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Physiol. Genomics 36: 15-23, 2008. First published September 23, 2008; doi:10.1152/physiolgenomics.90296.2008
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Received 23 July 2008; accepted in final form 21 September 2008.
Physiological Genomics 36:15-23 (2008)
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Transcriptomic analysis of PPAR{alpha}-dependent alterations during cardiac hypertrophy

Pascal J. H. Smeets 1, Heleen M. de Vogel-van den Bosch 1, Peter H. M. Willemsen 1, Alphons P. Stassen 2, Torik Ayoubi 2, Ger J. van der Vusse 1 and Marc van Bilsen 1

1 Department of Physiology, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
2 Clinical Genomics, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
Peroxisome proliferator-activated receptor (PPAR){alpha} regulates lipid metabolism at the transcriptional level and modulates the expression of genes involved in inflammation, cell proliferation, and differentiation. Although PPAR{alpha} has been shown to mitigate cardiac hypertrophy, knowledge about underlying mechanisms and the nature of signaling pathways involved is fragmentary and incomplete. The aim of this study was to identify the processes and signaling pathways regulated by PPAR{alpha} in hearts challenged by a chronic pressure overload by means of whole genome transcriptomic analysis. PPAR{alpha}–/– and wild-type mice were subjected to transverse aortic constriction (TAC) for 28 days, and left ventricular gene expression profile was determined with Affymetrix GeneChip Mouse Genome 430 2.0 arrays containing >45,000 probe sets. In unchallenged hearts, the mere lack of PPAR{alpha} resulted in 821 differentially expressed genes, many of which are related to lipid metabolism and immune response. TAC resulted in a more pronounced cardiac hypertrophy and more extensive changes in gene expression (1,910 and 312 differentially expressed genes, respectively) in PPAR{alpha}–/– mice than in wild-type mice. Many of the hypertrophy-related genes were related to development, signal transduction, actin filament organization, and collagen synthesis. Compared with wild-type hypertrophied hearts, PPAR{alpha}–/– hypertrophied hearts revealed enrichment of gene clusters related to extracellular matrix remodeling, immune response, oxidative stress, and inflammatory signaling pathways. The present study therefore demonstrates that, in addition to lipid metabolism, PPAR{alpha} is an important modulator of immune and inflammatory response in cardiac muscle.

microarray; lipid metabolism; inflammation; immune response


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
PEROXISOME PROLIFERATOR-activated receptor (PPAR){alpha} (NR1C1) is a ligand-activated transcription factor belonging to the nuclear hormone receptor family (32). PPAR{alpha} is primarily known for its pivotal role in the transcriptional regulation of lipid metabolism (1). Together with its dimerization partner retinoid X receptor (RXR), PPAR{alpha} binds to cis-regulatory elements, the so-called PPAR-response elements (PPREs), of many genes involved in lipid uptake and metabolism. Via this transactivation mechanism, PPAR{alpha} increases the expression of fatty acid (FA)-handling genes in tissues with high oxidative capacity, including cardiac muscle (43).

In addition, PPAR{alpha} has been shown to modulate the expression of genes involved in nonmetabolic processes, such as inflammation (6), cell proliferation and differentiation (34), and the response to oxidative stress (22). PPAR{alpha} is thought to suppress inflammation through interference with components of proinflammatory pathways, like nuclear factor-{kappa}B (NF-{kappa}B) and activator protein-1 (AP-1), a process referred to as transrepression (33). Currently, it is less clear whether the modulation of cell proliferation involves transactivation or transrepression primarily. In some cases, PPAR{alpha}-mediated transactivation of cell cycle inhibitors has been demonstrated (12, 49).

Inflammatory processes are likely to play a prominent role in the challenged heart, for instance, during cardiac hypertrophy, as supported by the observations that activation of NF-{kappa}B is intricately linked to cardiomyocyte hypertrophy (26) and that mice overexpressing TNF-{alpha} develop hypertrophic cardiomyopathy (16). Furthermore, fibroblast proliferation, extracellular matrix (ECM) remodeling, and oxidative stress all contribute to the deterioration of cardiac function (14). Therefore, in view of the pleiotropic effects of PPAR{alpha}, it is conceivable that PPAR{alpha} modulates tissue remodeling during cardiac hypertrophy. Indeed, treatment of aorta-banded rats with the PPAR{alpha} ligand fenofibrate has been reported to attenuate cardiac hypertrophy (19). Deletion of PPAR{alpha} in mice resulted in a normal cardiac function at a young age, but the hearts showed an increased vulnerability under conditions of stress, like β-adrenergic stimulation (27), ischemia-reperfusion (41), or transverse aortic constriction (TAC) (39). However, the outcome of studies examining the role of PPAR{alpha} during cardiac hypertrophy is not entirely clear, because cardiac-specific overexpression of PPAR{alpha} resulted in impaired function of the murine heart (10).

