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Physiol. Genomics 29: 76-83, 2007. First published December 12, 2006; doi:10.1152/physiolgenomics.00159.2006
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Received 19 July 2006; accepted in final form 5 December 2006.
Physiological Genomics 29:76-83 (2007)
1094-8341/07 $8.00 © 2007 American Physiological Society

Altered expression of a limited number of genes contributes to cardiac decompensation during chronic ventricular tachypacing in dogs

Caroline Ojaimi1, Khaled Qanud1, Thomas H. Hintze1 and Fabio A. Recchia1,2

1 Department of Physiology, New York Medical College, Valhalla, New York
2 Sector of Medicine, Scuola Superiore Sant' Anna, Pisa, Italy


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Our aim was to determine the changes in the gene expression profile occurring during the transition from compensated dysfunction (CD) to decompensated heart failure (HF) in pacing-induced dilated cardiomyopathy. Twelve chronically instrumented dogs underwent left ventricular pacing at 210 beats/min for 3 wk and at 240 beats thereafter, and four normal dogs were used as control. The transition from CD to HF occurred between the 3rd and 4th wk of pacing, with end-stage HF at 28 ± 1 days. RNA was extracted from left ventricular tissue at control and 3 and 4 wk of pacing (n = 4) and tested with the Affymetrix Canine Array. We found 509 genes differentially expressed in CD vs. control (P ≤ 0.05, fold change ≥±2), with 362 increasing and 147 decreasing; 526 genes were differentially expressed in HF vs. control (P ≤ 0.05; fold change ≥±2), with 439 increasing and 87 decreasing. To better understand the transition, we compared gene alterations at 3 vs. 4 wk pacing and found that only 30 genes differed (P ≤ 0.05; fold change of ±2). We conclude that a number of processes including normalization of gene regulation during decompensation, appearance of new upregulated genes and maintenance of gene expression all contribute to the transition to overt heart failure with an unexpectedly small number of genes differentially regulated.

heart failure; pacing dog; microarray


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
OVER THE PAST YEARS OTHER authors and we have used chronically instrumented dogs with high-frequency cardiac pacing to study pathophysiological and molecular mechanisms related to the development of dilated cardiomyopathy. This model of congestive heart failure is characterized by a very predictable evolution and reproduces many key features of the human disease, including progressive ventricular chambers dilation and wall thinning, decreased contractility, neurohormonal activation, beta adrenergic desensitization, and altered metabolism (19). In particular, we could determine functional and metabolic changes occurring only between the 3rd and 4th wk of pacing, i.e., during the transition from compensated to decompensated failure (25). The marked cardiac functional impairment and systemic deterioration observed during this relatively short phase of transition suggests the occurrence of profound molecular alterations. Their identification would provide notable insights in the pathophysiology and clinical management of heart failure. Unfortunately, given the complexity of the heart failure syndrome, such molecular changes are likely very numerous and interrelated, while most studies have been focused on single or selected groups of molecules, due to the limitations of the classical methods of analysis.

More recently, global gene transcript profiling has emerged as a powerful tool for delineating complex patterns of tissue- and disease-specific gene expression and for understanding fundamental pathophysiological processes. In cardiovascular research this technology has been employed to generate hypotheses about the molecular mechanisms underlying different pathological conditions and phenotypes [e.g., myocardial infarction (27), dilated and hypertrophic cardiomyophathy (3, 9, 11, 28, 30, 31), congenital heart disease (13)] and to identify new therapeutic targets. However, while microarray analysis has reached widespread use, reproducibility of data remains a critical issue. For instance, the analysis of human myocardial tissue is affected by biological variability, concomitant etiologies, medications, age, sex, and clinical stage. Conversely, animal models with no treatment present much less confounding variables, reflect the natural history of cardiac disease, and allow an easier comparison with healthy controls. Affymetrix-based oligonucleotide microarrays for dogs have been recently rendered available. These arrays are capable of monitoring the expression of thousands of canine genes in parallel. To date, there are only a few reports on canine DNA array utilized to assess the gene expression profile of ischemic myocardium (2), spontaneous dilated cardiomyopathy (24), and tachycardia-induced heart failure (7). This latter was compared with human and murine heart failure data sets that were already deposited into a database for public use. No prior reports have explored changes occurring during the progression of heart failure.

