Figures
Abstract
Atherosclerotic stenosis of cerebral arteries or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans, but relatively little is known about gene expression changes in vessels at risk. This study compares comprehensive gene expression profiles in the middle cerebral artery (MCA) of New Zealand White rabbits exposed to two stroke risk factors i.e. hypertension and/or hypercholesterolemia, by the 2-Kidney-1-Clip method, or dietary supplementation with cholesterol. Microarray and Ingenuity Pathway Analyses of the MCA of the hypertensive rabbits showed up-regulated genes in networks containing the node molecules: UBC (ubiquitin), P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP (amyloid precursor protein); and down-regulated genes related to MAPK, ERK 1/2, Akt, 26 s proteasome, histone H3 and UBC. The MCA of hypercholesterolemic rabbits showed differentially expressed genes that are surprisingly, linked to almost the same node molecules as the hypertensive rabbits, despite a relatively low percentage of ‘common genes’ (21 and 7%) between the two conditions. Up-regulated common genes were related to: UBC, SERPINB2, TNF, HNF4A (hepatocyte nuclear factor 4A) and APP, and down-regulated genes, related to UBC. Increased HNF4A message and protein were verified in the aorta. Together, these findings reveal similar nodal molecules and gene pathways in cerebral vessels affected by hypertension or hypercholesterolemia, which could be a basis for synergistic action of risk factors in the pathogenesis of ICLAD.
Citation: Ong W-Y, Ng MP-E, Loke S-Y, Jin S, Wu Y-J, Tanaka K, et al. (2013) Comprehensive Gene Expression Profiling Reveals Synergistic Functional Networks in Cerebral Vessels after Hypertension or Hypercholesterolemia. PLoS ONE 8(7): e68335. https://doi.org/10.1371/journal.pone.0068335
Editor: Ken Arai, Massachusetts General Hospital/Harvard Medical School, United States of America
Received: January 3, 2013; Accepted: May 28, 2013; Published: July 16, 2013
Copyright: © 2013 Ong et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by the National Research Foundation Singapore under its Competitive Research Programme (CRP Award NRF-CRP 3-2008-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Atherosclerotic stenosis of large arteries at the base of the brain or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans [1], and is possibly the most common vascular lesion in the world [2]. It affects the middle cerebral artery (MCA), intracranial portion of the internal carotid artery, vertebrobasilar artery and the posterior and anterior cerebral arteries [1]. ICLAD carries a poor prognosis in terms of subsequent vascular event and death, and there is 25 - 30% incidence of recurrence in the 2 years after stroke [3], [4]. The disease is also prevalent among 53% of vascular dementia and 18% of Alzheimer’s disease patients of Asian ethnicity [1], [5].
The risk factors for ICLAD include hypertension, diabetes, hypercholesterolemia and cigarette smoking [6], and a strong association is found between asymptomatic ICLAD presenting as intracranial stenosis or calcification with large artery stiffness, and patients with untreated hypertension [7]. Arterial stiffness is a major determinant of increased systolic blood pressure, and is associated with lesions in intracranial arteries [8]. Prolonged elevation of blood pressure leads to reduction in vessel cross sectional area, increased wall thickness and accelerated plaque formation [9], [10]. Moreover, hypertension is thought to drive the atherosclerotic changes from larger to smaller vessels, and from extracranial- to intracranial vessels [11], [12]. Hypercholesterolemia is also a risk factor for ICLAD [6], and ischemic stroke from both extracranial and intracranial large-artery atherothromboembolism is associated with increased dietary intake of saturated fat, physical inactivity, obesity, and diabetes [13]. Reduction of cholesterol levels with statin treatment delays the progression of lesions in patients with ICLAD [14]. Increased lipoprotein is an independent biochemical risk factor for the development of ICLAD [15], and increased serum cholesterol is associated with elevated levels of oxidized low density lipoprotein [16]. The latter inhibits nitric oxide in endothelial cells to induce vasospasm [17] or increases tissue factor activity in these cells, to promote thrombosis [18]. Other factors that could contribute to ICLAD include increased oxidative stress in vessel walls [19]. A combination of hypercholesterolemia and hypertension may result in greater damage to vessels [9], [20].
Epidemiological studies indicate that there is increased risk of a second stroke especially in the first 1 or 2 years of post-stroke event [3], [4], [21], [22]. The reasons for this are not fully understood, but almost certainly involve gene expression changes at the vascular level that drive the atherothrombotic process. Thus far, however, there have been no studies to delineate global gene expression or gene network profiles in large intracerebral arteries at risk of atherothrombosis.
The present study was carried out to compare gene expression and morphological changes in intracranial vessels of rabbits, after exposure to hypertension and/or hypercholesterolemia. These conditions were induced by mostly non-genetically based methods, to reduce possible confounding effects during microarray analysis. The middle cerebral artery (MCA) was chosen for study, as this vessel is often affected in ICLAD [1], [23], [24], [25].
Materials and Methods
Animals
Male New Zealand White rabbits were used as it is the gold standard in atherosclerosis studies [26]. Although it is possible to produce hypertension in rats and mice, it is difficult to produce hypercholesterolemia in these animals [27]. The very small size of the MCA in rats and mice also hinders gene expression analyses of these vessels. Rabbits were approximately 8 weeks old (young adults) and weighed 2.0–2.5 kg each at the start of the experiments. Two sets of experiments were carried out: i) to determine gene expression changes in the MCA after hypertension, and ii) to determine gene expression changes in the MCA after hypercholesterolemia plus sham operation, and gene expression changes in the MCA after hypertension plus hypercholesterolemia. The first set of experiments were carried on 6 rabbits with the Goldblatt 2-Kidney 1-Clip (2K1C) method used to induce hypertension and fed with normal diet, vs. 6 sham operated controls on a normal diet. The second set of experiments were carried out on 6 rabbits on a high cholesterol diet with sham operation, 6 rabbits with 2K1C to induce hypertension plus a high cholesterol diet, and 6 rabbits on a normal diet.