The collective findings suggest that PPAR{alpha} plays a decisive role in the development of hypertrophy, affecting the functional outcome of the heart. Unfortunately, information on the nature of PPAR{alpha}-dependent processes in cardiac hypertrophy is fragmentary and incomplete. Therefore, the primary aim of this study was to identify the processes and signaling pathways regulated by PPAR{alpha} in hearts challenged by a chronic pressure overload by means of whole genome transcriptomic analysis. Second, we wanted to gain insight into how PPAR{alpha} modulates the identified processes, e.g., by transactivation or by transrepression. To this end, wild-type and PPAR{alpha}–/– mice were sham operated or subjected to TAC for 28 days. Left ventricular (LV) gene expression profile was determined by using Affymetrix GeneChip Mouse Genome 430 2.0 arrays containing >45,000 probe sets (covering >34,000 mouse genes) to detect PPAR{alpha}-related differences in cardiac gene expression under basal conditions and after imposition of a sustained hemodynamic stress.


   METHODS
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 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 
Experimental Animals
Three-month-old male PPAR{alpha}–/– mice (25) and age-matched wild-type C57BL6/J mice (Charles River) were used in this study. The PPAR{alpha}–/– mice were backcrossed for >10 generations into a pure C57BL6/J background. Mice were kept on a 12:12-h light-dark cycle in temperature-controlled rooms and had ad libitum access to water and standard lab chow (Ssniff R/M-H, Ssniff, Soest, Germany). Animal experiments were approved by the Institutional Animal Care and Use Committee of Maastricht University and compliant with the guidelines of the Guide for the Care and Use of Laboratory Animals (NIH Pub. No. 85-23, revised 1996).

Pressure Overload-Induced Hypertrophy
The surgical procedure of TAC has been previously described (37). Briefly, mice were anesthetized with xylazine (5 mg/kg sc) and ketamine (100 mg/kg im). Anesthesia was maintained by isoflurane inhalation (1.5–2.5%). After the chest was opened, the transverse aorta of PPAR{alpha}–/– (n = 4) and wild-type (n = 4) mice was ligated between the truncus brachiocephalicus and the left common carotid artery by tying a 6-0 silk suture against a 25-gauge needle. Sham-operated PPAR{alpha}–/– (n = 4) and wild-type (n = 4) mice underwent the same procedure without ligation of the aorta. Animals recovered at 30°C for 24 h and were injected with the analgesic buprenorphine (Temgesic, 0.1 mg/kg sc). Mice were killed 28 days after TAC or sham operation. The heart was excised and rinsed, and atria were removed. Hypertrophy was assessed by determining total ventricular weight (VW), which was normalized to body weight or tibia length. Subsequently, the LV was separated from the right ventricle and snap-frozen for RNA analysis.

RNA Extraction, Labeling, and Hybridization
LV tissue was homogenized with an UltraTurrax (Janke & Kunkel, Staufen, Germany), and total RNA was isolated with TRI Reagent (Sigma) according to manufacturer's instructions and complemented with an additional wash step of 70% ethanol to increase the purity of the RNA. For all RNA samples quantity and purity were determined with the Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington, DE), and RNA integrity was determined with the Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). Five micrograms of total RNA was amplified with the One-Cycle cDNA synthesis and target labeling kit according to manufacturer's instructions (Affymetrix, Santa Clara, CA). Biotin-labeled target complementary RNA (cRNA) was fractionated and hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 arrays according to the manufacturer's instructions. On this chip, 45,101 probe sets analyze the expression of >39,000 transcripts representing >34,000 known genes.

