Whole genome expression analysis within the angiotensin II-apolipoprotein E deficient mouse model of abdominal aortic aneurysm
© Rush et al; licensee BioMed Central Ltd. 2009
Received: 04 September 2008
Accepted: 06 July 2009
Published: 06 July 2009
An animal model commonly used to investigate pathways and potential therapeutic interventions relevant to abdominal aortic aneurysm (AAA) involves subcutaneous infusion of angiotensin II within the apolipoprotein E deficient mouse. The aim of this study was to investigate genes differentially expressed in aneurysms forming within this mouse model in order to assess the relevance of this model to human AAA.
Using microarrays we identified genes relevant to aneurysm formation within apolipoprotein E deficient mice. Firstly we investigated genes differentially expressed in the aneurysm prone segment of the suprarenal aorta in these mice. Secondly we investigated genes that were differentially expressed in the aortas of mice developing aneurysms relative to those that did not develop aneurysms in response to angiotensin II infusion. Our findings suggest that a host of inflammation and extracellular matrix remodelling pathways are upregulated within the aorta in mice developing aneurysms. Kyoto Encyclopedia of Genes and Genome categories enriched in the aortas of mice with aneurysms included cytokine-cytokine receptor interaction, leukocyte transendothelial migration, natural killer cell mediated cytotoxicity and hematopoietic cell lineage. Genes associated with extracellular matrix remodelling, such as a range of matrix metalloproteinases were also differentially expressed in relation to aneurysm formation.
This study is the first report describing whole genome expression arrays in the apolipoprotein E deficient mice in relation to aneurysm formation. The findings suggest that the pathways believed to be critical in human AAA are also relevant to aneurysm formation in this mouse model. The findings therefore support the value of this model to investigate interventions and mechanisms of human AAA.
Summary of the included studies.
Paired supra and infrarenal aortas
Codelink mouse whole genome bioarray (36227 genes)
Differentially expressed between AAA prone supra and infrarenal aorta
Whole aortas of mice exposed to angiotensin II that did and did not develop aneurysms and saline infused controls
Illumina mouse sentrix 6 microarray (46,628 genes).
Differentially expressed between the 3 groups revealing aneurysm-associated and "protective" genes
Suprarenal aortas of mice exposed to angiotensin II that did and did not develop aneurysms
ELISA and IHC
Validate findings from the microarray in study 2 for Tnfrsf11b, Tgfb1, and inflammatory cell markers.
Comparison of gene expression in aneurysm prone suprarenal compared to aneurysm resistant infrarenal aorta
Examples of genes differentially expressed between paired supra and infrarenal aortas.
Mean expression ratio*
ADP-ribosylhydrolase like 1
Fatty acid binding protein 3
phosphoinositide-3-kinase adaptor protein 1
Death associated protein kinase 1 (Dapk1)
tubulin, alpha 8
chemokine (C-X-C motif) ligand 13
Transforming growth factor, beta receptor III
steroid 5 alpha-reductase 2
laminin, alpha 3
T cell receptor associated transmembrane adaptor 1
sex hormone binding globulin
aldo-keto reductase family 1, member B7
Genes expressed in aortas from mice with aneurysms compared to those without aneurysms and controls
Maximum aortic diameters of mice exposed to saline or angiotensin II that did or did not develop macroscopic aneurysms used in the microarray experiment (study 2).
Angiotensin II and aortic aneurysm (n = 5)
1.61 ± 0.18
1.11 ± 0.15
2.06 ± 0.48
0.72 ± 0.18
1.38 ± 0.17
Angiotensin II and no aortic aneurysm (n = 7)
1.34 ± 0.10
0.9 ± 0.10
1.13 ± 0.19
0.65 ± 0.09
1.0 ± 0.07
Saline controls (n = 6)
1.35 ± 0.11
1.16 ± 0.11
0.97 ± 0.08
0.67 ± 0.06
1.0 ± 0.06
Examples of genes upregulated in the aortas of mice with aneurysms.