The 2K1C procedure to induce hypertension was carried out as previous described [28]. In brief, animals were anesthetized with ketamine (75 mg/kg)/xylazine (10 mg/kg) cocktail followed by isoflurane maintenance, and the left renal artery exposed. The artery was partially occluded by attachment of a U-shaped silver ‘clip’ with a 0.6 mm slot. The clip was in left in place until the animals were sacrificed. Sham operated animals received the same surgical procedures as the 2K1C group, except that the renal artery was not partially occluded after its exposure. Animals that were subsequently treated with high cholesterol diet were allowed to recover from surgery for 1 week before treatment with diet containing cholesterol. Rabbits on this diet were fed with GPR diet +1% cholesterol (Glen Forrest Stockfeeders, Australia). Sham operated control rabbits were fed with GPR diet without cholesterol. All procedures including animals were approved by the Institutional Animal Care and Use Committee of the National University of Singapore, and carried out in accordance with guidelines of the National Advisory Committee for Laboratory Animal Research.
Measurement of Body Weight, Mean Arterial Pressure and Serum Total Cholesterol
Rabbits were anaesthetized by intramuscular injection of ketamine/xylazine cocktail, followed by mean arterial pressure measurements, and collection of blood. Mean arterial pressure was recorded from the ‘middle’ ear artery (Powerlab 4/30, AD Instruments, CO, USA), and blood samples obtained for cholesterol analysis, at 0, 4, 10 and 12 weeks. Approximately 3 mL of blood was withdrawn from the artery and collected in BD Vacutainer® Serum Tubes with Clot activator and silicone-coated interior (Becton Dickinson, NJ, USA). Whole blood was centrifuged at 1,000 g for 15 min, and the serum transferred to new vials and kept frozen at −80°C till analysis. Serum total cholesterol levels were measured by a fluorometric assay (Ex/Em 535/587 nm, BioVision Inc., CA, USA). Samples were analyzed in triplicates and read with a microplate reader (Infinite® i-control, Tecan Trading AG, Switzerland).
Tissue Harvesting and RNA Extraction
The 2K1C rabbits on normal diet, sham operated control rabbits on normal diet, or hypercholesterolemia plus sham operated rabbits and hypertension plus hypercholesterolemia rabbits were sacrificed 12 weeks after surgery. Sham operated control rabbits or untreated controls on a normal diet were sacrificed after a similar time. Animals were deeply anaesthetized by ketamine/xylazine cocktail and euthanized by intravenous injection of pentobarbital (250 mg/kg). The brains were removed and hemisected. The left half of the brain was immersed in 4% paraformaldehyde in 0.1M phosphate buffer in preparation for histology or electron microscopy (see below). The right MCA was identified and quickly stripped off the surface of the brain without any underlying cortical tissue, immersed in RNAlater® (Ambion, TX, USA), frozen in liquid nitrogen and stored in −80°C till further analysis. Total RNA was extracted using TRizol reagent (Invitrogen, CA, USA) according to the manufacturer’s protocol. Extracted RNA was purified using the RNeasy® Micro Kit (Qiagen, CA, USA). The cerebral neocortex, hippocampus, liver, kidney, aorta and other organs were also removed and snap frozen or stored in paraformaldehyde for future analyses.
DNA Microarray Analysis
Ten µL of total RNA from the MCA of four rabbits from each group were submitted to Genomax Technologies, Singapore. RNA quality was confirmed using an Agilent 2100 Bioanalyzer. cRNA was then generated and labeled using the one-cycle target labeling method, and hybridized to the 1-colour Agilent Rabbit Microarray (G2519F-020908; Agilent Technologies, CA, USA), according to the manufacturer’s protocol. Data was collected and exported into GeneSpring v11 software (Agilent Technologies) for analysis, using a parametric test based on the cross gene error model. Differentially expressed genes (DEGs) are those that show significantly increased or decreased expression compared to sham-operated controls using one-way ANOVA with Tukey HSD post-hoc test and corrected for multiple comparisons using Benjamini Hochberg FDR. P<0.01 was considered significant. In this study, to reduce false positives, only DEGs with greater than 4-fold change (or in the case of common genes between two data sets, greater than 4-fold change in at least one data set) were presented and used in IPA network analyses.
Network Analyses
The gene sets were analyzed using the Ingenuity Pathway Analysis (IPA) software (Ingenuity® Systems, www.ingenuity.com). Gene identifiers and corresponding expression values of up-regulated or down-regulated DEGS with more than 4-fold change was uploaded into IPA application. Each identifier mapped to its corresponding object in Ingenuity’s Knowledge Base, and was overlaid onto a global molecular network developed from information contained in the Ingenuity Knowledge Base. “Focus Genes” (Network Eligible genes) are defined as DEGs that have at least one other molecule in the Knowledge Base that interacts with it to form a “network”. The latter shows interactions between focus genes and ‘node molecules’ in the network, and how they work together at the molecular level.
Electron Microscopy
The left half of the brain was dissected out, fixed in 4% paraformaldehyde and 0.1 M phosphate buffer, and kept at 4°C. Blocks containing the MCA were osmicated, dehydrated in an ascending series of ethanol and acetone and embedded in Araldite. Thin sections were cut, mounted on Formvar coated copper grids and stained with lead citrate. They were viewed using a Jeol 1010 electron microscope (Jeol, Tokyo, Japan).
Quantitative Real-time PCR
The mRNA of one of the node molecules identified by IPA, HNF4A, was further verified in the aorta by real-time RT-PCR. This was necessary, as only a small amount of RNA could be extracted from the rabbit MCA. Purified RNA from the descending aorta of 4 hypercholesterolemia plus sham, 4 hypertension plus hypercholesterolemia and 4 untreated control rabbits were reverse-transcribed with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, CA, USA). Reaction conditions were 25°C for 10 min, 37°C for 120 min and 85°C for 5 sec. Real-time PCR amplification was performed using the 7500 Real time PCR system with TaqMan® Universal PCR Master Mix and probes. The PCR conditions were initial incubation of 50°C for 2 min and 95°C for 10 min, followed by 40 cycles of 95°C for 15 sec and 60°C for 1 min. Rabbit TaqMan® probe for HNF4A was purchased from Applied Biosystems. Rabbit ß-actin TaqMan® probe was used as an internal control. The fold change in expression was calculated using the 2-delta delta CT method as described previously [29]. Possible significant differences between the means were analyzed, using one-way ANOVA with Bonferroni’s multiple comparison post hoc test. p<0.05 was considered significant.
