The multi-ligand Receptor for AGE (RAGE) contributes to atherosclerosis in apolipoprotein (ApoE) null mice in both the non-diabetic and diabetic states. Previous studies using soluble RAGE, the extracellular ligand-binding domain of RAGE, or homozygous RAGE null mice showed that blockade or deletion of RAGE resulted in marked reduction in atherosclerotic lesion area and complexity compared to control animals. In parallel, significant down-regulation of inflammatory mediators and matrix metalloproteinases was evident in ApoE null mice aortas devoid of RAGE compared to those of ApoE null RAGE-expressing mice. Although these findings suggested that RAGE triggered pro-atherogenic mechanisms via regulation of inflammatory gene expression, these studies did not reveal the broader pathways by which RAGE contributed to atherosclerosis in ApoE null mice.
Therefore, we performed Affymetrix gene expression arrays on aortas of non-diabetic and diabetic ApoE null mice expressing RAGE or devoid of RAGE at nine weeks of age, as this reflected a time point at which frank atherosclerotic lesions were not yet present, but, that we would be able to identify the genes likely involved in diabetes- and RAGE-dependent atherogenesis. The comparisons were as follows: 1. diabetic ApoE null relative to non-diabetic ApoE null; 2. non-diabetic ApoE null / RAGE null relative to non-diabetic ApoE null; 3. diabetic ApoE null / RAGE null relative to non-diabetic ApoE null / RAGE null; and 4. diabetic ApoE null / RAGE null relative to diabetic ApoE null aorta.
Our data reveal that there is very little overlap of the genes which are differentially expressed both in the onset of diabetes in ApoE null mice, and in the effect of RAGE deletion in diabetic ApoE null mice. We next performed a Pathway-Express analysis to determine the pathways that were most associated with the onset of diabetes in ApoE null mice and the effect of RAGE gene deletion in diabetic ApoE null mice. Rigorous statistical analysis was undertaken and revealed that the transforming growth factor-β pathway (tgf-β) and focal adhesion pathways might be expected to play a significant role in both the mechanism by which diabetes facilitates the formation of atherosclerotic plaques in ApoE null mice, and the mechanism by which deletion of RAGE ameliorates this effect. We focused on three genes of the tgf-β family which were found to be up-regulated in diabetic vs. non-diabetic ApoE null aorta, and which were reduced by deletion of RAGE. These included: thrombospondin1 (Thbs1), transforming growth factor-β2 (tgf-β2) and rho-associated kinase (ROCK1). Real-time quantitative polymerase chain reaction and Western blotting experiments were performed, as well as ROCK1 activity assays in mouse aorta, and validated the findings of the Affymetrix gene array. Further, confocal microscopy revealed that a principal cell type in the ApoE null aorta expressing these factors was the vascular smooth muscle cell. Our data suggest the novel finding that the observed reduction of accelerated atherosclerosis in diabetic ApoE null / RAGE null vs. diabetic ApoE null mice occurs, all or in part, through the ROCK1 branch of the TGF-β pathway. We have inferred a detailed mechanism for this process.
Taken together, these data suggest that suppression of ROCK1 activity in the atherosclerosis-vulnerable vessel wall, especially in diabetes, but in non-diabetes as well, may underlie the beneficial effects of RAGE antagonism and genetic deletion in murine models. These findings highlight logical and novel targets for therapeutic intervention in cardiovascular disease and diabetes.
Overall design: 1. diabetic ApoE null relative to non-diabetic ApoE null; 2. non-diabetic ApoE null / RAGE null relative to non-diabetic ApoE null; 3. diabetic ApoE null / RAGE null relative to non-diabetic ApoE null / RAGE null; and 4. diabetic ApoE null / RAGE null relative to diabetic ApoE null aorta.
There were 4 mice in each group initially. However there are only 3 non-diabetic ApoE null / RAGE null mice in the final experimental sample in group 3 due to a failure to generate cRNA from that sample. All samples were normalized to remove chip-dependent regularities using the RMA method. Chips and controls at each combination of genotype and disease sate were normalized together. The statistical significance of differential expression was calculated using the empirical Bayesian LIMMA (LInear Model for MicroArrays) method A cut-off B>0 was used for the statistical significance of gene expression.
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