Published online before print February 19, 2009, doi: 10.1161/STROKEAHA.108.532036
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(Stroke. 2009;40:1252.)
© 2009 American Heart Association, Inc.
Original Contributions |
Genomics of Human Intracranial Aneurysm Wall
From the Department of Neurological Surgery (C.S., I.A.A., Z.A.H., R.S., C.C.G., M.B., H.H.B., B.R.B.), Center for Genetic Medicine (N.J., M.B.), and Robert H. Lurie Comprehensive Cancer Center (S.L., P.D., M.B.), Feinberg School of Medicine, Northwestern University, Chicago, Ill, and Division of Neurosurgery (C.S., I.A.A., R.S.), Northshore University HealthSystem, Evanston, Ill.
Correspondence to Bernard R. Bendok, MD, Department of Neurological Surgery, 676 N St Clair, Suite 2210, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611. E-mail BBendok{at}nmff.org
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Abstract |
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Background and Purpose— The pathogenesis of intracranial aneurysms (IAs) remains elusive. Most studies have focused on individual genes, or a few interrelated genes or products, at a time in human IA. However, a broad view of pathologic mechanisms has not been investigated by identifying pathogenic genes and their interaction in networks. Our study aimed to analyze global gene expression patterns in the IA wall.
Methods— To our knowledge, our group was the first to perform Illumina microarray analysis on human IA via comparison of aneurysm wall and superficial temporal artery tissues from 6 consecutive patients. We adopted stringent statistical criteria to the individual genes; genes with a false discovery rate <0.01 and >2-fold change were selected as differentially expressed. To identify the overrepresented biologic pathways with the differentially expressed genes, we performed hypergeometric testing of the genes selected by relaxed criteria of P<0.01 and fold change >1.5.
Results— There are 326 distinct differentially expressed genes between IA and superficial temporal artery tissues (>2-fold change) with a false discovery rate <0.01. Analysis of the Kyoto Encyclopedia of Genes and Genomes pathways revealed the most impacted functional pathways: focal adhesion, extracellular matrix receptor interaction, and cell communication. Analysis of the Gene Ontology also supported the involvement of another 2 potentially important pathways: inflammatory response and apoptosis.
Conclusions— The differentially expressed genes in the aneurysm wall may shed light on aneurysm pathobiology and provide novel targets for therapeutic intervention. These data will help generate hypotheses for future studies.
Key Words: intracranial aneurysms • cerebral aneurysms • acute stroke • microarray • gene expression
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Introduction |
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Subarachnoid hemorrhage (SAH) resulting from rupture of intracranial aneurysms (IAs) is an important cause of hemorrhagic stroke. The prevalence of IA ranges from 1% to 6% of the world’s population.1 It is estimated that 30 000 Americans are stricken with aneurysmal SAH each year.1 Despite the high mortality and morbidity of SAH, relatively little is understood with respect to IA molecular pathology and pathogenesis. Despite a growing body of literature on the genetics of individuals harboring IA, very little attention has been given to biologic processes in the aneurysm wall itself.
Genetic factors are thought to play an important role in the pathogenesis of IA. Most studies have focused on individual genes, or a few interrelated genes or products, at a time in human IA.2 IA is characteristic of multifactorial diseases with multiple interacting molecular pathways. With the advent of gene microarray technology, a study of gene expression in the IA wall from almost the entire human genome is now possible.3 In a disease that is biologically complex and multifactorial, this approach allows for a broad view of pathologic mechanisms by identifying pathogenic genes and their interaction in networks. This study aimed to analyze global gene expression patterns in the IA wall in comparison with superficial temporal artery (STA) tissue. To our knowledge, our group is the first to perform microarray analysis on human IA owing to the challenge of obtaining IA wall samples and RNA degradation. Our goal was to identify genes and pathways involved in human IA pathobiology.
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Materials and Methods |
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Patient Samples
The research was approved by our institution’s institutional review board. Clinical and lesion features of 6 patients with IA were categorized (Table 1). A section of the aneurysmal dome and paired STA from the same patient were harvested from patients who consented to participate in the study and who undergoing aneurysm clipping at Northwestern Memorial Hospital. The aneurysm and STA tissues were then rinsed with cold phosphate-buffered saline and immediately placed into precooled Rnase-free tubes. The tubes containing the tissues were immersed in dry ice mixed with 100% ethanol. The frozen tissues were then stored at –80°C until RNA extraction.