Western Blot Analysis
Aorta samples were homogenized in 10 volumes of ice-cold lysis buffer (150 mM sodium chloride, 50 mM Tris–hydrochloride, 0.25 mM EDTA, 1% Triton X-100, 0.1% sodium orthovanadate, and 0.1% protease inhibitor cocktail, pH 7.4), followed by centrifugation at 10,000 g for 10 min at 4°C. The supernatant was then collected, and protein concentrations measured using the Bio-Rad protein assay kit. The homogenates (20 µg) were resolved in 10% SDS-polyacrylamide gels under reducing conditions and electrotransferred to a polyvinylidene difluoride (PVDF) membrane. Non-specific binding sites on the PVDF membrane were blocked by incubation in 5% non-fat milk in tris-buffered saline-0.1% Tween 20 (TBST) for 1 h. The PVDF membrane was incubated overnight at 4°C with a mouse monoclonal anti-HNF4A antibody (K9218, Abcam, Cambridge, UK) diluted 1∶500 in 5% non-fat milk/TBST. After washing with TBST, the membrane was incubated with horseradish peroxidase-conjugated secondary anti-mouse IgG (Pierce, IL, USA) for 1 h at room temperature. Immunoreactivity was visualized using a chemiluminescence substrate (Millipore, MA, USA). Loading controls were carried out by incubating the blots at room temperature for 30 min with stripping buffer (100 mM 2-mercaptoethanol, 2% SDS, and 62.5 mM Tris-hydrochloride, pH 6.7), followed by reprobing with a mouse monoclonal antibody to ß-actin (Sigma, MO, USA; diluted 1∶10,000 in TBST). Exposed films containing blots were scanned and densities of the bands normalized to those of ß-actin. Possible significant differences between the values from treated and control rabbits were analyzed, using one-way ANOVA with Bonferroni’s multiple comparison post hoc test. p<0.05 was considered significant.
Histochemistry and Immunohistochemistry
Aorta samples were sectioned at 40 µm using a freezing microtome. Sections were processed for histochemistry using Masson’s Trichrome histochemical stain, or immunoperoxidase staining. The latter sections were incubated in a blocking solution composed of 5% donkey serum (Vector) and 0.1% Triton X-100 for 1 h, followed by incubation with mouse monoclonal antibody to HNF4A (diluted 1∶100 in PBS) overnight. The sections were then washed three times in PBS and incubated with biotinylated anti-mouse secondary antibody. Immunoreaction product was visualized using an avidin-biotinylated horseradish peroxidase kit (Vector Laboratories, Burlingame, USA). Histochemically or immunohistochemically stained sections were mounted on glass slides and viewed using a light microscope (IX70, Olympus, Japan).
Results
1. Body Weight, Mean Arterial Pressure and Serum Total Cholesterol Levels
The average body weight was not significantly different between the 2K1C and sham operated groups (data not shown),but mean arterial pressure of 2K1C group was markedly higher than that of sham group at 4, 10, 12 weeks after the surgery (Figure 1A). The serum total cholesterol level remained at a low level (<100 mg/dl) for both groups throughout the experiment, and no difference was found between the groups, except for a slightly lower value in the 2K1C group on week 4 (Figure 1B). The average body weight among all groups was not significantly different (data not shown).
(A) Mean arterial pressure in hypertension only rabbits. (B) Serum cholesterol levels in hypertension only rabbits. (C) Mean arterial pressure in hypercholesterolemia plus sham- and hypertension plus hypercholesterolemia rabbits. (D) Serum cholesterol levels in hypercholesterolemia plus sham- and hypertension plus hypercholesterolemia rabbits. H: Hypertension only. HC: Hypercholesterolesterolemia plus sham operation. HTHC: Hypertension plus hypercholesterolemia. MAP: mean arterial pressure. Data are expressed as mean ± SEM. *p<0.05, **p<0.01 vs. control (Student’s t-test in A,B; repeated measure ANOVA followed by Tukey test in C,D).
Increased mean arterial pressure was found in the 2K1C plus cholesterol-fed rabbits (Figure 1C), and markedly elevated serum total cholesterol levels (>200mg/dl) were found in both the hypercholesterolemia plus sham- and 2K1C plus hypercholesterolememia groups at 4, 10 and 12 weeks, compared to control rabbits on a normal diet (Figure 1D).
2. Microarray Analyses
2.1. Microarray analyses of the hypertension only group.
The gene expression profile in the MCA of the hypertension only group was compared with that of sham operated controls on a normal diet. After unknown genes and repeated probes of the same genes were omitted, 51 up-regulated and 97 down-regulated genes (greater than 4-fold change) were found in the MCA (Figure 2). Among the highly up-regulated genes in the MCA of the hypertension only group compared to sham controls were FAM167A, CERS3 and FAM53C (Table 1). Among the highly down-regulated genes were FOXN1, NSRP1 and THUMPD3 (Table 2). The panel of genes was imported into IPA to analyze network interactions.
A: total number of genes, B: up-regulated genes C: down-regulated genes (One gene which is common between the Hypertension only- and Hypertension plus hypercholesterolemia group was both up- and down-regulated, and omitted).
The IPA network with the ‘largest number of up-regulated focus genes’, contained 16 focus genes with functions in Cancer, Connective Tissue Disorders, Skeletal and Muscular Disorders. Focus genes in this network were ASB4, C1orf50, CCDC89, CSDE1, DIS3L2, EHBP1, FAM167A, GIT1, KIAA0232, NAA25, NAE1, PHRF1, SIPA1L3, TAF15, TESK2 and TTLL5. They were related to the ‘node molecule’, UBC (ubiquitin) (Figure 3, Table 1). The network with the second largest number of up-regulated focus genes had 12 focus genes, with functions in Cell-mediated Immune Response, Cellular Development, Cellular Function and Maintenance. Focus genes were CCL1, CD46, CYP1A2, FANCC, MEP1B, MFI2, MMP1, PDCD11, RNASE1, SERPINB2, SPAG6 and ZDHHC23; they were related to P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP (Figure 4, Table 1).