Fold increase cf no AAA
Fold increase cf saline
chemokine (C-X-C motif) ligand 10; IP-10
chemokine (C-X-C motif) ligand 12; SDF-1
chemokine (C-X-C motif) ligand 14; MIP-2g
chemokine (C-C motif) ligand 2; MCP-1
chemokine (C-C motif) ligand 4; MIP-1B
chemokine (C-C motif) ligand 7; MCP-3
chemokine (C-C motif) ligand 8; MCP-2
chemokine (C-C motif) ligand 19; ELC
chemokine (C-C motif) ligand 21; SLC
matrix metalloproteinase 2
matrix metalloproteinase 12
matrix metalloproteinase 13
matrix metalloproteinase 14
colony stimulating factor 3 receptor (granulocyte); CD114.
Fc receptor, IgE, high affinity I, gamma polypeptide; CD23
alanyl (membrane) aminopeptidase; CD13
Cytokines and receptors
interleukin 1 beta
Antigen processing and presentation
Ia-associated invariant chain
histocompatibility 2, class II antigen A, beta 1
Examples of genes upregulated in the aortas of mice exposed to angiotensin II which did not develop aneurysms. These genes are potentially protective against AAA.
Fold increase cf AAA
Fold increase cf saline
actin, alpha 2, smooth muscle, aorta
potassium large conductance calcium-activated channel, subfamily M, beta member 1.
tissue inhibitor of metalloproteinase 4
PDZ and LIM domain 3
regulator of G-protein signaling 17
heat shock protein 1-like
gamma-aminobutyric acid (GABA-A) receptor, subunit alpha 3
betacellulin, epidermal growth factor family member
F-box protein 30
heat shock protein 1A
microtubule-associated protein 1B
cardiomyopathy associated 1
solute carrier family 22 (organic cation transporter), member 1
Validation of genes up-regulated in AAA by real time PCR.
Relative expression in AAA
Relative expression in no AAA
Relative expression in saline control
P value AAA v no AAA
P value AAA v saline control
chemokine (C-C motif) ligand 4; MIP-1B
chemokine (C-C motif) ligand 8; MCP-2
matrix metalloproteinase 2
Investigation of known functional KEGG pathways related to the differentially expressed genes
Top 10 KEGG pathways enriched in mouse aortic aneurysms.
Pathway (KEGG linked)
Total genes in pathway
Number genes upregulated in pathway in AAA v no AAA
Representative Genes (Entrez Gene ID)
Cytokine-cytokine receptor interaction
Cxcl5 (20311), Cxcl9 (17329), Cxcl10 (15945), Cxcl12 (20315), Cxcl13 (55985), Cxcl16 (66102), Cxcl14 (57266), Xcl1(16963), Cx3cr1 (13051), Cxcr4 (12767), Ccl19(24047), Ccl21a (20298), Ccl21b (18829), Ccl2 (20296), Ccl12 (20293), Ccl4 (20303), Ccl7 (20306), Ccl5 (20304), Ccl8 (20307), Ccr5 (12774), Il6 (16193), Csf3r (12986), Csf2rb2 (12984), Il7r (16197), Il2rg (16186), Il10ra (16154), Tnfrsf13b (57916), Il1b (16176)
Leukocyte transendothelial migration
Cldn11 (18417), Mmp2 (17390), Mmp9 (17395), Ptpn11, Cybb (13058), Ncf2 (17970), Ncf4 (17972), Thy1 (21838), Cxcl12 (20315), Cxcr4 (12767), Rac2 (19354), Vav1 (22324), Ptk2b(19229), Cxcl13 (55985), Cxcl14 (57266)
Col3a1 (12825), Col1a1 (12842), Comp (12845), Reln (19699), Thbs1 (21825), Thbs2 (21826), Igf1 (16000), Igf1r (16000), Vav1 (22324), Rac2 (19354), Itga11(319480), Itga6 (16403)
B cell receptor signaling pathway
Cd72(12517), Cd79b (15985), Fcgr2b (14130), Inpp5d(16331), Btk (12229), Blnk (17060), Vav1(22324), Rac2(19354), Rasgrp3(240168), Ifitm1(68713)
Natural killer cell mediated cytotoxicity
Hcst (23900), Klrd1 (16643), Fcgr3(14131), Fcer1g (14127), Tyrobp (22177, Ptk2b (19229), Vav1 (22324), Lcp2(16822), Cd48 (12506), Rac2 (19354)
Hematopoietic cell lineage
H2-Eb1(14969), Il7r (16197), Cd3d (12500), Fcgr1(14129), Anpep (16790), Il6 (16193), Il1b(16176), Csf3r (12986), Itga6(16403), Cd14(12475)
Jak-STAT signaling pathway