In the present study, we utilized Affymetrix-based canine oligonucleotide microarrays to determine whether the transition from compensated to decompensated heart failure involves the altered expression of functionally-related groups of genes.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Surgical instrumentation and in vivo protocol.
We chronically instrumented 16 male mongrel dogs (25–28 kg, 1–2 yr of age) to measure left ventricular and aortic pressure and coronary flow and to place epicardial pacing leads on the left ventricular free wall as previously described (16, 23, 25). The dogs were divided in three groups: six were subjected to left ventricular pacing at 210 beats/min for 3 wk; six were paced for 210 beats/min for 3 wk and at 240 beats/min thereafter; four were not paced and used as normal controls. Hemodynamics recordings and two-dimensional and M-mode echocardiography were performed at baseline, at 3 wk of pacing and during terminal decompensation with the pacemaker turned off (16, 25). Arterial blood samples were taken at those same time points, and PO2 was measured with a blood gas analyzer. Dogs were considered in end-stage heart failure when left ventricular end-diastolic pressure reached 25 mmHg and clinical signs of severe decompensation were observed (25). To obtain cardiac tissue samples, the dogs were anesthetized with 30 mg/kg of pentobarbital sodium iv and then intubated and ventilated. The 5th intercostal space was rapidly opened to harvest a ~8-g transmural biopsy from the left ventricular anterior free wall while the heart was still beating. The harvested tissue was immediately freeze-clamped with tongs precooled in liquid nitrogen. The dog was subsequently euthanized with potassium chloride.

The protocol was approved by the Institutional Animal Care and Use Committee of New York Medical College and conforms to the current National Institutes of Health and American Physiological Society guidelines for the use and care of laboratory animals. During the entire duration of the protocols, the dogs were housed in separate cages in the Department of comparative medicine of the New York Medical College.

RNA isolation.
Total cardiac RNA was extracted from left ventricular tissue of control (n = 4), 3 wk-paced (n = 4), and decompensated heart failure dogs (n = 4) with a commercial RNA isolation kit using TRIzol (TRI Reagent; Sigma, St. Louis, MO) as described previously (22). RNA quality was assessed by electrophoresis using the Agilent Bioanalyzer 2100.

Microarray labeling and hybridization.
The microarray labeling, hybridization, and analysis procedures were described previously in detail (22). In brief, each individual sample was subjected to gene expression analysis via the Affymetrix Canine Genome Array, which was subsequently processed and scanned according to the manufacturer's instructions. The GeneChip Canine Genome Array was the first available commercial canine expression array and contains over 23,813 Canis familiaris probe sets to monitor gene expression for >16,000 C. familiaris full-length transcripts. Sequence information for the GeneChip Canine Genome Array includes public content from GenBank (release 137.0, August 2003), dbEST (October 2003), and proprietary beagle sequence content licensed from LION bioscience.

Microarray data analysis.
All arrays referred to in this study were assessed for "array performance" prior to data analysis. This process involved the statistical analysis of control transcripts that are spiked into the samples themselves and the hybridization cocktail to assess array performance. In addition, several genes have been identified on each array to help assess the overall quality of signal intensity from all arrays. The results of this analysis were helpful to validate the reproducibility of each array at baseline, allowing us to define the lower level of sensitivity sufficient to identify small changes in biologically relevant genes.

Prior to analysis, data from each hybridization were processed using Microarray Suite software, v. 5.0 (MAS 5.0), to yield average difference values corresponding to signal intensity for each probe-set. Distinct algorithms were used to determine the absolute call, which distinguishes the presence or absence of a transcript, the differential change in gene expression (increase, decrease, marginal increase, marginal decrease, and no change, and the magnitude of change), which is represented as signal log ratio (on a log base-2 scale). In brief, the algorithm which defines the presence or absence of a gene takes into consideration several qualitative and quantitative metrics from the raw data set. We performed t-tests on the normalized signal values prior to exploring additional analyses.