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RNA Isolation and Microarray Analysis
Each tissue sample was homogenized with zirconia/silica beads in a BeadBeater machine (BioSpec Products, Inc). After tissue homogenization, RNA was isolated and purified with an RNeasy mini kit with DNase I digestion on the column (Qiagen, Valencia, Calif). The quantity of RNA was measured with NanoDrop ND-1000 spectrophotometer from Thermofisher, and the quality was checked by the Agilent 2100 bioanalyzer (Agilent Technologies). The extracted total RNA was of high quality (RNA integrity number =6.9 to 8.7).
Illumina Human WG6-v2 Microarray Analysis
Biotin-labeled cRNA was generated from high-quality total RNA with the Illumina TotalPrep RNA amplification kit (Ambion). In brief, 50 ng of total RNA was reversely transcribed with an oligo(dT) primer bearing a T7 promoter. The first-strand cDNA was used to make the second strand. The purified second-strand cDNA, along with biotin UTPs, was then used to generate biotinylated, antisense RNA of each mRNA in an in vitro transcription reaction. The size distribution profile for the labeled cRNA samples was evaluated by Bioanalyzer. After RNA labeling, 1.5 µg of purified, labeled cRNA from each sample was hybridized at 55°C overnight with a Sentrix Human-6 v2 expression Illumina Beadchip containing 43 148 transcripts. The beadchip was washed the following day. A signal was developed with Streptavidin-Cy3, and each chip was scanned with an Illumina BeadArray Reader.
Statistical Analysis
The preprocessing of Illumina data was performed with a Bioconductor lumi package with default settings.4 To best utilize the unique features of Illumina BeadArray technology, the data were preprocessed with a variance-stabilizing transformation method 5 followed by quantile normalization. Probes with all samples "absent" (lower or near background levels) were removed from further analysis. To identify the differentially expressed genes in aneurysm versus control tissue, we applied routines implemented in the limma package6 to fit linear models to the normalized expression values. The variance used in the t-score calculation was corrected by an empirical Bayesian method6 for better estimation under a small sample size. To control the effects of multiple testing, we adopted the stringent statistical criterion of selecting the interesting individual gene from almost the whole genome: the false discovery rate (FDR)7 was limited to be <0.01, and only the probes with fold-change higher than 2 were selected as differentially expressed. To identify the overrepresented biologic pathways with the differentially expressed genes, we did a hypergeometric test based on genes selected by a relaxed criteria of P <0.01 and fold change >1.5. After the hypergeometric test, we also included a few genes with fold change >1.5 and P <0.05 in the pathways to avoid ignoring subtly expressed genes in a limited number of genes in identified overrepresented pathways.
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Results |
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Our study assessed the genetic profiles of 6 consecutive, surgically excised human IA specimens: 3 were ruptured and 3 were unruptured. A total of 17 524 distinct genes from 43 148 transcripts passed the expression criteria (filter assessment based on "absent" count) in both aneurysm and STA groups. Sample relations were overviewed by using a multidimensional scaling plot. Multidimensional scaling is a set of statistical visualization techniques used for exploring the similarities or dissimilarities of the data. Distinct separation was demonstrated between the aneurysm group and control group (STA) along dimension 1. This indicated that there were differentially expressed genes in the aneurysm versus the control group. Meanwhile, we also observed separation between ruptured (red) and unruptured (black) aneurysms along dimension 2. This indicated that differential gene expression may exist between ruptured and unruptured aneurysms (supplemental Figure I, available online at http://stroke.ahajournals.org). Our results revealed 326 distinct differentially expressed genes from almost the whole genome (with a minimum 2-fold change and an FDR set at <0.01) between aneurysm and STA tissues (supplemental Table I
, part I, available online at http://stroke.ahajournals.org). There were more genes with increased expression (172) than with decreased expression (154) in aneurysm tissue. When we focused on large fold changes in gene expression between aneurysm and control STA samples (
8-fold change in gene expression), 6 functional annotation groups known to have the most pathobiologic relevance in terms of aneurysm development and rupture, according to previously published reports, were identified: (1) collagens, (2) cell communication, (3) angiogenesis, (4) inflammation, (5) apoptosis, and (6) cytoskeleton negative regulation (data not shown). Additional analysis of the 326 distinct differentially expressed genes for enrichment in the Gene Ontology (GO) database revealed that these genes were involved in several biologic/molecular processes, including organ and system development, cell-cell adhesion, actin cytoskeleton organization and biogenesis, actin binding, cytoskeletal protein binding, collagen, extracellular matrix (ECM), adherens junction, and actin cytoskeleton; in the Kyoto Encyclopedia of Genes and Genomes (KEGG), the most impacted pathways were focal adhesion, ECM-receptor interaction, and cell communication (data not shown).