Il6(16193), Csfrb2(12984), Csf3r(12986), Il10ra(16154), Il2rg(16186), Il7r(16197), Jak3 (16453), Socs3(12702)
Reln(19699), Itga11(319480), Itga6(16403), Col3a1(12825), Col1a1(12842), Thbs1(21825), Thbs2(21826), Sdc3(20970)
Toll-like receptor signaling pathway
Cd14(12475), Il6 (16193), Il1b(16176), Ccl5(20304), Ccl4(20303), Cxcl10(15945), Cxcl9(17329),
Cell adhesion molecules (CAMs)
H2-Ab1(14961), H2-Eb1(14969), H2-DMb1(14999), Selpl (20345), Sdc3(20970), Itga6(16403), Cldn11(18417)
Mouse models of human diseases are potentially important tools with which to investigate mechanisms involved in the pathology and identify new treatments. Currently a number of animal models of human AAA are available . Many of these models require significant interventions such as exposing the aorta and subsequently infusing or painting elastolytic solution on a segment of the artery to induce weakening and inflammation. Currently the angiotensin II infusion model is most commonly used, possibly due to the relatively ease with which aneurysms are produced and the lack of requirement for what might be considered artificial manipulation of the aorta. To our knowledge this is the first study to examine whole genome expression in relation to aneurysm formation within this model. Our findings demonstrate that aneurysms forming in ApoE-/- mice have marked influx by a range of inflammatory cells and upregulation of cytokines which have all been previously demonstrated in human AAA [8, 9, 13–17]. These findings confirm those from more selective previous studies within this model [5–7, 18–22]. Importantly they suggest the value of this model for investigating the inflammatory and cytokine aspects of human AAA. We also demonstrated the upregulation of a range of chemokines, cytokines and proteolytic enzymes, such as Ccl4, Ccl8, Il6 and Mmp2 which have been previously implicated in human AAA [9, 10, 23, 24]. The upregulation of the latter genes in AAAs was validated using real time PCR. We identified genes up or downregulated in the aortas of mice resistant to aneurysm formation suggesting potentially protective and pathological roles of these genes respectively in AAA. Sclerostin expression is decreased within human AAA biopsies compared to controls, however the significance of this finding is unclear . We found increased expression of the sclerostin gene (Sost) in the aortas of mice resistant to aneurysm formation compared to both mice with aneurysms and saline controls, suggesting that sclerostin may play a role in inhibiting aortic dilatation. The ability of sclerostin to antagonise transforming growth factor beta, which has been linked to aortic aneurysm development, could be of significance in an aortic protection role for this gene . Acta2 (vascular smooth muscle actin) expression was increased in aortas resistant to aneurysm formation compared to other groups. Acta2 encodes the single most abundant protein in vascular smooth muscle cells, and mutations in the human gene are associated with ascending thoracic aortic aneurysms and dissections . Increased expression of Acta2 and other genes encoding smooth muscle cell proteins (Cald1, Dstn), in aortas protected from aneurysm, highlight the importance of vascular smooth muscle cells in maintaining vascular integrity. We observed downregulation of the genes encoding kininogen (kng1), Apolipoprotein CI (Apoc1) and the neutrophil-associated leucine-rich alpha-2-glycoprotein 1 (Lrg1) amongst others, in aortas of mice resistant to aneurysm suggesting that they may be pathological genes. The role of these in aneurysm formation warrants further investigation.
