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Cardiovascular Research 2003 57(2):477-485; doi:10.1016/S0008-6363(02)00703-4
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Copyright © 2003, European Society of Cardiology

Genetic basis for chamber-specific ventricular phenotypes in the rat infarct model

Sumeet S Chugha,*, Stacey Whitesela, Mark Turnerb, Charles T Roberts, Jr.b and Srinivasa R Nagallab

aDivision of Cardiology, Department of Medicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
bDepartment of Pediatrics, Oregon Health and Science University, Portland OR, USA

chughs{at}ohsu.edu

* Corresponding author. Fax: +1-503-494-8750

Received 22 May 2002; accepted 25 September 2002


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
 References
 
Background: We, and others, have previously reported a strong correlation between increased inter-ventricular dispersion of repolarization and the occurrence of fatal arrhythmia in animal models of CHF. The existence of this and other such distinct electrophysiologic phenotypes in right (RV) vs. left ventricles (LV) could be explained by chamber-specific patterns of gene expression. Methods: We employed microarray gene profiling of 13 824 sequence-verified, nonredundant rodent cDNAs to compare myocardial gene expression in RV vs. LV of rats with surgically induced myocardial infarction (MI: n=3) and in sham-operated animals (Sham: n=3). Results: Significant LV infarction (32±4% LV) and severe CHF were observed in all MI animals at 4 weeks. In Sham animals, 937 genes exhibited significant differential expression in RV vs. LV myocardium. In MI animals, 1158 genes exhibited significant differential expression in RV vs. LV. Of those genes exhibiting significant differential expression, only 241 were common to both Sham and MI animals. Differentially expressed genes included those involved in signal transduction, cell growth and maintenance, and apoptosis. Genes with potential roles in altered dispersion of repolarization included voltage-dependent Ca2+ channel {gamma} subunit (MI 8-fold{uparrow}) and K+ inwardly rectifying channel subfamily J, member 10 (MI 6-fold{downarrow}). Gap junction membrane channel protein {alpha} 4 (MI 6-fold{downarrow}) and cardiac troponin I (MI 8-fold{downarrow}) were also significantly differentially expressed. Inter-ventricular comparisons revealed significantly greater alterations in gene expression vs. intra-ventricular comparisons. Conclusions: Microarray gene profiling has revealed candidate genes, some of them novel, which may account for chamber-specific ventricular electrophysiologic phenotypes, both in physiologic as well as in arrhythmogenic states such as CHF.

KEYWORDS Arrhythmia (mechanisms); Gene expression; Heart failure; Infarction; Ion channels; Repolarization; Sudden death


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
 References
 
The right and left cardiac ventricles have distinct morphologic, hemodynamic and electrophysiologic properties. In normal mammalian hearts, these discrete properties are of functional significance, and the chambers have a complementary role in cardiac excitation and myocardial contractile function. However, disease states may result in an imbalance of chamber-specific properties of the right and left ventricles. Such alterations are well documented for arrhythmogenic states in animal models, as well as in human subjects. Vos et al. described a strong correlation between ventricular proarrhythmia and increased inter-ventricular dispersion of repolarization in a canine model of chronic AV block [1]. We have reported similar observations in the canine model of pacing-induced heart failure [2]. In addition, recent studies have implicated electrophysiologic changes specific to the RV in the pathophysiology of Brugada syndrome [3,4].

Knowledge of the genetic basis of such ventricular-specific phenotypes in normal and disease states may significantly advance the understanding of ventricular arrhythmogenic mechanisms. Gene expression profiling using cDNA microarrays is a useful tool for the simultaneous and comprehensive evaluation of myocardial gene expression [5]. The rat model of surgically-induced myocardial infarction manifests with severe dilated cardiomyopathy and an early incidence of fatal arrhythmia [6,7]. Having previously characterized the hemodynamic and structural remodeling that occurs in this model during the progression of heart failure [8], we employed microarray gene profiling to study chamber-specific ventricular gene expression patterns, with a focus on known/putative cardiac rhythm-related genes.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
 References
 