All the hybridization data have been submitted to the National Center for Biotechnology Information Gene Expression Omnibus database (GEO: http://www.ncbi.nlm.nih.gov/geo) with GEO accession numbers for series GSE5247. The raw pixels data were imported into GeneTraffic MULTI, and all subsequent analyses were performed on a GeneTraffic server (GeneTraffic v. 3.2–11; Iobion Informatics, La Jolla, CA) at the Functional Genomics Core Facility of New York Medical College. All the microarray data were analyzed and normalized using a robust multichip analysis algorithm. The average of all the control animal data sets was used as the baseline for the analysis. Gene Ontology biological process annotations was performed using several programs including DAVID at http://david.abcc.ncifcrf.gov/.

Real-time quantitative RT-PCR.
To independently confirm the differential expression data generated by microarray analysis, real-time quantitative reverse transcription (RT)-PCR was utilized to determine the relative expression of selected genes. cDNA for RT-PCR was generated using 1 µg of total RNA and in a 20-µl reaction containing first-strand buffer, dTTP, dATP, dGTP, and dCTP (final concentration, 0.4 mM each), 100 U of Superscript II (Life technologies), 10 U of RNase inhibitor, 500 ng of random hexamer. The cDNA synthesis reaction mixture was incubated at 42°C for 1 h. Then, the real-time PCR step was carried out in the presence of specific primers of each of the genes (see supplementary Table 5 for primer details). (The online version of this article contains supplemental material.) RT-PCR was performed in triplicate on 10 ng of each cDNA with the SYBR Green master mix using the LightCycler PCR system following the manufacturer's instructions (Roche Diagnostics, Mannheim, Germany). To insure that there was no genomic contamination of cDNA and no primer dimmer artifact, real-time reactions containing cDNA generated without reverse transcriptase and reactions containing primers alone were also included, respectively. A relative quantitation method ({Delta}{Delta}Ct) (17) was used to evaluate the relative expression of each gene between control and 4-wk samples.

Statistical analysis.
Hemodynamic, echocardiographic, and PO2 data were expressed as means ± SE and compared by one-way ANOVA followed by Dunnett's test.

Statistical significance for changes in gene expression was performed in GeneTraffic using a multiclass method (ANOVA) and with variance stabilization. Differences were considered statistically significant at a nominal significance of P ≤ 0.05 and at least ± twofold change in expression between control, 3 wk of pacing, and end-stage heart failure.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Hemodynamics, cardiac function, and arterial PO2.
After 3 wk of pacing, dP/dtmax and ejection fraction, two indexes of cardiac contractile function, were significantly decreased (Fig. 1); however, arterial PO2 was not significantly different from control (98 ± 3 vs. 95 ± 2 mmHg), and dogs did not present signs of decompensation, such as dyspnea, lethargy, and ascites. Overt congestive heart failure developed after 28 ± 1 days of pacing, when left ventricular end-diastolic pressure reached 25 mmHg, arterial PO2 was significantly reduced (74 ± 6 mmHg), and clinical signs of decompensation were manifested. Changes in the main hemodynamic and echocardiographic parameters are presented in Fig. 1.


Figure 1
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  		Fig. 1. Changes in hemodynamics during the progression of pacing-induced heart failure (n = 6, *P < 0.05 vs. control). EF, ejection fraction; LVSP, left ventricular systolic pressure; LVEDP, left ventricular end-diastolic pressure.