Nodes are displayed using various shapes that represent functional classes of gene products. Focus genes in this network are indicated in grey nodes. Solid and dotted lines indicate direct and indirect interactions, respectively.
The network with the largest number of down-regulated focus genes contained 23 focus genes with functions in Cardiovascular System Development and Function, Organismal Development, Cell Morphology. Focus genes in this network were ANK2, BTG1, CCNH, EPAS1, GNMT, HPGD, ITK, KDM4A, LIMD1, MS4A1, NDUFB6, NPM1, OGN, PAK4, PAPOLA, PARK7, PSMD4, PURA, RPL26, SFRP4, SPARC, TNFAIP8 and TRPV5. They were related to MAPK, ERK1/2, Akt, 26s proteasome, histone H3 and PKC (Figure 5, Table 2). The network with the second largest number of down-regulated focus genes had 16 focus genes with functions in Cell Death and Survival, Embryonic Development, Cellular Development. Focus genes were ARMCX3, BUD31, DPY19L1, FAM177A1, FAM210B, GALK2, ITM2C, LSG1, LYRM7, MRPL15, NDUFAF5, SEC24A, TBC1D8B, THUMPD3, TIMMDC1 and TOMM5; they were related to UBC (ubiquitin)(Figure 6, Table 2).
2.2. Microarray analyses of the hypercholesterolemia plus sham group.
The gene expression profile in the MCA of the hypercholesterolemia plus sham group was compared with that of sham controls on a normal diet. After unknown and repeated genes were omitted, 107 up-regulated and 351 down-regulated genes (greater than 4-fold change) were found (Figure 2). Among the highly up-regulated genes in the MCA of the hypercholesterolemia plus sham group compared to sham controls were SLFN14, CA1, and LOC100357902 (Table 3). Among the highly down-regulated genes were LOC100125984, PFDN5 and CUL3 (Table 4).
The IPA network with the ‘largest number of up-regulated focus genes’, contained 21 focus genes with functions in Cell Death and Survival, Lipid Metabolism, Small Molecule Biochemistry. Focus genes in this network were ATP7A, C11orf71, C1orf51, CA1, CA2, CCNB3, CMTM2, CORIN, DTX3, EPHA1, FAM19A4, GTF2E2, MEP1B, NAA25, PALM2, RNASE1, SOAT2, SP110, TENM4, TSPAN33 and UHRF1BP1. They were related to the ‘node molecules’, APP and tretinoin (Figure 7, Table 3). The next network of up-regulated focus genes had 18 focus genes, with functions in Organ Morphology, Reproductive System Development and Function, Developmental Disorder. Focus genes were APBB3, AQP1, CD2, FANCC, FCRL3, FSHR, IAPP, IKBKE, MAP3K4, NR1D1, OGT, PSMC3IP, SERPINB2, SP100, SYK, TAF15, TMEM173 and TRAF3IP1; they were related to P38 MAPK, ERK1/2, NFkB, SERPINB2, Akt, interferon alpha and VEGF (Figure 8, Table 3).
The network with the largest number of down-regulated focus genes contained 26 focus genes with functions in Tissue Development, Connective Tissue Disorders, and Developmental Disorder. Focus genes in this network were ARNT, BMF, CADM1, CDC37L1, DNAJB4, DNAJC6, ELOVL5, GPBP1, GTF2F2, INSIG1, INSIG2, KDM4A, KIF20A, NUMB, PHIP, PKN2, PSMC6, PSMD4, PVRL3, RNF168, RPN1, SNAP25, SNTA1, SPRR3, STX2 and TOP2B. They were related to Ubiquitin, 26s Proteasome and Akt (Figure 9, Table 4). The next network of down-regulated focus genes had 25 focus genes with functions in Organ Morphology, Visual System Development and Function, Lipid Metabolism. Focus genes were ABLIM1, ACTA1, ATAD2, CDC73, CRYAA, CYP7A1, DHX9, HNRNPC, ME1, MLL3, MYBBP1A, PABPC4, POU2F3, SHROOM3, SMARCA5, SMARCAD1, SYT12, TIAL1, TMPO, TRPM7, USP3, WDR61, XRN1, YWHAQ and ZBTB44; they were related to histone H3 and F Actin (Figure 10, Table 4).
2.3. Microarray analyses of the hypertension plus hypercholesterolemia group.
The gene expression profile in the MCA of the hypertension plus hypercholesterolemia group was compared with that of sham controls on a normal diet. After unknown and repeated genes were omitted, 222 up-regulated and 133 down-regulated genes (greater than 4-fold change) were found (Figure 2). Among the highly up-regulated genes in the MCA of the hypertension plus hypercholesterolemia group compared to sham controls were EPHA1, SP110, SLFN14 (Table 5). Among the highly down-regulated genes were FOXN1, TNFRSF11B and GAPDHS (Table 6).
The IPA network with the ‘largest number of up-regulated focus genes’, contained 22 focus genes with functions in Tissue Development, Connective Tissue Disorders, Developmental Disorder. Focus genes in this network were ALAS2, CCL19, CD2, CD4, CD244, CLEC1B, CNP, DHRS9, FKBP1B, IAPP, KLF13, LTN1, MS4A2, RASGRP4, RNASEL, SLC5A1, SPTA1, SYK, TMEM173, TRAF3IP1, TYMP and UBASH3B. They were related to ERK1/2, Interferon alpha, IL12 complex and SYK (complex), CD2, CD4 and CD244 (Figure 11, Table 5). The next network of up-regulated focus genes had 18 focus genes, with functions in Organ Morphology, Visual System Development and Function, Lipid Metabolism. Focus genes were CA2, CDH17, COL17A1, ELOVL3, FANCC, FCRLA, FLT3, HRH1, MAP3K4, MEP1B, MMP1, NFkBID, NR1D1, PIGR, RET, SERPINB2, SPINK1 and TINF2; they were related to P38 MAPK, NFkB, SERPINB2, MMP1 and TNF (Figure 12, Table 5).