Microarray Analysis
Affymetrix GeneChip Operating Software (GCOS, version 1.4) was used to analyze image data. For each transcript represented on the array by a probe set, the expression algorithm computed the detection call (present, absent, or marginal), the detection P value, and the signal, which is an average intensity value for each probe set. This resulted in a table with 45,101 probe sets. For each probe set the detection calls of the 16 arrays were used to determine whether the probe set was reliably detected and selected for further analysis (30). To this end, for every two groups of four arrays that were compared, the probe had to be present in at least three samples of one of these two groups. In addition, only probe sets with average signal intensity higher than 100 in one of the two groups compared was selected for further analysis. Finally, the over- or underexpression of the remaining probe sets in one of the two groups was analyzed with the class comparison method in the BRB ArrayTools software package, applying a univariate test with a random variance model. BRB ArrayTools is developed by the Biometric Research Branch of the National Cancer Institute (http://linus.nci.nih.gov/BRB-ArrayTools.html). The data set was submitted to NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nih.gov/projects/geo) with the accession number GSE12337.

To search for enrichment of specific biological processes the genes showing significant differential expression between the two groups (P < 0.0125) were classified into functional groups with DAVID (Database for Annotation, Visualization, and Integrated Discovery) according to Gene Ontology (GO; Biological Process) (7). As input, the differentially regulated probe sets (up- as well as downregulated; upregulated only; downregulated only) from each comparison were used and analyzed to all probe sets selected on call and signal intensity of the appropriate comparison. As output, enriched processes (GOTERM) with P < 0.05 were generated and the differentially expressed probe sets for each process were listed. In addition, related biological processes were clustered with the functional annotation clustering algorithms of DAVID. For each clustered process this results in an Enrichment Score, the –log value of the geometric mean of the member's P values.

Additionally, biological interaction network maps for each comparison were generated through the use of Ingenuity Pathways Analysis (IPA, Ingenuity Systems; www.ingenuity.com). This bioinformatics tool is based on the Ingenuity Pathways Knowledge Base. This large database of biological networks has been created from relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases, obtained from >200,000 peer-reviewed scientific publications. All differentially regulated probe sets with their corresponding fold change for each comparison were used as input in IPA.

Quantitative PCR Analysis
To assess the degree of hypertrophy and to verify the microarray data, quantitative PCR (qPCR) was performed on markers of hypertrophy, inflammation, and metabolism. Five hundred nanograms of total RNA was used for DNase I treatment (Sigma) and subsequent cDNA synthesis (Iscript cDNA synthesis kit, Bio-Rad, Hercules, CA). qPCR assays were performed as previously described (42). Primers used for analysis are given in Supplemental Table S1.1 Results were normalized to the geometric mean of three reference genes, i.e., cyclophilin A (CycloA), acidic ribosomal phosphoprotein P0 (ARBP), and hypoxanthine guanine phosphoribosyl transferase (HPRT), according to Vandesompele et al. (45), using qBase software (15) as described previously (39). The expression of these reference genes was not affected by genotype and intervention.

Statistics
Results from VW measurements and qPCR analysis are presented as means ± SE. Data were analyzed by one-way ANOVA and contrast analysis for multiple comparisons with SPSS 12 software (SPSS). A P value of <0.05 was considered to be statistically significant.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS AND DISCUSSION
GRANTS
 REFERENCES
 
Cardiac Hypertrophic Response of PPAR{alpha}–/– and Wild-Type Mice to TAC
In unstressed, sham-operated PPAR{alpha}–/– and wild-type mice no differences in VW were apparent (Table 1). After 28 days of TAC, VW was substantially increased in both PPAR{alpha}–/– and wild-type mice. The relative increase in VW in response to TAC was more pronounced in PPAR{alpha}–/– mice (+40%) than in wild-type mice (+16%). The difference persisted when VW was normalized to body weight or to tibia length. Consistent with this, qPCR analysis showed that the expression of the hypertrophic marker genes atrial natriuretic factor (ANF) and {alpha}-skeletal actin ({alpha}-SKA) increased after TAC in wild-type and PPAR{alpha}–/– mice, and that the increase was significantly higher in PPAR{alpha}–/– mice. These collective data point to a more pronounced hypertrophic response in PPAR{alpha}–/– compared with wild-type mice, suggesting that the absence of PPAR{alpha} is unfavorable for the pressure-overloaded heart.


