulation. Gene expression analysis in peripheral blood monocytes can be used for non-invasive differentiation between individuals with poorly and with well grown collaterals. MCP-1 can influence the arteriogenic potential of monocytes.
BACKGROUND: In patients with coronary artery disease (CAD), a well grown collateral circulation has been shown to be important. The aim of this prospective study using peripheral blood monocytes was to identify marker genes for an extensively grown coronary collateral circulation. METHODS: Collateral flow index (CFI) was obtained invasively by angioplasty pressure sensor guidewire in 160 individuals (110 patients with CAD, and 50 individuals without CAD). RNA was extracted from monocytes followed by microarray-based gene-expression analysis. 76 selected genes were analysed by real-time polymerase chain reaction (PCR). A receiver operating characteristics analysis based on differential gene expression was then performed to separate individuals with poor (CFI<0.21) and well-developed collaterals (CFI>or=0.21) Thereafter, the influence of the chemokine MCP-1 on the expression of six selected genes was tested by PCR. RESULTS: The expression of 203 genes significantly correlated with CFI (p = 0.000002-0.00267) in patients with CAD and 56 genes in individuals without CAD (p = 00079-0.0430). Biological pathway analysis revealed 76 of those genes belonging to four different pathways: angiogenesis, integrin-, platelet-derived growth factor-, and transforming growth factor beta-signalling. Three genes in each subgroup differentiated with high specificity among individuals with low and high CFI (>or=0.21). Two out of these genes showed pronounced differential expression between the two groups after cell stimulation with MCP-1. CONCLUSIONS: Genetic factors play a role in the formation and the preformation of the coronary collateral circulation. Gene expression analysis in peripheral blood monocytes can be used for non-invasive differentiation between individuals with poorly and with well grown collaterals. MCP-1 can influence the arteriogenic potential of monocytes.
Authors: Liam Bourke; Garry A Tew; Marta Milo; David C Crossman; John M Saxton; Timothy J A Chico Journal: BMC Public Health Date: 2010-10-18 Impact factor: 3.295
Authors: Kim E Jie; Karien van der Putten; Sebastiaan Wesseling; Jaap A Joles; Marloes W Bergevoet; Floor Pepers-de Kort; Pieter A Doevendans; Yutaka Yasui; Qi Liu; Marianne C Verhaar; Carlo A Gaillard; Branko Braam Journal: PLoS One Date: 2012-09-05 Impact factor: 3.240
Authors: Pascal Meier; Stephan H Schirmer; Alexandra J Lansky; Adam Timmis; Bertram Pitt; Christian Seiler Journal: BMC Med Date: 2013-06-04 Impact factor: 8.775
Authors: Sebastian Grundmann; Stephan H Schirmer; Liesbeth H P Hekking; Jan Andries Post; Mihaela G Ionita; Daphne de Groot; Niels van Royen; Bernard van den Berg; Hans Vink; Martin Moser; Christoph Bode; Dominique de Kleijn; Gerard Pasterkamp; Jan J Piek; Imo E Hoefer Journal: J Cell Mol Med Date: 2009-03-06 Impact factor: 5.310