We also investigated genes that might underlie the predilection for suprarenal aneurysm formation within this model, highlighting downregulation of a number of genes which may explain the susceptibility of the suprarenal aorta to aneurysm formation. Urocortin has been shown in vitro and within animal models to inhibit the effects of the renin-angiotensin system, thus downregulation of Ucn3 (urocortin 3) within the suprarenal aorta of ApoE-/- mice may be relevant to its predilection for aneurysm formation following angiotensin II infusion [11, 12]. We also demonstrated downregulation of Lama3 (laminin alpha 3) within the suprarenal aorta. This extracellular matrix protein has been demonstrated to be present in reduced concentrations within some human AAAs and therefore may also be relevant to the preponderance of the suprarenal aorta to aneurysm formation [27, 28]. In vitro laminin also plays important roles in modulating inflammation and MMP production suggesting its relevance to aneurysm formation [29, 30]. Further studies will be required to investigate these candidate genes for example employing deficient mice.
Comparison of results from this study and those from other expression arrays for AAA.
Number of samples/controls
Tissue of interest
Similar genes upregulated
18057 oligonucleotides microarray
Chemokines (e.g. CCL2, CCL4, CCL8, CCR5, CXCL5, CXCR4, TNFRSF13B)
Pro-inflammatory cytokines (e.g. IL1B, IL2RG)
Matrix metalloproteinase (e.g. MMP9)
Cell lineage markers (e.g. CD53, CD68, CD72)
1181 cDNA clones
Elastase induced AAA
Inactivated elastase infused aortas
Pro-inflammatory cytokines (e.g. IL1B, IL6, INF, IGF1)
Chemokines (e.g. CCL7)
JAK-STAT signalling (e.g. SOC3)
375 cDNA clones
Chemokines (e.g. CXCR2)
265 cDNA clones
AOD and normal†
Matrix metalloproteinase (e.g. MMP9, MMP12)
Pro-inflammatory cytokines (e.g. IL1B, IL6)
Chemokines (e.g. CCL4, CCR5)
Fibrinolysis (e.g. uPA)
8799 cDNA clones microarray
Elastase induced AAA
Saline infused aortas
Oxidative stress (Heme oxygenase, lipoxygenase)
1176 cDNA clones
Cathepsins (e.g. cathepsin H)
Matrix metalloproteinase (e.g. MMP9)
Chemokines (e.g. CXCR4, CCL5)
This study is the first to carry out a whole genome expression analysis within the angiotensin II- Apo E-/- model. We used an explorative approach using relatively small numbers of arrays (28 in total were included in the array studies). We were not adequately powered to adjust for multiple testing given the number of transcripts examined. Unlike some other microarray studies we have used real time PCR, IHC and ELISA to confirm some of our findings rather than relying on RNA assessment alone . Numerous studies have now demonstrated the validity of microarray platforms therefore we felt it would be useful to demonstrate the functional relevance of altered RNA expression [9, 35]. Our findings suggest the value of this mouse model as one to investigate the role of inflammation, cell recruitment and proteolysis in AAA.
In conclusion our study supports the value of the angiotensin II infused ApoE-/- mouse model for investigating mechanisms and interventions relevant to human AAA.