2.1 Creation of the animal model and harvest of tissue
The Oregon Health and Science University Institutional Animal Care and Use Committee approved all aspects of the study, and the investigation conforms with the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health (NIH Publication No. 85-23, revised 1996). Surgical ligation of the left coronary artery via a small left thoracotomy (Charles River Labs., Raleigh, NC, USA) was performed in nine male Sprague–Dawley rats (MI), using previously described techniques [8]. Three animals underwent sham surgery, i.e. left thoracotomy was performed without actual ligation of the left coronary artery. Harvest of tissue in all animals was performed at 4 weeks following surgery. Following liberal general anesthesia with Nembutal and heparin injection (1000 units, intra-peritoneal), the heart was excised using a median sternotomy. In five MI animals, myocardial infarct size was determined by planimetry of serial sections taken from each heart at 4 weeks following surgery. In the remaining three MI animals and three Sham animals, the RV and the infarcted and noninfarcted regions of the LV were carefully separated (inter-ventricular septum was included in the LV). Tissue was flash-frozen with immediate storage at –70 °C. Gene expression comparisons were made between RV myocardium and LV noninfarcted myocardium (remote from the infarct zone) in both Sham and MI animals.

2.2 Microarray procedures
Custom microarrays were prepared by printing 13 834 sequence-verified rodent cDNAs (Research Genetics, Huntsville, AL, USA) on silylated (superaldehyde-coated) glass slides (Telechem, Sunnyvale, CA, USA). Total RNA was extracted using Qiagen RNeasy columns (Qiagen, Valencia, CA, USA). Comparisons were performed between RV Sham, RV MI, LV Sham and LV MI. For each comparison, RNA was pooled from three Sham or three MI animals. Separate microarrays were used for each tissue type (i.e. RV Sham, LV Sham, RV MI and LV MI). In addition, duplicate microarrays were hybridized and analyzed for each tissue type. A 10-µg amount of total RNA underwent reverse transcription to generate biotinylated fluorescent cDNA probes. These probes were hybridized in 50% formamide, 5x Denhardt's and 6xSSC in a humidity chamber at 45 °C overnight. Streptavidin–HRP and Cy5 tyramide (New England Nuclear, http://lifesciences.perkinelmer.com/) were used for signal detection. Slides were scanned using a ScanArray 4000 slide reader (GSI Lumonics, http://www.gsilumonics.com/). Detailed descriptions of microarray procedures are available at http://medir.ohsu.edu/~geneview, under Protocols.

2.3 Data analysis
Spot and grid parameters from array images were extracted using IMAGENE 4.1 software (BioDiscovery, http://www.biodiscovery.com/). The mean fluorescence intensity of the signal pixels for each spot was corrected for local background fluorescence by subtracting the median fluorescence of the background pixels. Arrays were assessed for quality by visual inspection as well as determination of detectable gene expression using control spots printed on all arrays. Sequences were determined to be detectable using frequency signal (frequency difference significant at P<0.0005 by contingency table analysis). Determination of differential expression in the detectable expressed genes was done using ARRAYSTAT (Imaging Research, http://www.imagingresearch.com/). The data were analyzed using the Proportional Model with Offsets option, which log transforms the data (base 10) and screens replicate measurements for outliers. Global differences in labeling and hybridization efficiency between arrays were normalized in a two-step process that centered data within replicate arrays for a given condition, and then normalized the mean data for each condition by a scaling factor. Global scaling was used in preference to normalization by the signal intensity of housekeeping genes, because the housekeeping genes that were previously used to normalize RT-PCR expression data typically have strong signals that fall at the upper end of the distribution of signals from the microarray [9]. Pairwise comparisons of conditions were made using the z test. Differences were considered statistically significant if they achieved a nominal significance of P<0.05 after adjusting the cutoff P value for multiple comparisons by the stepdown Bonferroni method [10]. Among the 13 834 genes spotted on the array, a set of 120 genes were prespecified as known or potential cardiac rhythm-related genes, based on the existing cardiac electrophysiology literature. In addition to analyzing all spotted genes, the cardiac rhythm-related set was subjected to focused investigation regarding potential interrelationships between these genes and their function.