 
Global gene transcript profiling.
When statistical analysis was performed using P ≤ 0.05 and ± 1.5-fold change compared with the control group, our result showed that 1,375 and 1,261 genes were differentially expressed at end-stage heart failure (4 wk) and 3 wk, respectively. Of these, 399 genes were unique to 4 wk, 285 genes unique to 3 wk, and 976 genes were differentially expressed in both. To render this screening more selective, we used ± twofold change as a cutoff; then the number of differentially regulated genes at 4 and 3 wk was greatly reduced. We observed that 526 (439 up and 87 down) and 509 (362 up and 147 down) genes were differentially regulated at 4 and 3 wk, respectively, compared with the control group (for a full list of genes, see supplementary Tables S1 and S2). Of these, 156 and 139 were unique to 4 and 3 wk, respectively, and 370 genes in common (Fig. 2 and supplementary Tables S3 and S4). As shown in Fig. 3, we could group differentially expressed genes into six functional categories based on their Gene Ontology biological process annotations. Unfortunately, about half of the genes remained unidentified, due to the lack of annotation. When considering the identified genes, we found that those encoding for proteins involved in immune response, cell signaling/communication, and metabolism were changed in almost equal proportion in compensated and decompensated failure relative to control. Interestingly, however, most of the identified genes whose expression was changed only in compensated failure belong to the functional category of metabolism. Conversely, only 8% of the genes whose expression was changed exclusively in end-stage failure are involved in metabolic pathways.


Figure 2
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  		Fig. 2. Genes differentially expressed at 3 and 4 wk or both with P ≤ 0.05 and fold change of ±2.0.

 

Figure 3
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  		Fig. 3. Differentially expressed genes separated by functional categories based on their Gene Ontology biological process annotation.

 
We found that the expression of 509 genes changed between control and 3 wk and that the expression of 526 genes changed between control and 4 wk. This analysis, however, does not take into consideration the dynamics of changes in gene expression over time. From control to 3 wk to 4 wk, a particular gene can change in expression in several manners as are represented in a schematic fashion in Fig. 4. We compared gene alterations at 3 vs. 4 wk pacing and found that only 30 genes differed (P ≤ 0.05; fold change of ±2, GoGoTable 3). When we repeated the same analysis considering fold changes of ±1.5 instead of ±2, we found 174 genes differentially regulated between 3- and 4-wk groups. Tables 1 and 2 list some of the genes whose expression was more markedly changed only at 3 wk and at 4 wk compared with control, respectively. The full list of differentially expressed genes is provided in the Data Supplements.


Figure 4
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  		Fig. 4. Schematic representation of the possible different patterns of change in gene expression during the progression of heart failure. Examples of genes with the more pronounced changes are shown.

 

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  		Table 1. Examples of genes with increased and decreased expression at 3 weeks only

 

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  		Table 2. Examples of genes with increased and decreased expression at 4 weeks only

 

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  		Table 3. Genes with increased and decreased expression at 3 wk vs. 4 wk with P ≤ 0.05 and fold change of ±2.0

 
Changes in the expression of selected genes by real-time RT-PCR.
Real time RT-PCR was employed to validate the final microarray data in 12 representative genes listed in supplementary Table S5. Of these 12 genes, eight were found significantly changed in heart failure, three showed a nonsignificant trend toward increase (ANF, eNOS, iNOS), and one was not significantly changed (nNOS). As shown in Fig. 5, there was a highly significant correlation between expression values obtained by real-time PCR analysis and those measured by microarray analysis. However, ANF, eNOS, and iNOS expression resulted in significant differences when measured by RT-PCR (twofold increase compared with control), while nNOS expression was found not significantly different with both methods of analysis.


Figure 5
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  		Fig. 5. Concordance of changes in the expression of selected genes as measured by Affymetrix microarray and quantitative real-time RT-PCR.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
By using a ±2.0-fold change vs. control as cutoff for gene expression analysis, we found that, during the progression of pacing-induced heart failure: 1) <200 genes were changed only during the compensated or the decompensated phase and 2) only 30 genes were differentially expressed between the compensated and the decompensated stage. These numbers are surprisingly low if we consider the extremely complex phenotypic alterations of the failing heart. Particularly surprising is the fact that a dramatic event such as the transition from compensated to decompensated heart failure involves changes in the expression of a very few genes.