Infusion of angiotensin II induces aortic dilatation particularly affecting the suprarenal aorta in ApoE-/- mice [5, 6, 18–21]. Based on studies carried out in our and other laboratories the response to angiotensin II is variable, with some mice developing large aneurysms but other animals appearing resistant to aneurysm formation with aortic diameters similar to that of saline controls (Additional file 12). The infrarenal aorta is protected from aneurysm formation in these mice. To assess the likely signalling pathways relevant to aneurysm development and progression within this mouse model we carried out three studies (Table 1): 1) We compared RNA expression within segments of supra and infrarenal aortas from 13 week old male ApoE-/- mice unexposed to angiotensin II (n = 10). 2) We compared RNA expression from whole aortas of 17 week old male ApoE-/- mice which had been exposed to angiotensin II (1.44 μg/kg/min) for 4 weeks where there was clear evidence of aortic aneurysm formation (n = 5) with that of mice failing to develop aneurysms (n = 7) and those exposed to saline infusion (n = 6). 3) We selected 2 genes and 5 cellular pathways identified as upregulated within the aortas of mice with aneurysms for validation using protein assessments including ELISAs and immunohistochemistry (IHC). The selection of genes was based on their association with pathways we had identified from pathway analysis of the data and recognised ability to be able to assess them using ELISAs or IHC. For study 3, twenty-eight additional 17 week old male ApoE-/- mice were infused with angiotensin II for 4 weeks. Ten mice in study 3 died prematurely due to aortic rupture and were excluded from further analysis in order to avoid post-mortem or post rupture effects confounding assessments, leaving 18 animals in this group.
This investigation conformed to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication No. 85-23, revised 1996). Ethical approval was obtained from the local institutional committee prior to commencement of the study. Male ApoE-/- mice were obtained from Animal Resources Centre, Canning Vale, Western Australia aged 6–8 weeks. Mice were fed standard chow, and at 13 weeks either their aortas were harvested (study 1, n = 10) or angiotensin II (n = 12 study 2; n = 28 study 3) or saline (n = 6 study 2) infusion commenced. Aortic harvesting and osmotic minipump placement (Model 2004, ALZET, Durect Corporation, Cupertino, California, USA) was carried out under ketamine (150 mg/kg i.p.) and xylazine (10 mg/kg i.p.) anaesthesia as previously described . The 28 day infusion period and dose of angiotensin II were selected as these have been routinely used in other studies within this model [5, 6, 18–21]. In studies 1 and 2, mice were euthanized by carbon dioxide asphyxiation, the aortas perfused with RNAlater® (Qiagen, Doncaster, Victoria, Australia), and harvested from arch to iliac bifurcation and stored at -80°C for later analysis. For study 3 mice were euthanized, aortas were perfused with PBS and the suprarenal aortic segments divided into 2 and stored separately at -20°C for later IHC and cytokine assessment.
Aortas were placed on a black background and digitally photographed (Coolpix 4500, Nikon). Maximum diameters of the aortic arch, thoracic, suprarenal and infrarenal aorta were determined from the images using computer-aided analysis (Scion Image, Scion Corporation). Preliminary studies (n = 27) established that these measurements could be repeated with good intra-observer reproducibility (Coefficient of repeatability 0.98, 95% confidence intervals 0.975–0.982, and coefficient of variation 4%).
