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Recent studies suggest the presence of both “classically activated” M1 and “alternatively activated” M2 macrophages in human atherosclerotic tissue, yet due to the lack of validated markers the reported localization patterns of these macrophage phenotypes within plaques are ambiguous. In the present study, we searched for markers that indisputably can identify differentiated M1 and M2 macrophages independently of stimuli that affect the activation status of the two subpopulations. We used these validated markers to assess the presence of M1 and M2 macrophages in different zones of human carotid artery atherosclerotic plaques obtained from 12 patients. Using microarray and qPCR technology we show that the frequently used macrophage subpopulation markers MCP-1 and CD206 do not discriminate between M1 and M2 macrophages. However, we confirm the subtype specificity of the classical M2 marker CD163 and we report that the genes INHBA and DSP (both M1) and SEPP1 and MARCKS (both M2) are highly suitable for macrophage phenotyping. mRNA expression of the pan-macrophage marker CD68 in the shoulder zones of the plaques and in adjacent tissue segments correlated positively with mRNA expression levels of SEPP1, MARCKS and CD163 (r=0.86, 0.94 and 0.96, and r= 0.86, 0.98 and 0.69, respectively) but not with the expression of the M1 markers DSP and INHBA. In contrast, mRNA expression of CD68 in the core of the plaques correlated positively with expression of DSP and INHBA (r=0.73 and 0.49) but not with SEPP1, MARCKS and CD163. These findings suggest that M1 macrophages predominate in the core of human carotid atherosclerotic plaques while M2 macrophages prevail at the periphery of the plaque. Keywords: Expression profiling by array Monocytes from healthy volunteers were differentiated into M1 and M2 macrophages by incubation with granulocyte-macrophage colony-stimulating factor (GM-CSF) or macrophage colony-stimulating factor (M-CSF), respectively. After 5 days cells were exposed to oxidized LDL. Total RNA was isolated and subjected to gene expression profiling.

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