As previously described by us (25), our model of heart failure is characterized by marked depression of contractile function occurring at very early stages. During that period, however, mechanisms of compensation limit the increase in left ventricular end-diastolic pressure, thus preventing pulmonary congestion and preserving alveolar gas exchange and peripheral perfusion. The transition to overt failure occurs over a relatively short period of ~7 days. Although more rapid than the progression of the human disease, this change might provide important insights in the processes that cause the transition to final and irreversible stages of heart failure. In this regard, microarray analysis cannot define mechanisms, but is a precious tool to obtain an overall view of the gene expression profile and to generate new working hypotheses or to further support existing ones.

Some of the genes that we found markedly up- or downregulated encode for proteins whose role in myocardial physiology and pathophysiology is well defined. Other genes are presently difficult to put in a pathophysiolgical context. It is obviously impossible to examine in detail functions and potential pathophysiological roles of all of the identified alterations, therefore our discussion will focus on selected genes whose expression was found markedly altered and whose potential importance is supported by the existing literature. One of the genes that was highly expressed at both 3 and 4 wk (especially at 3 wk) is metallothionein 1, encoding for a cysteine-rich metal binding protein. Previous studies have shown that metallothionein functions as a protective factor against oxidative damage (6, 12, 29). It is conceivable that, in our model of heart failure, metallothionein overexpression is a protective antioxidant mechanism maintained during the progression towards decompensation. Conversely, gene expression of thioredoxin-like protein 1, another antioxidant molecule, was decreased by more than threefold compared with control and only in decompensated failing hearts. Thioredoxins are the major cellular protein disulfide reductases and serve as electron donors for several important antioxidant enzymes (1). They are therefore critical for redox regulation of protein function and signaling via thiol redox control. In fact, the lack of thioredoxin is lethal during embryonic life (18). Since the failing heart is notoriously characterized by elevated oxidant stress, it is very likely that the downregulation of thioredoxin-like protein 1 constitutes a detrimental mechanism that further worsens myocardial redox state and contributes to the progression towards decompensation. At present, the role of this protein in cardiac pathological conditions, including failure, has not been explored and deserves more investigation.

Among the genes that were overexpressed only in decompensated failure, particularly interesting are those encoding for the serotonin receptor 2B and for the monoamine oxidase B. These displayed the highest levels of upregulation. Experiments in 5HT2B knockout mice have recently revealed a critical role played by this receptor in cardiac embryogenesis, while mice that survived until adulthood exhibited dilated cardiomyopathy-like signs (20). Conversely, transgenic mice overexpressing 5HT2B developed cardiac hypertrophy (21). More recently, serotonin and serotonin receptors 2A and 2B have been recognized as critically involved in processes of liver regeneration (15). To our knowledge, alterations in cardiac serotonin metabolism in human heart failure are presently almost unexplored. Brattelid et al. (4) reported functional 5HT4 receptors in porcine and human failing hearts. These authors have shown that ventricular 5-HT4b mRNA was increased by four times in 20 failing human hearts compared with five donor hearts. These results seem consistent with our data. Taken together, those studies and the present microarray data suggest the new hypothesis that a previously compensatory mechanism of 5HT2B upregulation takes place in the severely decompensated heart in response to a reduced local release of serotonin and/or in the attempt to stimulate cardiac hypertrophy and regeneration. Given the marked 5HT2B upregulation, it is possible that this mechanism plays an important role in the progression of heart failure. Monoamine oxidase B, which was also markedly upregulated in the terminal stage of pacing-induced heart failure, was previously found overexpressed in atrial tissue of patients with atrial fibrillation (14). The authors of that study pointed out that monoamine oxidase B is involved in oxidative deamination of biologic amines and, when it metabolizes tyramine (10), it generates the oxidant H2O2 that enhances the release of Ca2+ and glutathione from mitochondria (26), leading to mitochondrial damage (8). Based on these premises, it is difficult to understand whether, in our dogs, monoamine oxidase B upregulation is a compensatory or a maladaptive mechanism.