Total RNA was extracted from homogenised aortas using the TRI reagent (Sigma) and RNeasy Mini kits (Qiagen) and analysed on the HP 2100 Bioanalyzer (Agilent Technologies) for integrity using Eukaryotic total RNA nano chips (Agilent) (Additional File 11). All samples had RNA integrity scores between 6.9 and 8.1. For study 1, RNA extracted from the pooled suprarenal aortas of two mice was compared with that obtained from the infrarenal aortic segments of the same mice. A total of 10 mice (i.e. 5 pairs of pooled segments) were included in study 1. For study 2, RNA extracted from the whole aortas of mice with aneurysms (n = 5, Additional File 12A) was compared with that extracted from the whole of aortas of saline controls (n = 6, Additional File 12C) and mice exposed to angiotensin II which did not develop aneurysms (n = 7, Additional File 12B). No sample pooling was carried out in study 2. RNA hybridization was performed, and gene expression profiles determined, using CodeLink Mouse Whole Genome Bioarray chips (GE healthcare, Amersham, Bioscience) (study 1, n = 10) and Illumina Mouse Sentrix 6 version 1.1 Beadchips (study 2, n = 18). For study 1 total RNA from infrarenal and suprarenal aortas was supplied to GenUS BioSystems Inc. (Northbrook, Illinois USA) who conducted cDNA synthesis, hybridization and scanning using standard protocols. In brief, 10 μg of total RNA was used for each 'sample versus sample' comparison and first and second strand cDNA were prepared using the Codelink™ iExpress Expression assay Reagent kit (GE healthcare Amersham). Biotinylated cRNA target was prepared from the cDNA template by linear amplification using biotin-dNTPs and verified on a Bioanalyzer 2100. The cRNA was fragmented to uniform size and once again verified on the Bioanalyzer 2100. Each fragmented, biotin-labeled cRNA was added to a Codelink Mouse Whole Genome array which contained 34,957 probes targeting unique mouse transcripts. The bioarrays were washed, exposed to Cy5 streptavidin and scanned using GenePix 4000B laser scanner. Scanned image files were examined using CodeLink image and data analysis software (GE healthcare, Amersham, Bioscience). The image information was converted into spot intensity values using CodeLink™ Expression Analysis software (GE healthcare). The generated values were exported to GeneSpring GX 7.3.1 software (Silicon Genetic, USA) for further analysis. Study 2 labelling, hybridisation and scanning was done at the SRC Microarray Facility, University of Queensland, Brisbane, Australia according to the manufacturer's instructions. For study 2 total RNA was amplified in a single-round of in vitro transcription amplification that allowed incorporation of biotin-labeled nucleotides using the Illumina TotalPrep RNA amplification kit (Ambion, Inc., Austin, TX). mRNA samples were assessed for integrity and purity prior to hybridization using the Bioanalyser 2100 with mRNA Nano chips (Agilent Technologies). cRNA of each sample was hybridized to an Illumina Mouse WG-6 V1.1 BeadChip followed by washing, blocking, and streptavidin-Cy3 staining steps, and scanning with a high-resolution Illumina BeadArray reader scanner. The data extraction was performed by using Illumina Bead Studio V2.3.41 software with the output being raw, non-normalized bead summary values. The BeadStudio matrix contains the summarised expression values (Avg_Signal), standard error of the bead replicates (BEADSTDEV), number of beads used (Avg_NBEADS) and a detection score, which estimates the confidence limit of detection of a gene. The performance of the built-in controls that accompany each Illumina beadchip experiment was assessed as part of the Bead Studio V2 experiment performance report and was found to be satisfactory. Controls included Housekeeping controls for intactness of the biological specimens, negative controls to establish gene expression detection limits and hybridization controls including low and high stringency controls and biotin signal generation controls. The raw data matrix extracted from Beadstudio was uploaded into GeneSpring GX 7.3.1 (Silicon Genetics, Redwood City, CA) software for downstream analysis. Details of GeneSpring analysis including data transformations, per chip and per gene normalisations are described below in Analysis and Design.