The network with the largest number of down-regulated focus genes contained 21 focus genes with functions in Cardiovascular Disease, Cellular Assembly and Organization, Post-Translational Modification. Focus genes in this network were ARNT, CCT2, ELAVL4, HNRNPC, KIF20A, ME1, NCALD, NRGN, PDK4, PFDN5, PLN, PPP1R8, PPYR1, SHROOM3, SNAP25, SNTA1, SSB, STMN2, SYT12, TTN and WAC. They were related to ERK, Akt, PKC, Vegf, actin and insulin. (Figure 13, Table 6). The next network of down-regulated focus genes had 20 focus genes with functions in Endocrine System Disorders, Gastrointestinal Disease, and Hereditary Disorder. Focus genes were BMF, CDX1, CKM, CRYAA, DNAJB4, DNAJC6, GTF2E2, IFIH1, IFRD1, INSIG2, PAX4, PLP1, POU2F3, PSMD4, RPN1, SAP30, SMARCA5, TANK, TIAL1 and WDR61; they were related to P38 MAPK, NFkB, 26S proteasome, histone H3, interferon alpha and IL12 (Figure 14, Table 6).
2.4. Microarray analyses of the common area between hypertension only- and hypercholesterolemia plus sham groups.
The gene expression profile in the common area between the hypertension only- and hypercholesterolemia plus sham groups was also compared with that of sham controls on a normal diet (Fig. 2A). After unknown and repeated genes were omitted, 18 up-regulated and 13 down-regulated genes (greater than 4-fold change) were found (Figure 2). Among the highly up-regulated genes in the MCA of the hypertension only group compared to sham controls were Nibrin like (LOC100352398), TAF15 and ANKAR (Table 7). Among the highly down-regulated genes in the MCA of the hypertension only group were FOXN1, ribosomal protein S3a-like and ADAMTS17 (Table 8).
A single network of up-regulated focus genes was found, which contained 13 focus genes with functions in Drug Metabolism, Endocrine System Development and Function, Lipid Metabolism. Focus genes in this network were ASB4, DIS3L2, DZANK1, FANCC, GUCY2D, MEP1B, NAA25, RNASE1, RXFP2, SERPINB2, SIPA1L3, TAF15 and TESK2. They were related to UBC, APP, SERPINB2, TNF and HNF4A (Figure 15, Table 7).
A single network of down-regulated focus genes was found, which contained 11 focus genes with functions in Cell Morphology, Embryonic Development, and Cellular Compromise. Focus genes were ADAMTS17, BCCIP, FAM177A1, FOXN1, HPGDS, LSG1, MRPL15, PPIG, PSMD4, RPL26 and TOMM5. They were related to UBC (Figure 16, Table 8).
2.5. Microarray analyses of the ‘exclusive area’ in the hypertension plus hypercholesterolemia group.
The gene expression profile in the exclusive area of the hypertension plus hypercholesterolemia group was compared with that of sham controls on a normal diet (Fig. 2A). After unknown and repeated genes were omitted, 132 up-regulated and 22 down-regulated genes (greater than 4-fold change) were found (Figure 2). Among the highly up-regulated genes in the MCA of the hypertension plus hypercholesterolemia compared to sham controls were SLFN, MRS2 and HEAT repeat containing (LOC100357872) (Table 9). Among the highly down-regulated genes in the MCA of the hypertension group were SST, ADAM6, and PRLR (Table 10). The panel of genes was analyzed by IPA.
The IPA network with the largest number of up-regulated focus genes contained 20 focus genes with functions in Cell Death and Survival, Cellular Compromise, Inflammatory Response. Focus genes in this network were CCL19, CD2, CD4, CD244, CDH17, CGN, CNP, COL17A1, DHRS9, FLT3, IQUB, KLF13, LTN1, MS4A2, PIGR, RASGRP4, RET, RNASEL, TYMP and UBASH3B. They were related to P38 MAPK, ERK 1/2, interferon alpha and CD2, CD4 and CD244 (Figure 17, Table 9). The next network of up-regulated focus genes had 14 focus genes with functions in Cell Cycle, Nervous System Development and Function, Cell Death and Survival. Focus genes were C5orf28, CDK15, FAM71C, GBA3, GLB1L3, IRX2, LRRTM4, NAA25, NAV2, PRPF18, PSRC1, PTCH2, SLC13A1 and STAMBPL1; they were related to UBC and APP (Figure 18, Table 9).
The network with the largest number of down-regulated focus genes contained 10 focus genes with functions in Digestive System Development and Function, Hepatic System Development and Function, Organ Morphology. Focus genes in this network were ELAVL4, GFRA4, KCNK18, PAX4, PDK4, POU3F4, PRLR, SPHKAP, SST and STMN2. They were related to MAPK, ERK and insulin (Figure 19, Table 10). The next network of down-regulated focus genes also had 10 focus genes with functions in Metabolic Disease, Gene Expression, and Cellular Compromise. Focus genes were INHBE, KIAA1549, MARCH6, MOBP, NRGN, OLFM3, PLP1, SEMA4D, SULT4A1 and ZC3H7B; they were related to UBC and APP (Figure 20, Table 10).
3. Electron Microscopy of the MCA
The MCA of sham operated rabbits on a normal diet showed continuous healthy appearing endothelial cells (Figure 21A). In comparison, the MCA of hypertension only rabbits contained pyknotic endothelial cells (Figure 21B), while that of hypercholesterolemia plus sham rabbits showed large intracellular vacuoles in endothelial cells (Figure 21C). The above changes were exacerbated in the hypertension plus hypercholesterolemia rabbits, and pyknotic endothelial cells, breaks in the basement membrane, and large extracellular spaces were present between the basement membrane and underlying smooth muscle cells (Figure 21D, E). In addition, subendothelial foam cells were observed (Figure 21E, F) consistent with early atherosclerotic changes. The tunica media and tunica adventitia had a normal appearance.