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  		Table 1. Degree of hypertrophy in wild-type and PPAR{alpha}–/– mice 28 days after TAC or sham operation

 
Transcriptomic Analysis
qPCR validation of microarray analysis.
Gene expression profiling was performed on LV tissue samples of four mice per experimental group with Affymetrix GeneChip Mouse Genome 430 2.0 arrays. In each experimental group, ~17,000 filtered probe sets were selected on detection call and signal intensity (Fig. 1A). To validate the microarray data, eight genes that were either up- or downregulated in the microarray analysis as a function of genotype or TAC were also determined by qPCR. The selected genes were related to metabolism [pyruvate dehydrogenase kinase-4 (PDK4), β-oxidation enzyme hydroxyacyl-coenzyme A dehydrogenase (Hadha), acyl coenzyme A (CoA) oxidase (AOX), acyl coA synthetase (Acsl1)], ECM remodeling [matrix metalloproteinase-2 (MMP2), collagenase-3 (Col3)], and inflammation [cyclooxygenase-2 (Cox2) and interleukin-6 (IL6)]. Scatter plot analysis of the relative changes in expression as determined by qPCR and microanalysis, respectively, revealed a good correlation between the microarray and qPCR data, thereby confirming the validity of the microarray data set (Fig. 2).


Figure 1
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  		Fig. 1. Number of differentially regulated probe sets for the 4 distinct comparisons after each step of the selection procedure (A) and the number of probe sets up- or downregulated in each comparison (B). PPAR, peroxisome proliferator-activated receptor; TAC, transverse aortic constriction.

 

Figure 2
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  		Fig. 2. Scatter plot of relative changes in gene expression as determined by microarray analysis and by quantitative PCR (qPCR). Eight genes were analyzed: metabolic marker genes pyruvate dehydrogenase kinase-4 (PDK4), hydroxy-acyl CoA dehydrogenase (Hadha), acyl CoA oxidase (AOX), and acyl CoA synthetase (Acsl1) and the extracellular matrix (ECM) and inflammatory marker genes cyclooxygenase-2 (Cox2), matrix metalloproteinase-2 (MMP2), interleukin-6 (IL6) and collagen-3 (Col3). Each symbol represents the fold change of the respective gene for 1 of the 4 comparisons investigated.

 
Basal differences between PPAR{alpha}–/– and wild-type mice (comparison 1).
In the LV tissue of sham-operated, unstressed mice 821 probe sets were already found to be differentially regulated between PPAR{alpha}–/– and wild-type animals (Fig. 1A). Of these 821 probe sets, 458 were upregulated and 363 downregulated (Fig. 1B). To assess the function of the differentially regulated probe sets, overrepresented GO classes were determined with DAVID. With this unbiased approach biological processes affected by PPAR{alpha} were identified (Supplemental Table S2). In Table 2 these processes are summarized along with the other three comparisons. The annotated clusters in this table are listed alphabetically. For the purpose of comparison, the enrichment scores in Table 2 are ranked, with 1 being the highest enrichment score. The individual genes belonging to the clustered process are provided in Supplemental Table S3. When sham-operated PPAR{alpha}–/– mice and wild-type mice were compared, by far the most prominently enriched biological processes in the heart were lipid metabolism and defense mechanisms, with enrichment scores of 7.63 and 6.38, respectively (Supplemental Tables S2 and S3).


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  		Table 2. Overrepresented annotation clusters in all comparisons

 
The overrepresentation of genes involved in lipid metabolism is in line with the notion that PPAR{alpha} is a major regulator of genes involved in cardiac lipid metabolism and that PPAR{alpha}–/– mice show an impaired fatty acid catabolism (1, 43, 47). Indeed, this cluster consisted primarily of downregulated genes that are involved in intracellular FA transport [e.g., cytoplasmic FA-binding protein (FABP)] and metabolism [e.g., Acsl1; mitochondrial carnitine palmitoyl transferase I (mCPT-I)] and confirms that PPAR{alpha} plays an important role in the transactivation of these genes in the cardiac muscle.

The annotation cluster "defense mechanisms" mainly comprises genes related to antigen presentation and processing (histocompatibility related) and the immune response (complement system, interferons, chemokines). The fact that these genes are upregulated in the hearts of PPAR{alpha}–/– mice is indicative of the transrepression activity of PPAR{alpha} in these processes. In this respect it is important to note that previous investigations revealed a functional relationship between PPAR{alpha} and immune response (2, 5). PPAR{alpha} was found to repress the host defense in the small intestine (2). The latter finding correlates well with the present GO analysis, indicating that in the cardiac context a lack of PPAR{alpha} leads to enhanced expression of genes involved in cardiac immune response.