Real time PCR
Using RNA obtained for the mice employed in the micro-array investigations in study 2 we validated findings for 4 genes (Ccl4, Ccl8, Il6 and Mmp2) using real time PCR. RNA samples from mice exposed to angiotensin II that developed aneurysms (n = 5), mice exposed to angiotensin II that did not develop aneurysms (n = 7) and saline control mice (n = 6) were included in the analysis. The QuantiTect SYBR Green one-step RT-PCR Kit (Qiagen) and Quantitect Primer Assays (Qiagen) (Il6, QT00098875; Ccl4, QT00154616; Ccl8, QT00128548; Mmp2, QT00116116) were used according to the manufacturer's instructions with 25 ng of total RNA as template. Primers for mouse Gapdh were used to amplify the housekeeping gene (Qiagen, QT01658692). Standard curves for each gene including the housekeeping gene were constructed using duplicate sets of five (5) 10-fold serial dilutions of equal volumes of the pooled saline control RNAs. Negative and "minus-RT" controls were also included. All reactions were independently repeated in duplicate to ensure the reproducibility of the results. Cycling parameters were as follows: 50°C 30 min for RT; 95°C 15 min; 40 cycles of 94°C 15 sec, 55°C 30 sec, 72°C 30 sec. Data were viewed and analysed using the Rotor-Gene's real-time analysis software (Rotor-Gene 6000; Corbett Life Science, Sydney). The relative expression of the gene of interest in each sample was calculated by the Rotor-Gene software using the concentration-Ct-standard curve method and normalised using the average expression of Gapdh for each sample. SSPS statistical software was used to calculate median and interquartile ranges for expression of each gene of interest in each group.
Serial cryostat sections 7 μm thick were cut from suprarenal aortas with and without aneurysms prior to staining for inflammatory cells. Serial frozen sections were air-dried, fixed in acetone for 10 min at -20°C, air dried and rehydrated with PBS before being incubated in 3% H2O2/0.1% sodium azide/PBS to block endogenous peroxidase. For macrophage detection, sections were blocked in 2% normal goat serum in PBS followed by staining using pan-macrophage antibody (clone MOMA-2, Abcam AB33451), and goat anti-rat HRP (Millipore AP136P). Rat IgG (Sigma I4131) was used as isotype control. Detection of osteoprotegerin (OPG) was carried out using biotinylated goat anti-mouse OPG (R&D BAF459) diluted to 1 μg/ml in blocking buffer followed by Vectastain Elite ABC-HRP (Vector Laboratories). Biotinylated goat-IgG was used as isotype control (Vector Laboratories VEBI1001). T cells (CD3e FITC clone 145-2C11, BD Biosciences 553061), B cells (CD45R/B220 biotin clone RA3-6B2, BD Biosciences 550385), dendritic cells (CD11c biotin clone HL3, BD Biosciences 553800) and neutrophils (Ly6G/Ly6C(Gr-1) FITC clone RB6-8C5, BD Biosciences 553127) were demonstrated using either anti-FITC HRP (Invitrogen), biotinyl-tyramide (Perkin Elmer), SA-HRP (Perkin Elmer) for FITC-conjugated antibodies or SA-HRP, biotinyl-tyramide, SA-HRP for biotinylated antibodies. Appropriate isotype controls were added to other sections (all BD Biosciences). Slides were incubated in the peroxidase substrate 3, 3'-diamminobenzidine (ImmPACT DAB, Vector), counterstained in Mayer's Haematoxylin, dehydrated, cleared in xylene and mounted in Depex mounting medium. Sections were photographed using a Nikon Eclipse 50i microscope, Digital Sight camera and NIS-elements software.
Protein was extracted from individual frozen suprarenal aortic segments by homogenising in buffer (10 mM cacodylic acid, 60 mM L-arginine, 0.25% triton x-100 in PBS, pH 7.2) and centrifuging at 18,000 × g at 4°C for 20 min. Supernatant protein was quantified by the Bradford technique (Protein Assay, Bio-Rad, Hercules, California, USA). Concentrations of OPG and transforming growth factor beta-1 (TGFb-1) were assessed using commercial ELISAs (Quantikine, R&D Systems, MOP00 for OPG, MB100B for TGFb-1) and expressed as pg/mg of protein. Initial tests were performed to determine an appropriate amount of extracted aortic protein to load in each well to suit the ELISA standard curves (10 μg for OPG ELISA, 20 μg for TGFb-1 ELISA). Serum and extracted aortic proteins from OPG deficient mice were confirmed as having zero readings using the OPG ELISA (data not shown). Batch analysis of the samples was carried out to facilitate comparison between groups. We have previously reported excellent reproducibility of similar assays .
