11ß-HSD1 inhibition reduces atherosclerosis in mice by altering proinflammatory gene expression in the vasculature.

11ß-Hydroxysteroid dehydrogenase type 1 (11ß-HSD1) is implicated in the etiology of metabolic syndrome. We previously showed that pharmacological inhibition of 11ß-HSD1 ameliorated multiple facets of metabolic syndrome and attenuated atherosclerosis in ApoE-/- mice. However, the molecular mechanism underlying the atheroprotective effect was not clear. In this study, we tested whether and how 11ß-HSD1 inhibition affects vascular inflammation, a major culprit for atherosclerosis and its associated complications. ApoE-/- mice were treated with an 11ß-HSD1 inhibitor for various periods of time. Plasma lipids and aortic cholesterol accumulation were quantified. Several microarray studies were carried out to examine the effect of 11ß-HSD1 inhibition on gene expression in atherosclerotic tissues. Our data suggest 11ß-HSD1 inhibition can directly modulate atherosclerotic plaques and attenuate atherosclerosis independently of lipid lowering effects. We identified immune response genes as the category of mRNA most significantly suppressed by 11ß-HSD1 inhibition. This anti-inflammatory effect was further confirmed in plaque macrophages and smooth muscle cells procured by laser capture microdissection. These findings in the vascular wall were corroborated by reduction in circulating MCP1 levels after 11ß-HSD1 inhibition. Taken together, our data suggest 11ß-HSD1 inhibition regulates proinflammatory gene expression in atherosclerotic tissues of ApoE-/- mice, and this effect may contribute to the attenuation of atherosclerosis in these animals.

Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

Identification and validation of genes affecting aortic lesions in mice.

Atherosclerosis represents the most significant risk factor for coronary artery disease (CAD), the leading cause of death in developed countries. To better understand the pathogenesis of atherosclerosis, we applied a likeli-hood-based model selection method to infer gene-disease causality relationships for the aortic lesion trait in a segregating mouse population demonstrating a spectrum of susceptibility to developing atherosclerotic lesions. We identified 292 genes that tested causal for aortic lesions from liver and adipose tissues of these mice, and we experimentally validated one of these candidate causal genes, complement component 3a receptor 1 (C3ar1), using a knockout mouse model. We also found that genes identified by this method overlapped with genes progressively regulated in the aortic arches of 2 mouse models of atherosclerosis during atherosclerotic lesion development. By comparing our gene set with findings from public human genome-wide association studies (GWAS) of CAD and related traits, we found that 5 genes identified by our study overlapped with published studies in humans in which they were identified as risk factors for multiple atherosclerosis-related pathologies, including myocardial infarction, serum uric acid levels, mean platelet volume, aortic root size, and heart failure. Candidate causal genes were also found to be enriched with CAD risk polymorphisms identified by the Wellcome Trust Case Control Consortium (WTCCC). Our findings therefore validate the ability of causality testing procedures to provide insights into the mechanisms underlying atherosclerosis development.

Integrated genomic and proteomic analyses of gene expression in Mammalian cells.

Using DNA microarrays together with quantitative proteomic techniques (ICAT reagents, two-dimensional DIGE, and MS), we evaluated the correlation of mRNA and protein levels in two hematopoietic cell lines representing distinct stages of myeloid differentiation, as well as in the livers of mice treated for different periods of time with three different peroxisome proliferative activated receptor agonists. We observe that the differential expression of mRNA (up or down) can capture at most 40% of the variation of protein expression. Although the overall pattern of protein expression is similar to that of mRNA expression, the incongruent expression between mRNAs and proteins emphasize the importance of posttranscriptional regulatory mechanisms in cellular development or perturbation that can be unveiled only through integrated analyses of both proteins and mRNAs.