(A) Sham operated rabbit on a normal diet showing continuous endothelial cells (EC) (B) Hypertension only rabbit, showing a pyknotic cell (arrow) in the endothelial layer (EC). (C) Hypercholesterolemia plus sham rabbit, showing large intracellular vacuoles (V) in endothelial cells. (D) Hypertension plus hypercholesterolemia rabbit, showing breaks in the basement membrane (BR), and a large extracellular space (S) between the basement membrane and the underlying smooth muscle cells. (E) Hypertension plus hypercholesterolemia rabbit, showing a pyknotic cell among the endothelial layer (arrow), and presence subendothelial foam cells (FC). (F) Higher magnification of a foam cell in E, showing intracellular vacuoles, and extracellular spaces (S) containing collagen fibrils. Scale: A = 1 µm, B–D = 0.5 µm, E = 2 µm, F = 0.2 µm.
4. Vascular Changes in the Aorta
4.1. RT-PCR.
HNF4A mRNA expression was increased in the aorta of the hypercholesterolemia plus sham-operated group- and hypertension plus hypercholesterolemia group (3.64 and 2.25-fold change respectively), compared to controls on a normal diet (Figure 22A).
(A) Real-time RT-PCR analyses of HNF4A in the aorta of control, hypercholesterolemia plus sham, and hypertension plus hypercholesterolemia rabbits. The mean and standard error are shown. *p<0.05 vs. controls by one-way ANOVA with Bonferroni’s multiple comparison post-hoc test (n = 4 in each group). (B) Western blot analyses of HNF4A in the aorta of control, hypercholesterolemia plus sham and hypertension plus hypercholesterolemia rabbits. (C) Densitometric analyses of HNF4A protein, normalized to ß-actin. The mean and standard error are shown. *p<0.05 vs. control by one-way ANOVA with Bonferroni’s multiple comparison post-hoc test (n = 3 in each group). Abbreviations as in Fig. 1.
4.2. Western blot analyses.
The antibody to HNF4A detected a 53 kDa band in homogenates of the aorta consistent with the expected molecular weight of the protein (Figure 22B). Increased density of the HNF4A band relative to beta actin was found in homogenates from hypercholesterolemia plus sham- and hypertension plus hypercholesterolemia group compared to controls, indicating up-regulation of HNF4A protein expression after exposure to hypertension and/or hypercholesterolemia (Figure 22C).
4.3. Histochemistry and immunohistochemistry.
The general structure of the aorta was examined by Masson’s Trichrome staining (Figure 23A–C). Hypercholesterolemia plus sham rabbits as well as the hypertension plus hypercholesterolemia rabbits showed neointimal formation along part of the circumference of the vessel. This was associated with migration of red-staining, smooth muscle cells from the tunica media into the neointima (Figure 23C). The changes were more pronounced in the hypertension plus hypercholesterolemia than the hypercholesterolemia plus sham rabbits (Figure 23A–C). The tunica media and tunica adventitia had a normal appearance.
A, D, G: Rabbits on normal diet. B, E, H: Hypercholesterolemia plus sham group. C, F, I: Hypertension plus hypercholesterolemia group. A-C: Aorta of rabbits stained by Masson’s Trichrome. Increased thickness of the neointima (NI) is seen in the hypercholesterolemia plus sham group (B, arrow). The changes are exacerbated in the hypertension plus hypercholesterolemia group (C, arrow). SM = smooth muscle cells in the neointima. D, E, F: Aorta of rabbits immunostained with a mouse monoclonal antibody to HNF-4A. Very little or no labeling is present in normal rabbits, but dense staining is observed in endothelial cells in the hypercholesterolemia plus sham, and hypertension plus hypercholesterolemia rabbits (arrows). G, H,I: Higher magnification of the aorta of rabbits immunostained with mouse monoclonal antibody to HNF-4A, showing dense staining in endothelial cells of hypercholesterolemia plus sham, and hypertension plus hypercholesterolemia rabbits (arrows). Scale: A-F = 200 µm, G-I = 70 µm.
Immunostaining of the aorta with HNF4A antibody showed that the endothelial layer of hypercholesterolemia plus sham group and the hypertension plus hypercholesterolemia group were densely stained for HNF4A, compared to controls (Figure 23D–I). Immunolabel was observed in the nucleus and cytoplasm of endothelial cells and other cells near the endothelial layer. No staining was observed in the tunica media or adventitia (Figure 23D-I). These results indicate that increased HNF4A gene expression in the aorta occurred mainly in endothelial cells.
Discussion
The present study was carried out to elucidate differential gene expression changes in the MCA of rabbits exposed to two stroke risk factors, i.e. hypertension and/or hypercholesterolemia. Of the DEGs in the MCA that were altered by a single risk factor, hypertension alone vs. sham controls on a normal diet, FAM167A had the highest fold change, followed by CERS3 and FAM53C. FAM167A encodes a ubiquitously expressed gene, the function of which remains unknown. CERS3 (ceramide synthase 3) catalyzes the condensation of sphinganine and fatty acyl-coenzyme A to form dihydroceramide, which is oxidized to ceramide [30]. Among the down-regulated DEGs in the MCA of the hypertension only group were FOXN1, NSRP1 and THUMPD3. Forkhead transcription factor is essential for thymus development [31] and keratinocyte differentiation [32].
Of the DEGs in the MCA that were up-regulated in the hypercholesterolemia plus sham group vs. sham controls on a normal diet, SLFN14 had the largest fold change, followed by CA1 and Gap protein alpha-3 protein-like (LOC100357902). SLFN14 is part of the Schlafen family of proteins which have growth regulatory properties [33]. CA1 (carbonic anhydrase I) is a member of the carbonic anhydrase family that catalyzes the hydration and dehydration of CO2/H2CO3 [34] and gene mutation is associated with rheumatoid arthritis [35].
Among the DEGs that were down-regulated in the hypercholesterolemia plus sham group vs. sham controls were beta tropomyosin (LOC100125984), PFDN5 and CUL3. The latter is a member of the cullin protein family [36], [37] involved in ubiquitination [38], and gene polymorphism is associated with hypertension [39].
Of the DEGs in the MCA that were up-regulated in the hypertension plus hypercholesterolemia group vs. sham controls on a normal diet, EPHA1 had the largest fold change, followed by SP110, and SLFN14. EPHA1 (Ephrin receptor A1) has recently been identified in large-scale genome-wide association studies to be one of the risk genes for late onset Alzheimer’s disease (AD) [40], [41]. SLFN14 has been mentioned in the hypertension only group.