Analysis and design
We designed the current study as an exploratory analysis expecting a minimal level of false discovery inevitable in analysis of large microarray gene probes. Sample size calculations were conducted using SPCalc [37, 38]. For study 1 (which included paired samples) we aimed to detect a 1.5-fold difference at a power of 0.8 (alpha uncorrected 0.05), while for study 2 (which included unpaired samples) we aimed to detect a 2-fold difference. Based on the number of gene probes to be examined (26,522) we wished to control the false positives to a mean of 2 [17, 18]. We estimated the total number of arrays needed for study 1 and 2 were 10 and 18 respectively. Microarray data were imported into Genespring GX 7.3.1 (Agilent) for analysis. The data from the individual bioarrays have been deposited in NCBIs Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO accession number GSE7006 (GEO Accession viewer) for study 1 and GSE12591 http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=rduxbsiqmqswefi&acc=GSE12591 for study 2. For study 1 which used paired samples, normalisations were as follows: each chip was normalised to the median intensity of the array; each gene was normalised relative to the suprarenal sample of each pair. Thus the expression of each SRA sample was normalised to 1. Volcano plots were used to identify differentially expressed genes with >1.5 fold difference in expression and p < 0.05. Statistical analysis was carried out using a paired t-test (unequal variances) comparing the mean infrarenal/suprarenal ratio to a baseline value of 1 for each sample pair. In study 2 we followed the standard normalization procedures recommended for the GeneSpring GX 7.3.1 software for one-colour array data. In brief, data transformation was corrected for a low signal, with values recorded at <0.01 increased to the minimum (0.01). Default settings were used for experiment normalisation which included chip normalisation to 50th percentile and gene normalisation to the median. The cross gene error model was used to further filter low quality data. We sought to identify genes with a 2-fold differential expression within the aortas of mice with and without aneurysms based on an uncorrected p value of < 0.05 included in our sample size estimate. We initially compared findings from mice that received angiotensin II and developed AAAs (n = 5) with both other groups of mice (n = 7 and 6). Genes showing a greater than 2 fold difference in expression between groups (unpaired t-test (unequal variance) p < 0.05), were considered to be differentially expressed. We reasoned that the most significant findings would relate to genes differentially expressed between angiotensin II perfused mice, that did (n = 5) and did not (n = 7) develop aneurysms. Volcano plots were used to identify differentially expressed genes between the aortas of these two groups of mice. This group of 531 genes was further investigated by hierarchical clustering in GeneSpring, in which a tree of transcripts or genes is built by successively finding the two most similar gene expression patterns from the full transcript set. Individual samples were then arranged in a condition tree according to overall similarity. We also included the saline group in this clustering analysis in order to show how these 531 genes are expressed in control aortas. Genes with similar expression patterns were grouped as hierarchical clusters with distances between samples computed using Pearson correlations for similarity measures and average linkage as the clustering algorithm. Hierachical clustering revealed several major nodes in the gene tree structure which indicated at least 4 different patterns of gene expression. Lists of differentially expressed genes were examined for biologically relevant associations using Gene Ontologies and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis in the web-based software Webgestalt http://bioinfo.vanderbilt.edu/webgestalt. Quantitative real time PCR outcomes in study 2 and concentrations of cytokines measured in study 3 were compared between groups using Mann Whitney U test.
Grants from the National Institute of Health, USA (RO1 HL080010) and NHMRC (project grant 540403) supported this work. JG is supported by a Practitioner Fellowships from the NHMRC, Australia (431503). These funding sources took no part in the design of this study, data collection or analysis, and the decision to submit the work for publication. Study 2 was supported by the Australian Research Council's, Special Research Centre for Functional and Applied Genomics (Institute for Molecular Bioscience) Microarray Facility.
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