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To better understand the biologic roles of the differentially expressed genes, we also performed a functional analysis of those genes. In this regard, our interest was to find the functional categories instead of individual genes, and consequently the FDR of individual genes was no longer a major concern. Therefore, we selected differentially expressed genes in certain functional categories based on both a value of P<0.01 and a fold change >1.5. Hypergeometric testing of these selected genes was applied to identify the differentially-represented function categories, which included both GO and KEGG pathways. Besides the aforementioned 3 pathways of focal adhesion (KEGG ID: hsa04510, P=0.000026, FDR=0.0029), ECM-receptor interaction (KEGG ID: hsa04512, P=0.00014, FDR=0.008), and cell communication (KEGG ID: hsa01430, P=0.002, FDR=0.05) in KEGG pathways, we also selected enriched functional pathways in GO, including inflammatory response (GO: 0006954, P=0.0002, FDR=0.014) and apoptosis (GO: 0006915, P=0.000093, FDR=0.0098). Subsequently, we chose to focus on these 5 pathways, as they appeared to be of most relevance according to previously published findings on cerebral aneurysm biology. Additionally, subtly expressed genes could not be ignored when testing in the context of biologic processes, as the greater change in gene expression is not always correlated with the greater pathologic change. Therefore, we also included a few genes with fold change >1.5 and P<0.05 in the identified functional pathways. To better interpret the genes in these pathways, we also performed a network analysis and visualized the networks with the use of Ingenuity software (Ingenuity Systems, Inc). The Figure gives an example of the inflammatory pathway. We will describe these pathways in more detail in the following sections.
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Our data showed that 58 differentially expressed genes were related to inflammatory and immune response (the Figure and supplemental Table I
, part II). Of those, 40 inflammation-related genes were upregulated and 18 were downregulated. Eight genes were related to the complement system, 5 genes to the 5-lipoxygenase (5-LO) pathway, 22 to cytokines and chemokines, and 5 to macrophages and lymphocyte markers (Table 2). In the apoptosis pathway, 129 genes were differentially expressed. Of those, 78 apoptosis-related genes were upregulated and 51 were downregulated. There were many differentially expressed genes associated with the intrinsic pathway of apoptosis (mitochondrial activation) and the extrinsic direct signal transduction of the apoptosis-tumor necrosis factor (TNF)–induced model (Table 3). In the focal adhesion pathway, our results demonstrated that 53 genes were significantly differentially expressed. Of those, 28 focal adhesion–related genes were upregulated and 25 were downregulated. Genes related to integrins (6) and actin regulation (18) were differentially expressed in aneurysms (Table 4). In the ECM-receptor interaction pathway, our data showed that 39 genes were significantly differentially expressed. Of those, 28 genes were upregulated and 11 were downregulated. There were 19 differentially expressed genes related to 7 types of ECM (such as collagens, laminins, etc), and 6 genes related to integrins in aneurysms (Table 5, part I). In the cell communication pathway, our findings demonstrated 38 significantly differentially expressed genes. Of those, 22 cell communication–related genes were upregulated and 16 were downregulated. There were 18 differentially expressed genes related to regulation of actin and intermediate filaments in aneurysms (Table 5, part II).
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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A holistic, data-driven approach with microarray analysis provides us with a broad view of the mechanisms of IA by identifying pathogenic genes and characterizing their interrelation in networks. To put the microarray data in perspective, we selected 5 functional annotation pathways: inflammatory response, apoptosis, focal adhesion, ECM-receptor interaction, and cell communication. Consequently, we were able to select potential gene candidates of interest.