Among the DEGs that were down-regulated in the hypertension plus hypercholesterolemia group were FOXN1, TNFRSF11B, and GAPDHS. TNFRSF11B (tumor necrosis factor receptor superfamily, member 11b) is the gene encoding osteoprotegerin, a member of the tumor necrosis factor receptor superfamily of cytokines [42] involved in bone resorption [43] and vascular diseases [44], [45]. Gene polymorphism of TNFRSF11B is a risk factor for ischemic stroke [46]. FOXN1 has been mentioned in the hypertension only group.
Of the DEGs in the that were up-regulated in common between the hypertension only- and hypercholesterolemia plus sham groups (both vs. sham controls), Nibrin like (LOC100352398) showed the largest fold change, followed by TAF15, and ANKAR. TAF15 (TATA box binding protein associated factor 15) is a member of the FET family of RNA-binding proteins [47]. ANKAR (ankyrin and armadillo repeat containing) is one of the genes affected in aortic dilatation/dissection [48].
Among the DEGs that were down-regulated in common, between the hypertension only, and hypercholesterolemia plus sham groups (both vs. sham controls) were FOXN1, Ribosomal protein S3-like (LOC100354966) and ADAMTS17 (ADAM metallopeptidase with thrombospondin type 1 motif, 17). The ADAMTS family of genes is involved in cancer, arthritis and coagulation [49], and variants of ADAMTS17 are associated with pediatric stroke [50].
The network in the MCA with largest number of up-regulated focus genes affected by hypertension showed many focus genes related to the ‘node molecule’, ubiquitin, a regulatory protein that directs other proteins to the proteasome [51]. Apart from chronic neurodegenerative diseases, the ubiquitin-proteasome system is implicated in brain ischemia by inducing cell damage or leukocyte infiltration into the brain [51]. The network with the second largest number of up-regulated molecules was related to P38 MAPK and ERK. P38 MAPK (mitogen-activated protein kinase) is a member of the MAPK family involved in stress-related signal transductions [52], and sustained activation can result in apoptosis in various cell types [53], [54], [55]. Inhibition of P38 activity is reported to reduce infarct volume and neurological deficits [52], [56] as well as cytokine expression after stroke [52]. ERK1/2 (extracellular signal-regulated kinase 1/2) is a well-characterized member of the MAPK family that is activated by mitogens or stressors, and plays an important role in cell differentiation and proliferation [57], [58]. Phosphorylated ERK1/2 is increased after cerebral ischemia/reperfusion, and the ERK pathway is involved in both neuroprotection and cell death [58]. Other focus genes in this network were related to NF-κB, SERPINB2, MMP1 and APP. NF-κB (nuclear factor-kappa B) is a central regulator of inflammation and apoptosis [59] and is active in many chronic inflammatory diseases including atherosclerosis [60]. It could have damaging effects in cerebral ischemia [61], [62], and inhibition of NF-κB decreases neointimal formation [63], [64], [65] and reduces infarct volume and neurological deficits after stroke [66]. On the other hand, NF-κB activation could also be neuroprotective [67], [68], as it participates in cell death/survival pathways through regulation of pro- and anti-apoptotic genes [69], [70]. SERPINB2 (serpin peptidase inhibitor, clade B (ovalbumin), member 2), also known as plasminogen activator inhibitor (PAI) type 2 is a physiological inhibitor of urokinase plasminogen activator (uPA) [71]. Increased SERPINB2 expression is found in the AD brain [72], and after brain ischemia or trauma, particularly in the basement membrane and endothelial cells of vessels adjacent to the lesion [73]. MMP1 (matrix metallopeptidase 1) belongs to a family of protein-digesting enzymes that degrades the extracellular matrix in both physiological and pathological conditions including stroke [74]. MMP1 is increased in atherosclerotic plaques [75] and gene polymorphism is suggested to influence the risk of coronary heart disease [76]. APP (β-amyloid precursor protein) can be processed by an amyloidogenic pathway to form A-beta. The latter and vascular risk factors [77], [78] play important roles in the pathogenesis of AD [79], [80], and endothelial dysfunction in APP overexpressing mice increases the susceptibility of the brain to AD pathology [81] and cerebral ischemia [82].
The network in the MCA with the largest number of down-regulated focus genes affected by hypertension was related to MAPK, ERK 1/2, Akt, 26s proteasome, histone and PKC, while the network with the second largest number of down-regulated focus genes was related to UBC. Akt is a serine/threonine kinase that is activated by PI3K in various growth factors-mediated signaling cascades [83]. The PI3K/Akt signaling pathway is important in mediating cell survival [83], [84] and Akt activity is shown to confer neuroprotection after ischemic brain injury [85], [86]. PKC (protein kinase C) is a serine-threonine kinase family that is important in regulating cellular functions, and several isozymes of PKC such as PKC<$>\raster="rg1"<$>, PKCδ and PKCγ, are associated with cerebral ischemic and reperfusion injury [87], [88]. The use of PKCδ peptide inhibitors is reported to alleviate reperfusion injury and reduce stroke infarct size [87], [88], [89]. 26s Proteasome is an essential component of the ubiquitin-proteasome system which functions to degrade cellular proteins [90]. The exact role of the ubiquitin-proteasome system in cerebral ischemia is at present unclear, and deleterious effects of proteasome malfunction, as well as beneficial effects of proteasome inhibition on cerebral ischemia have been reported [51], [90]. Histones affect gene transcription by binding to DNA; hence changes in histone H3 may affect the expression of downstream molecules in vessels during hypercholesterolemia. Interestingly, promising outcomes from the use of histone deacetylase (HDACs) inhibitors have been reported in preclinical stroke models [91].
Gene network analysis of the MCA after hypercholesterolemia (plus sham operation), surprisingly, showed very similar networks as that the hypertension only group. This was despite a relatively low percentage of genes in the common area between these two conditions (20.8% of hypertension genes and 6.8% of hypercholesterolemia genes were in the common area, respectively). The results suggest recruitment of different focus genes that are related to similar ‘node molecules’, as in the following example: the network in the MCA with largest number of up-regulated focus genes affected by hypercholesterolemia showed many molecules related to APP. This is similar to hypertension only rabbits, and could indicate synergism of the two risk factors in affecting the expression of molecules related to APP. Other focus genes were related to tretinoin or all-trans retinoic acid (ATRA) [92], a molecule known to modulate A-beta associated memory deficits and neuropathological alterations in animal models of AD [92], [93].
