Physiological Genomics of Human Arteries

Abstract

Background-Previous genomic studies with human tissues have compared differential gene expression between 2 conditions (ie, normal versus diseased) to identify altered gene expression in a binary manner; however, a potentially more informative approach is to correlate the levels of gene expression with quantitative physiological parameters. Methods and Results-In this study, we have used this approach to examine genes whose expression correlates with arterial stiffness in human aortic specimens. Our data identify 2 distinct groups of genes, those associated with cell signaling and those associated with the mechanical regulation of vascular structure (cytoskeletal-cell membraneextracellular matrix). Although previous studies have concentrated on the contribution of the latter group toward arterial stiffness, our data suggest that changes in expression of signaling molecules play an equally important role. Alterations in the profiles of signaling molecules could be involved in the regulation of cell cytoskeletal organization, cell-matrix interactions, or the contractile state of the cell. Conclusion-Although the influence of smooth muscle contraction/relaxation on arterial stiffness could be controversial, our provocative data would suggest that further studies on this subject are indicated.

Genome-Wide Expression Studies of Atherosclerosis

“…To assess the design, we scored the published studies based on following parameters: (1) 20 or after macroscopic inspection. 16,22 However, a detailed microscopic characterization of human samples has only been given in 2 studies.…”

“…Finally, our analysis reveals that data from only 3 expression studies expression are available in a public repository for microarray data (GEO data sets GSE1560, 9 GSE420, 20 and GSE2143 21 ). Even more striking, GSE1560 contains the expression data of only two-thirds of the experimental groups (ie, for all C3H/HeJ and C57BL/6 *groups, but not of the apolipoprotein E Ϫ/Ϫtm1Unc groups).…”

“…However, most of these studies aimed to identify the expression level of individual genes, and not pathways. 18 -20 In these studies, GO analysis suggested that the differentially expressed genes were involved in inflammation, 19,21,22 cell turnover, 19,21,22 matrix degradation, 18,19 lipid metabolism, 18,19 coding for matrix proteins, 20 or originated from SMC proliferation and dedifferentiation. 21 Thus, to date, gene expression studies have merely validated the differential expression of genes and pathways known to be involved in atherosclerosis, [42][43][44][45] and have yet to fully exploit the power and possibilities of identifying novel players (and eventually novel pathways) underlying atherosclerosis.…”

“…50,51 A major bottleneck in analyzing these studies was the lack of publicly available data sets. Expression data from only 3 of 20 gene expression studies 9,20,21 are deposited in a public repository for microarray data (GEO data sets GSE1560, GSE420, and GSE2143). As mentioned in the section entitled "Key Features of Gene Expression Studies in Atherosclerosis," GSE420 is incomplete and GSE2143 does not include a clear description of the samples.…”

“…In contrast to the murine data set that indicates an upregulation of CCL2 throughout plaque progression, CCL2 was downregulated in coronary arteries from patients with unstable angina versus stable angina 17 and was not differentially expressed according to the degree of aortic stiffness. 20 However, this comparison is hampered by the fact that plaque instability and aortic stiffness in humans does not necessarily reflect the same molecular processes as plaque progression in mice. CCL3 was mentioned in the list of genes associated with disease burden, 22 but neither quantitative nor qualitative details were given.…”