In the inflammatory response pathway, our microarray data showed that 5 differentially expressed genes in aneurysm walls were related to macrophages and lymphocytes. These cells have been implicated in the progression and rupture of IAs.8 Our results also demonstrated the differential expression of 8 genes related to classic and alternative complement pathways and suggested a modified equilibrium between complement, its inhibitor, and its receptor. Complement activation has also been implicated in IA wall degeneration and rupture.9 Moreover, complement-activating immune complexes have been linked to the cerebral vasospasm after rupture of saccular aneurysms.10 Interestingly, our data showed ALOX5 (5-LO), ALOX5AP (5-LO–activating protein [FLAP]), LTB4R (BTL1), Pla2g4a (cPLA2), and CCL3 to be upregulated in the aneurysm wall, indicating that the 5-LO pathway may be involved in the pathogenesis of IAs. The enzyme 5-LO is known to catalyze the conversion of arachidonic acid to leukotrienes (such as leukotriene B4) with the aid of the accessory protein FLAP.11 The 5-LO pathway has been implicated in the pathogenesis of atherosclerosis12 and aortic aneurysms.13 In fact, a 5-LO deficiency, along with diminished plasma CCL3, significantly attenuates abdominal aortic aneurysm (AAA) formation in mice.13 Furthermore, variants of ALOX5AP have implicated in the pathogenesis of both myocardial infarction and stroke.14 However, the 5-LO cascade has never been investigated in IA pathogenesis. Our study also showed 22 differentially expressed genes related to pro- and anti-inflammatory cytokines and chemokines, including transforming growth factor (TGF)-β1, TNF, interleukin (IL)-1ß, migration inhibitory factor (MIF), CXCR4, CXCL12, and CCL5. This might imply a role for a Th1/Th2 pro- and anti-inflammatory cytokine imbalance in cerebral aneurysm pathobiology, consistent with findings for AAAs.15 Cytokines and chemokines have been related to the pathogenesis of IAs. TGF-β1 and TNF-
were elevated in experimental and human IA walls.16,17 IL-1ß plays an important role in the progression of IA in IL-1ß–deficient mice.18 MIF has been associated with the pathogenesis of atherosclerosis and AAAs.19 MIF could interact with its functional chemokine receptor, CXCR4, and trigger chemotaxis of monocytes and T cells. MIF could also compete with cognate ligands for CXCR4, such as CXCL12.20 It remains to be determined whether MIF serves as a ligand for CXCR4 in IAs. On the other hand, the CXCR4/CXCL12 pairing has been critically involved in inflammatory conditions, such as rheumatoid arthritis, and it is often highly overexpressed in cancers.21 CXCR4 plays an essential role in vascularization, probably by regulating vascular branching and/or through remodeling processes in endothelial cells.22 CCL5/RANTES, a chemokine ligand, is crucial for CCR1-mediated arrest, but not for CCR5-mediated spreading/transmigration in flow or transendothelial chemotaxis of leukocytes.23 Moreover, the deposition and immobilization of platelet-derived CCL5/RANTES have been shown to trigger monocyte recruitment on activated aortic endothelium.24 Taken together, our data suggest that inflammatory cell infiltration, along with an inflammatory mediator imbalance, may contribute to the pathophysiology of aneurysm formation.
In the apoptosis pathway, our microarray data demonstrated that 129 differentially expressed genes were associated with the 2 main apoptotic pathways, intrinsic and extrinsic, in the aneurysm wall. Of those genes, we found increased expression of proapoptotic genes TNF, IL-1ß, FADD, Bid, and caspase-3 and decreased expression of the antiapoptotic gene Bcl-2 in IAs. It has been suggested that apoptosis is involved in aneurysmal development and rupture.25 Apoptosis of medial smooth muscle cells has been observed in human IAs.26 Endothelial apoptosis may also occur during cerebral vasospasm after SAH.27 Furthermore, the extrinsic apoptotic signaling pathway that involves TNF- and the downstream signaling molecule FADD seem to initiate vessel weakening and remodeling in human IAs.16 Moreover, both TNF-–mediated extrinsic and Bcl-2-mediated intrinsic apoptotic pathways induced apoptosis in a rabbit aneurysm model.28 These data, therefore, indicate that genes involved in both intrinsic and extrinsic apoptotic pathways may contribute to the pathogenesis of IAs.
In the focal adhesion pathway, our microarray data showed overexpression of integrin-V (ITGAV) and decreased expression of integrin-β4 (ITGB4). ITGAV is a regulator of angiogenesis, but its function as either proangiogenic or antiangiogenic is still controversial.29 In certain AAA cases, overexpression of ITGAV was noted.30 Nonetheless, ITGAV was downregulated in other AAA cases.31 ITGB4 was found to be overexpressed in rat IAs,32 whereas our data showed decreased expression of ITGB4. A possible explanation for this discrepancy may be the difference in species, stage of disease, and tissue bias selection. On a different note, we observed decreased expression of genes encoding linker proteins (signaling proteins) and genes encoding cytoskeletal proteins, an event that leads to the loss of cell/matrix interactions. This could induce a process of programmed cell death, or anoikis, which causes pathologic remodeling of cardiovascular tissues, including deendothelization and plaque rupture in atherosclerosis and smooth muscle cell disappearance in aneurysms.33 Therefore, it is suggested that a disruption in the expression of genes encoding integrins, signaling proteins, and cytoskeletal proteins in IA walls might be involved in the development of IAs.