The network with the second largest number of up-regulated focus genes also had many similarities with the hypertension only group, with P38 MAPK, ERK 1/2, NFkB, SERPINB2 and Akt being central players, together with focus genes related to interferon alpha and VEGF. Interferon alpha is a member of a family of nonspecific antiviral agents with immunomodulatory and cytostatic properties [94]. Although other isoforms of the interferon family such as interferon beta and gamma are associated with atherosclerosis [94], a possible role of interferon alpha in this condition is yet unknown. Vegf (vascular endothelial growth factor) is involved in conditions such as atherosclerosis, cerebral edema, brain and vascular repair following ischemia [95], and plasma vegf values are increased immediately after stroke [96].
The network in the MCA with largest number of down-regulated focus genes affected by hypercholesterolemia is related to ubiquitin, 26s proteasome and Akt, and the network with the second largest number of down-regulated focus genes is related to histone H3 and F actin. These changes in ubiquitin, proteasome, and histone H3 are very similar to that of hypertension only animals. Down-regulation of genes related to actin may affect process outgrowth or motility of vascular cells, and actin cytoskeleton signaling is one of the functional pathways that are related to male-specific ischemic stroke genes [97].
The network in the MCA with largest number of up-regulated focus genes affected by hypertension plus hypercholesterolemia showed many molecules related to ERK 1/2, interferon alpha, IL12, SYK, CD2, CD4, and CD244. IL12 (interleukin 12) is a proinflammatory and immunomodulatory cytokine [98] released in response to tissue injury [99]. Elevated serum levels of IL12 are observed in patients with acute myocardial infarction [100], traumatic brain injury [101] and ischemic stroke [102]; in addition, IL 12 signaling is related to female-specific ischemic stroke genes [97]. SYK (spleen tyrosine kinase) is a non-receptor tyrosine kinase [103] involved in signaling cascades in platelets [104]. The use of inhibitors of SYK is a potential treatment for occlusive vascular disease, due to its effect in modulating platelet aggregation and thrombus formation [104]. SYK also phosphorylates tau [105] and α-synuclein [106]. CD2 (CD2 molecule) is a member of the immunoglobulin superfamily and mediates the activation of T and natural killer cells [107]. CD4 (CD4 molecule) is expressed on the surface of T cells [108] and CD4+ T cells are regulators of humoral and cellular immune response [109]. Lack of CD4+ T cells is associated with decreased lesion size after stroke [110]. CD244 (CD244 molecule, natural killer cell receptor 2B4) is part of the ‘signaling lymphocyte activation molecule’ (SLAM) family of receptors [111] and is present on natural killer cells, activated CD8+ T cells, and monocytes [112], [113]. It is postulated that CD244 may be involved in a pathway that promotes inflammatory neurological disease [114]. The network with the second largest number of up-regulated focus genes was related to P38 MAPK, NFkB, SERPINB2, MMP1 and Tnf (family). TNF (tumor necrosis factor) plays a key role in increasing the expression of inflammation related genes in atherosclerosis [115], and expression is increased in brain during ischemia [116] or in patients who suffer intracerebral hemorrhage [117]. Antagonism of the TNF-α receptor modulates neurovascular injury and improves neurobehavioral outcomes, after intracerebral hemorrhage in mice [118].
The network in the MCA with largest number of down-regulated focus genes affected by hypertension plus hypercholesterolemia showed many molecules related to ERK, Akt, PKC, Vegf, actin, and insulin. Diabetes mellitus and insulin resistance increase the risk of ICLAD and stroke [119], [120], [121], [122], [123]. Moreover, patients with diabetes show poorer post-stroke functional outcomes in terms of mortality [124], [125] and cognition [126]. These findings may be related to the effect of insulin on activation of NFkB and generation of pro-inflammatory factors involved in atherogenesis [127]. The network with the second largest number of down-regulated focus genes was related to P38 MAPK, NFkB, 26s proteasome, histone H3, interferon alpha and IL12.
The common area between the hypertension only- and hypercholesterolemia plus sham groups showed up-regulated focus genes related to UBC, APP, SERPINB2, TNF and HNF4A, and down-regulated focus genes related to UBC. HNF4A (hepatocyte nuclear factor 4 alpha) is a ligand activated nuclear transcription factor that regulates the expression of many genes involved in lipid transport and glucose metabolism and are associated with cell cycle, immunity, apoptosis, stress response and cancer [128]. Increased expression of HNF4A was shown by RT-PCR and Western blot, and the protein immunolocalized to endothelial cells in the aorta. Since HNF4A suppresses hepatocyte proliferation in adult mice [129], increased expression may likewise affect the turnover of endothelial cells. The effect of this on atherosclerosis is unclear, although excess proliferation of vascular smooth muscle cells is known to have an atherogenic effect [130].
The hypertension plus hypercholesterolemia ‘exclusive’ area showed up-regulated and down-regulated pathways, related to many of the node molecules mentioned above. This area is tentatively interpreted as containing genes that are exacerbated by two risk factors, and the effects tends towards recruitment of additional molecules into existing networks rather than initiation of new networks.
An ischemic cerebrovascular event or transient ischemic attack is a risk factor for a subsequent event [21], [22], [131]. The reasons for this are multifactorial [132] and may be partly due to presence of existing atherosclerotic lesions. The present findings extend these concepts to the gene network level, and delineates pathways related to NF-κB and TNF that are involved in inflammation and atherosclerosis [60], [133], as well as focus genes related to ubiquitin, proteasome, histone, HNF4A, insulin and APP. It is hoped that these could provide a framework for better understanding of pathophysiological mechanisms, and development of new therapies for ICLAD.
Author Contributions
Conceived and designed the experiments: WYO PTHW. Performed the experiments: WYO MPEN SLJ YJW. Analyzed the data: WYO SYL MPEN KT. Contributed reagents/materials/analysis tools: WYO PTHW. Wrote the paper: WYO SYL MPEN KT.
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