To explore in more detail the role of PPAR{alpha} in the murine heart, biological interaction networks of each comparison were constructed with IPA. In Supplemental Fig. S1A the merged biological networks in sham-operated PPAR{alpha}–/– mice compared with wild-type animals are shown. In line with the notion that PPAR{alpha} regulates cardiac lipid homeostasis, many downregulated genes involved in lipid metabolism are directly linked to PPAR{alpha}. It is of interest to note that many differentially regulated genes connections are linked to NF-{kappa}B, indicating that many of the effects identified in unstressed hearts of PPAR{alpha}-deficient mice are mediated via the PPAR{alpha}-NF-{kappa}B axis. At least three other genes, positioned at important nodes in the composite network, i.e., p38MAPK, transforming growth factor (TGF)-β, and CDKN1A, are apparently indirectly linked to PPAR{alpha}. The indirect relation between PPAR{alpha} and cyclin-dependent kinases (CDKs) is of great interest, as it points toward a role of this PPAR isoform in cell proliferation and growth. Collectively, the present findings support the notion that PPAR{alpha} is an important regulator of cardiac FA metabolism and modulator of the immune-inflammatory response in the myocardium of PPAR{alpha}–/– mice.

Cardiac hypertrophy in wild-type mice (comparison 2).
In wild-type mice, TAC-induced hypertrophy resulted in 312 (72 up; 240 down) differentially regulated probe sets (Fig. 1). Overrepresented GO processes in wild-type mice in response to TAC (comparison 2), as identified with DAVID analysis, were related to development and morphogenesis, with enrichment scores of 2.17 and 1.48, respectively (Table 2). The enrichment of these processes is indicative of the reactivation of the fetal gene program, which is a hallmark of cardiac hypertrophy (3, 17, 40), as exemplified by the upregulation of ANF and {alpha}-SKA (Table 1).

Genomewide changes in gene expression in wild-type mice after TAC have been extensively studied before (31, 36, 44). Most genes described in these studies are related to reactivation of fetal gene expression, in line with the present observations. Although genes involved in ECM organization and remodeling are also frequently found in hypertrophic hearts (31), our study did not reveal significant changes in clusters representing these processes (Table 2 and Supplemental Table S2). This might be due to the fact that the hypertrophic response in wild-type mice is relatively mild (+16%, Table 1) and that fibrosis is considered a feature of more advanced stages of cardiac hypertrophy. It is of note that from IPA analysis pivotal components of signaling pathways [e.g., p38MAPK, TGF-β, phosphatidylinositol 3-kinase (PI3K), Akt, and AP-1], which traditionally are considered to play an important role in the activation of cardiomyocyte hypertrophy (4, 23, 38), emerged as nodes in the composite network (Supplemental Fig. S1B).

Cardiac hypertrophy in PPAR{alpha}–/– mice (comparison 3).
The TAC-induced hypertrophy in PPAR{alpha}–/– mice gave rise to 1,910 differentially regulated probe sets, 1,230 of which were upregulated and 680 were downregulated (Fig. 1). This large number of probe sets (compared with comparison 2) is in line with the observation that the PPAR{alpha}–/– mice are more sensitive to chronic hemodynamic stress than wild-type mice (9, 28, 39). Moreover, the mere fact that the degree of hypertrophy is more pronounced in this group (+40%, Table 1) likely results in a larger number of genes for which the change in expression reaches the level of statistical significance. Accordingly, substantially more GO processes were overrepresented in this comparison relative to wild-type mice subjected to TAC (Table 2 and Supplemental Table S2). The most enriched processes are development, signal transduction, actin filament organization, and anion transport. The first three processes again reflect elements of the hypertrophic response. It is of note that a closer inspection of the contents of the fourth cluster (anion transport) reveals that virtually all of the differentially expressed genes in this functional group actually are procollagens (Supplemental Table S3). This finding is consistent with the upregulation of profibrotic growth factors, like connective tissue growth factor (CTGF) and TGF-β, that is seen in this comparison. Hence, the enrichment of this cluster is indicative of ECM remodeling in the hypertrophied myocardium. Previous studies mainly reported a role of PPAR{gamma} in suppressing TGF-β-mediated processes in various cell types (29, 50). The present findings suggest that PPAR{alpha} has similar effects, at least in the cardiac context. Interestingly, in a recent study (21) it was shown that PPAR{delta} may have opposite effects, because it was able to directly enhance transcription of TGF-β1 in vascular smooth muscle cells.