To our knowledge, only two studies have previously assessed global gene expression profiles in dogs with heart failure. Oyama and Chittu (24) used the same canine DNA microarrays to explore the gene expression profile in spontaneous dilated cardiomyopathy in dogs. In their study, gene grouping revealed that pathways involving cellular energy production, signaling and communication, and cell structure were mostly downregulated, whereas pathways involving cellular defense and stress responses were upregulated. However, these interesting data were obtained by comparing only two female Doberman Pinschers at different ages with spontaneous end-stage dilated cardiomyopathy and under pharmacological treatment. The authors commented on the fact that future studies would have benefited from the inclusion of age- and breed-matched control, standardization of medical treatments, longitudinal tissue samples obtained during progression of disease, and comparisons with experimentally induced heart failure. The present study meets in part those criteria.

A microarray analysis on cardiac tissue from dogs with pacing-induced heart failure was performed by Gao et al. (7). By employing a less specific human 20K cDNA microarray and by using also existing databases, they compared gene expression profiles of normal and end-stage failing canine hearts as well as human and murine models of heart failure. They found that human ischemic heart failure and canine pacing-induced cardiomyopathy share a similar pattern of gene overexpression. Interestingly, they found that in end-stage failure the major affected pathways were energy and metabolism ones, whereas we had opposite results. This discrepancy is difficult to explain and will require more investigation. It could be possibly due to the different pacing protocol that we followed compared with theirs and to the different probes utilized for microarray analysis.

Finally, it is important to note that none of the above mentioned studies has specifically explored the transition from compensated to decompensated heart failure.

Gene array technology for analysis of changes in gene expression in failing human hearts is now well advanced. The literature has 46 citations for 2001–2006 (PubMed search with human heart failure AND microarray). Unraveling the molecular complexities of human heart failure, particularly end-stage failure, can be achieved by combining multiple investigative approaches. Today, we only have data obtained from different heart failure cohorts done under different circumstances and using different tools. There are several parts to the problem. Each patient is the product of a complex set of genetic variations, different degrees of influence of diets and lifestyles, and usually heart transplantation patients are treated with multiple drugs.

Although the analysis of gene expression by oligonucleotide microarrays is a powerful technique, limitations warrant mention. Not all dog genes are represented on the Affymetrix GeneChip Canine Genome Arrays used in this study. Furthermore, the annotations of high number of the genes are still unknown, and therefore the knowledge that can be acquired from these experiments remains incomplete. However, the gene annotations of these arrays have improved dramatically as reported by Affymetrix at their web site (http://www.affymetrix.com). Up to now, this version of the Canine array contains 7,340 complete annotated dog genes. Another limitation is that some of the genes shown to be differentially expressed by RT-PCR in previous studies may not result significantly different in the present one. This is an intrinsic limitation of the sensitivity of microarray analysis. For instance, we found that ANF, eNOS, and iNOS expression displayed a nonstatistically significant trend to increase in HF compared with control, whereas PCR analysis revealed a high significance. There seems to exist a good correlation between oligonucleotide microarray and qRT-PCR data when ratios of gene expression in different tissues were compared for highly expressed genes and not for those expressed at low levels due to the smaller dynamic range of microarrays (5).

In conclusion, our study suggests that a number of processes including normalized expression of some cardiac genes and altered regulation of a very limited number of other genes may contribute to the transition from compensated to decompensated heart failure. Although gene array analysis could not provide mechanistic insights, it revealed the potential importance of some previously unsuspected factors in determining the malignant evolution of heart failure.


   ACKNOWLEDGMENTS
 
This study was supported by the National Heart, Lung, and Blood Institute Grants P01 HL-74237 (F. A. Recchia) and P01-HL-43023, R01-HL50142, HL-61290 (T. H. Hintze).


   FOOTNOTES
 
Address for reprint requests and other correspondence: C. Ojaimi, Dept. of Physiology, New York Medical College, Valhalla, NY 10595 (e-mail: caroline_ojaimi{at}nymc.edu).

Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).


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 RESULTS
 DISCUSSION
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