META - ANALYSIS

Reconstruction and functional analysis of altered molecular pathways in human atherosclerotic arteries .

Stefano Cagnin,#1,2 Michele Biscuola,#3 Cristina Patuzzo,3 Elisabetta Trabetti,3 Alessandra Pasquali,3 Paolo Laveder,2 Giuseppe Faggian,4 Mauro Iafrancesco,4 Alessandro Mazzucco,4 Pier Franco Pignatti, 3 and Gerolamo Lanfranchi 1,2 1CRIBI Biotechnology Centre, University of Padova, Padova, Italy 2Department of Biology, University of Padova, Padova, Italy 3Department of Mother and Child, Biology and Genetics, Section of Biology and Genetics, University of Verona, Verona, Italy 4Division of Cardiac Surgery, University of Verona Medical School, Verona, Italy Corresponding author. #Contributed equally. .

Abstract .

Background .

Atherosclerosis affects aorta, coronary, carotid, and iliac arteries most frequently than any other body vessel. There may be common molecular pathways sustaining this process. Plaque presence and diffusion is revealed by circulating factors that can mediate systemic reaction leading to plaque rupture and thrombosis. .

Results .

We used DNA microarrays and meta-analysis to study how the presence of calcified plaque modifies human coronary and carotid gene expression. We identified a series of potential human atherogenic genes that are integrated in functional networks involved in atherosclerosis. Caveolae and JAK/STAT pathways, and S100A9/S100A8 interacting proteins are certainly involved in the development of vascular disease. We found that the system of caveolae is directly connected with genes that respond to hormone receptors, and indirectly with the apoptosis pathway.Cytokines, chemokines and growth factors released in the blood flux were investigated in parallel. High levels of RANTES, IL-1ra, MIP-1alpha, MIP-1beta, IL-2, IL-4, IL-5, IL-6, IL-7, IL-17, PDGF-BB, VEGF and IFN-gamma were found in plasma of atherosclerotic patients and might also be integrated in the molecular networks underlying atherosclerotic modifications of these vessels. .

Conclusion .

The pattern of cytokine and S100A9/S100A8 up-regulation characterizes atherosclerosis as a proinflammatory disorder. Activation of the JAK/STAT pathway is confirmed by the up-regulation of IL-6, STAT1, ISGF3G and IL10RA genes in coronary and carotid plaques. The functional network constructed in our research is an evidence of the central role of STAT protein and the caveolae system to contribute to preserve the plaque. Moreover, Cav-1 is involved in SMC differentiation and dyslipidemia confirming the importance of lipid homeostasis in the atherosclerotic phenotype. .

Meta-analysis .

To compare our expression data with published expression profiles, we applied a meta-analysis approach to expression datasets of 8 carotid samples taken from Array Express database (E-MEXP-268) and 6 coronary controls retrieved from Gene Expression Omnibus (GSE3526, GSE7307), using row data only[46]. Normal coronary profiles were used as common reference for carotid plaque expression data, since no important differences emerged from the comparison between normal carotid and normal coronary expression profiles (data not shown). Moreover, since the characteristics of peripheral arteries, like thickness of intima-media layers of carotid wall, are used as surrogate markers for coronary atherosclerosis, we decided to compare directly gene expression of these two vessels. However, since it is known that atherosclerosis show some rate of artery-dependent patterns[47], it should be clarified that the comparison of diseased carotids to normal coronaries could result in some grade of under- or overestimation of differences in gene expression. Briefly, data have been normalized using the invariant probe set normalization method[48], implemented in d-chip software, and matched for the common probe set between the different platforms used in the experiments. Differentially expressed genes were calculated from normalized values by applying the fold change and t-test methods.The lists of genes differentially expressed in atherosclerotic coronaries and carotids were compared using the identification of Entrez Gene database and matching entries were classified as "atherogenes" (see the Results). Coronary specific, carotid specific and common differentially expressed genes have been functionally classified using Gene Ontology criteria as implemented in DAVID[49] and used to build networks of functionally correlated genes/protein by Cytoscape[50]. Cytoscape is an open source bioinformatic platform for visualizing molecular interaction networks and biological pathways. To retrieve interactions between differentially expressed genes and to construct the larger general interaction network (Figure ​(Figure4a),4a), we used the Biomolecular Interaction Network Database (BIND) http://bond.unleashedinformatics.com/index.jsp?pg=0, that is a collection of records documenting protein interaction, molecular complexes and pathways. We also made use of the Biological General Repository for Interaction Datasets (BioGRID) database http://www.thebiogrid.org[51] developed at the University of Toronto (Canada) to house and distribute collections of proteins and genetic interactions from major model organisms. This larger network was used to identify high interconnected nodes with the MCODE[52] Cytoscape plug-in. MCODE is an algorithm that allows the finding of clusters in interaction networks to evidence protein complexes or related pathways. Parameters used for MCODE were: Score 1.80, Nodes 76 and 170 Edges. The MCODE defines score as the product of the complex sub-graph density and the number of vertices in the complex sub-graph. With this process MCODE assigns higher values to large node and dense complexes. The inferred sub-network displayed in Figure ​Figure4b4b was that classified with the highest score.Functional classification of genes connected in the larger network (Figure ​(Figure4a)4a) was done according to Gene Ontology (GO) using the Cytoscape plug-in BINGO[53]. This is a bioinformatic tool able to determine which GO categories are statistically overrepresented in a set of genes or a sub-graph of a biological network. We used a hypergeometric test and the Benjamini and Hochberg False Discovery rate (FDR) correction with 0.05 level of significance. The results are plotted in the additional Figure S2 (see Additional file 2, Figure S2).Quantitative real-time PCR Equal aliquots of aRNA from each sample were mixed and 400 ng of this pool were used for first strand cDNA synthesis using Superscript II (Invitrogen). Four independent reactions were carried out, pooled and used for qRT-PCR with SYBR green. Each qRT-PCR was performed in triplicate using the 7500 Real Time PCR System (Applied Biosystems), and analyzed according the Pfaffl method[54]. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glucuronidase beta (GUSB), TATA box binding protein (TBP) and hypoxanthine phosphoribosyltransferase 1 (HPRT1) were used as reference transcripts. Sequences of the primers used for qRT-PCR of various mRNA are reported in the additional Table S1 (see Additional file 1, Table S1). .

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