In the ECM-receptor interaction pathway, our microarray analysis revealed genes related to different types of ECM to be differentially expressed. One such gene, secreted phosphoprotein-1 (SPP1), also known as osteopontin, was overexpressed. SPP1 could impair reendothelialization by interacting with ITGAV, contributing to restenosis and atherosclerosis.34 SPP1 also plays an important role in atherosclerosis and AAA formation in SPP1-deficient mice.35 SPP1 was upregulated in human AAAs and thoracic aortic aneurysms.36 Moreover, SPP1 was increasingly upregulated from 30- to 45-fold in swine carotid artery aneurysms.37 Our study is the first to provide evidence of SPP1 overexpression (35-fold increase) in human IAs. Indeed, ECM may be involved in the formation and growth of IAs.38 Recently, microarray data on rat aneurysm showed differential expression of ECM genes.39 It is possible that despite the altered genetic profiles of the ECM in aneurysm walls, as long as a new balance between ECM degradation and remodeling is restored, no rupture occurs. Once this balance is interrupted, the aneurysm might rupture. The ECM not only plays a structural role but also relays the extracellular signaling into intracellular signaling via integrins. It can be assumed that a disruption of regulation in both ECM and integrins in IA walls may be related to the mechanism of IA formation and/or rupture.
Our microarray data also showed differentially expressed genes related to cell communication; many of these genes overlap with genes in other pathways such as ECM and focal adhesion pathways. Lenk et al40 demonstrated that regulation of the actin cytoskeleton, focal adhesion, ECM-receptor, immune response, and inflammatory pathways was involved in the pathogenesis of AAAs. Cell communication has also been previously linked to the pathogenesis of AAAs.41
As evident herein, our microarray data suggest that inflammatory response, ECM-receptor interaction, focal adhesion, cell communication, and apoptotic pathways might all be involved in the pathogenesis of IAs. This might indicate shared pathogenic mechanisms between IAs, thoracic aortic aneurysms, and AAAs. In fact, Ruigrok et al42 recently identified 5 chromosomal regions that may include common genes for intracranial, thoracic aortic, and AA aneurysms.
The present study has several limitations. Most tissue samples harvested from the aneurysm wall came from lesions in a late stage of development, therefore resulting in sample bias. Lesions at an earlier stage might show a different gene expression pattern. In addition, the relatively small cohort might have diminished the statistical power of this study. STA as an internal control is yet another limitation. Nonetheless, the use of STA for similar experimental work has been previously established.43 Obtaining intracranial arteries from humans is difficult, and specimens from autopsies seldom have intact RNA. Other arteries that might be harvested during temporal or frontal lobectomies are not ideal controls either. Phenotypic heterogeneity (ruptured vs unruptured aneurysms) and morphological heterogeneity (different sites of aneurysms) of IAs might also have acted as limiting factors. Another drawback in this study is that the microarray data from aneurysms may reflect a mixture of a variety of cell homogenization in aneurysm walls and STA. Laser capture microdissection may circumvent this problem in the future.
Pathobiologic Significance and Future Directions
This study provides a comprehensive, global view of gene expression in IAs, and the pathway analysis sheds light on the pathogenesis of IAs. Our findings may provide a simple basis to interlink the various pathogenic mechanisms of IAs and provide novel targets for therapeutic intervention to prevent aneurysm formation, growth, or rupture. Laser capture microdissection and real-time polymerase chain reaction will be useful to evaluate the genetic profiles of the IA wall in future studies. Knockout mice of compelling candidate genes can also constitute an adjunctive approach for promoting establishment of new hypotheses, such as SPP135 and ALOX5.44 In addition, given the considerable inflammatory mediators and proteases produced by immunocompetent cells in IAs, the deletion of B cells, T cells, and macrophages in animal models could be another therapeutic approach. The concept of neutrophil depletion has been used to inhibit AAA development.45 A more detailed analysis of ruptured versus unruptured IAs is under way in our laboratory.
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Acknowledgments |
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We acknowledge Monika Rymsza, BS, of the Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, for editing assistance.
Sources of Funding
This work was supported in part by grants from the Erica Keeney Foundation (to B.R.B.) and the Eleanor Wood Prince Grant Initiative Project of the Woman’s Board of Northwestern Memorial Hospital (to B.R.B.).
Disclosures
None.
Received July 19, 2008; revision received August 27, 2008; accepted September 12, 2008.
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