IPA analysis (Supplemental Fig. S1C) indicated that in the PPAR{alpha}–/– hypertrophied heart p38MAPK, tumor suppressor p53 (TP53), NF-{kappa}B, and Akt1 are important nodes in linking upregulated and downregulated genes.

The Venn diagram of Fig. 3A shows the overlap in probe sets between the two genotypes after TAC. Approximately 28% (86 of 312) of the probe sets in wild-type mice after TAC are also regulated in PPAR{alpha}–/– mice after TAC. As expected, the overlapping probe sets primarily belonged to functional groups that are important in hypertrophy (muscle development, actin filament organization) and included, among others, typical hypertrophic marker genes like ANF, {alpha}-SKA, and β-myosin heavy chain (β-MHC) and are indicative of processes not dependent on the absence or presence of PPAR{alpha} (see Supplemental Table S4 for detailed information).


Figure 3
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  		Fig. 3. Venn diagrams with numbers of overlapping and nonoverlapping probe sets. The overlap encompasses genes that are primarily regulated by genotype (PPAR{alpha}; A) or by intervention (TAC; B).

 
Genotype-related differences in pressure-overloaded hearts (comparison 4).
After imposition of a chronic pressure overload, 1,831 differentially regulated probe sets were identified when the hypertrophied hearts of PPAR{alpha}–/– and wild-type mice were compared (comparison 4) (Fig. 1A). The vast majority (83%) of these differentially expressed probe sets were upregulated, probably pointing to a diminished transrepression activity in the PPAR{alpha}–/– mouse heart (Fig. 1B). DAVID analysis revealed that processes related to immune response, defense mechanisms, response to stress, anion transport (a category mainly including genes involved in collagen synthesis), and actin filament organization were enriched (enrichment scores: 3–2) among the differentially regulated probe sets (Table 2 and Supplemental Table S2). More detailed analysis of Supplemental Table S3 indicates that in the enriched biological processes, e.g., GO term cell adhesion, genes involved in organization of the ECM, like tissue inhibitor of metalloproteinase (TIMP)-2, matrix Gla protein (MGP), and CTGF, were overrepresented in PPAR{alpha}–/– mice after TAC compared with hypertrophied wild-type hearts. PPAR{alpha} has been reported previously to beneficially affect ECM remodeling in the hypertrophied heart (8). Moreover, it has been demonstrated that the PPAR{alpha} agonist fenofibrate decreased fibrosis in mice with aldosterone-induced hypertension (24). The present findings might indicate that PPAR{alpha} modulates cardiac ECM at the gene expression level via transrepression, although other, most likely indirect mechanisms cannot be excluded. In this respect, the more pronounced hypertrophic response in PPAR{alpha}-deficient mice could also have influenced the expression of ECM-related genes. Further experimentation is required to deeply investigate this issue.

Again, the immune-related processes were highly enriched in this comparison. Examples of genes belonging to this group are histocompatibility 2, fc receptor, components of the complement system, and interferon regulatory factors. Earlier studies indicated that the immune response is affected in cardiac hypertrophy and failure. Enhanced immune activation, closely related to the inflammatory response, appeared to be a major contributor to the development of chronic heart failure, enhancing disease progression and increasing mortality (20). The association of PPAR{alpha} with the cardiac immune response represents a new mechanism as to how PPAR{alpha} may modulate cardiac disease. Activation of PPAR{alpha} is anticipated to suppress the exaggerated immune reaction during LV hypertrophy and heart failure (48). Given the recent interest in the relation between immunomodulation, inflammation, and cardiac disease (20), the regulatory role of PPAR{alpha} in this process warrants further investigation.

The combined biological interaction network (IPA analysis; Fig. 4) clearly reveals four nodes that were central in connecting many of the genes differentially expressed in the hypertrophic heart of PPAR{alpha}-deficient compared with wild-type mice. These nodes relate to two transcription factors, i.e., the inflammatory transcription factor NF-{kappa}B and the tumor suppressor TP53, and protein kinases, i.e., MAPK including p38MAPK, enzymes playing important roles in signaling pathways leading to cardiac hypertrophy (4). The central position of NF-{kappa}B in the composite network is in line with earlier studies revealing the pivotal role of NF-{kappa}B in cardiac hypertrophic growth (26, 35) and showing that activation of PPAR{alpha} inhibits NF-{kappa}B-dependent signaling via transrepression (18, 39). At present, the functional impact of mitogen-activated protein kinases and related genes in the hypertrophied heart of PPAR{alpha}–/– mice is incompletely understood, because recent studies have revealed complex roles for individual MAPK pathways in both cardiac protection and cardiac pathologies (46).


Figure 4
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  		Fig. 4. Biological interaction networks with central genes. Ingenuity Pathway Analysis (IPA) was used to search for biological networks in comparison 4 (PPAR{alpha}–/– TAC vs. wild-type TAC). In short, all differentially regulated probe sets, including fold changes per comparison, were entered into IPA. Individual genes are linked in biological networks. In these networks, differentially regulated genes are distinguished by the use of color coding (red, upregulated; green, downregulated in the PPAR{alpha}–/– TAC group compared with corresponding wild-type group; a greater intensity represents a higher degree of regulation). The biological networks obtained were merged in larger biological networks, indicating the mutual relationship between networks. As a cutoff value, networks with a significance score of >35 (P < 10–35) were chosen to be merged. IPA analysis of comparisons 1, 2, and 3 are shown in Supplemental Fig. S1.

 
When looking at genotype-related genomic effects, only 312 of the differentially expressed probe sets in unstressed hearts (sham PPAR{alpha}–/– vs. sham wild type) also emerge when comparing the two TAC groups (PPAR{alpha}–/– TAC vs. wild-type TAC) (Venn diagram, Fig. 3B; Supplemental Table S4). The overlapping probe sets often belonged to functional groups related to lipid metabolism and immune response. A large fraction of the 1,519 nonoverlapping probe sets in TAC mice are related to hypertrophy and ECM remodeling. It is of note that the functional clusters related to "response to stress" were also strongly represented in this group. A role of PPAR{alpha} in response to stress has already been observed by Ichihara and coworkers (18), demonstrating that activation of PPAR{alpha} repressed redox-regulated transcription factors, among which was NF-{kappa}B. Our microarray analysis also showed that lack of PPAR{alpha} resulted in the downregulation of antioxidant genes, e.g., superoxide dismutase (SOD)2, catalase, and glutathione transferase. This finding is consistent with the observation that several of these genes are directly activated by PPARs (11) and that the hearts of PPAR{alpha}–/– mice are more susceptible to oxidative stress (13).

In summary, the present transcriptomic analysis demonstrates that in the normal heart, in addition to regulating lipid metabolism, PPAR{alpha} is an important factor in cardiac immune response. After 28 days of increased hemodynamic load, a lack of PPAR{alpha} was associated with a more pronounced hypertrophy phenotype, accompanied by extensive changes in gene expression. NF-{kappa}B- and TP53-regulated genes were upregulated in hypertrophied hearts of PPAR{alpha}–/– mice, indicating that PPAR{alpha}, in addition to its well-established role in cardiac lipid metabolism, modulates immune-inflammatory signaling pathways and the expression of ECM genes in cardiac muscle. The association between PPAR{alpha} and the immune-inflammatory axis and genes involved in cardiac fibrosis might direct further studies to the transactivation and transrepression properties of PPAR{alpha} and to explore new opportunities for pharmacological interventions in cardiac disease.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS AND DISCUSSION
 GRANTS
REFERENCES
 
This work was supported by the Netherlands Organization for Scientific Research (NWO; 912-04-017) and EU-FP6 grant LSHM-CT-2005-018833, EUGeneHeart.


   FOOTNOTES
 
Address for reprint requests and other correspondence: M. van Bilsen, Dept. of Physiology, Cardiovascular Research Institute Maastricht, Maastricht Univ., PO Box 616, 6200 MD Maastricht, The Netherlands (e-mail: marc.vanbilsen{at}fys.unimaas.nl).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 The online version of this article contains supplemental material. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS AND DISCUSSION
 GRANTS
 REFERENCES
 

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