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
 References
 
3.1 Evidence of myocardial infarction and significant heart failure
One of the nine MI animals died within 48 h of surgery. At 4 weeks, all MI animals had signs of heart failure, with evidence of significant 4-chamber dilated cardiomyopathy when tissue was harvested. In five separate MI animals that underwent planimetry, the average infarct size was 32±4% of LV myocardium.

3.2 Global gene expression patterns of RV vs. LV in Sham animals
Of a total of 13 824 cDNA sequences profiled on the arrays, 12 567 were determined to be detectable for this comparison. The majority of profiled genes were not significantly differentially expressed in RV vs. LV (92.5%, Fig. 1). However, among the remaining genes, 5.8% had increased expression in RV vs. LV, and 1.7% genes had decreased expression in RV vs. LV.


Figure 1
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  		Fig. 1 Chamber-specific gene expression. (A) Data from Sham animals and (B) from MI animals. The Venn diagram shows relative number of genes upregulated in RV vs. LV in both groups of animals.

 
3.3 Global gene expression patterns of RV vs. LV in MI animals
In MI animals, a total of 11 639 cDNA sequences were expressed at detectable levels. As in Sham animals, the majority of genes in MI animals (90%) were also expressed similarly in RV vs. LV. Of the remaining genes, 3.6% were significantly upregulated in RV vs. LV and 6.4% were significantly downregulated (Fig. 1). Among the total genes that were significantly differentially expressed (Sham or MI), only 241 genes were common to both Sham and MI animals. A compressed view of the cluster analysis of all expressed genes showing relative differential expression in Sham RV, Sham LV, MI RV and MI LV is shown in Fig. 2A. Detailed gene expression data for all cDNAs profiled on the microarray are available in tabular form at http://medir.ohsu.edu/~geneview, under Rat Myocardial Infarction Model: Gene Expression Data.


Figure 2
Figure 2
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  		Fig. 2 (A) This cluster analysis (GeneMaths) provides an overall comparison of absolute gene expression (of all genes spotted on the array), between RV Sham, LV Sham, RV MI and LV MI (columns 1–4 from left to right, respectively). The color scale (green–yellow–orange–red) denotes a quantification of gene expression, green indicating least and red the greatest degree of gene expression. (B) This cluster analysis provides a means of finding potential similarities in gene expression trends or cross talk between 58 of the 120 preselected known/putative cardiac rhythm-related genes. The displayed data are based on differential expression of these genes in RV Sham, LV Sham, RV MI and LV MI in columns 1–4 from left to right, respectively. The top of the figure shows the color scale for increasing relative gene expression from a scale of 1–4 (green->red). Parentheses to the left of the figure relate families of genes that cluster together based on extent of gene expression, with a scale from 60 to 100 (100 represents strongest cluster relationship).

 
3.4 Functional classification of global gene expression
The differentially expressed genes represented several categories of broad functions. Fig. 3 shows the distribution of differentially expressed genes based on their functional classification. From the available literature, a function was ascribable for 151 (16%) differentially expressed genes in the Sham comparisons and for 233 genes (20%) in the MI comparisons of RV vs. LV.


Figure 3
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  		Fig. 3 Functional classification of genes differentially expressed in RV vs. LV. Data in pie diagrams is expressed as a percentage of total genes.

 
3.5 Alterations in myocardial gene expression of individual chambers
As a result of myocardial infarction, expression of profiled genes was altered significantly in MI RV vs. Sham RV for 67 genes. When MI LV and Sham LV were compared, there was significant differential expression of 24 genes. Only 45 of these 91 genes were found to overlap with those differentially expressed in RV vs. LV comparisons.

3.6 Differential expression of known/putative cardiac rhythm-related genes
In Sham animals, of 120 prespecified genes profiled, significant differential expression in RV vs. LV was observed for 11 genes. In MI animals, there was significant differential expression in RV vs. LV for 17 of 120 genes. The majority of these genes did not overlap. However, of the 28 genes (11+17), five genes overlapped and were differentially expressed in a similar manner for RV vs. LV in both groups. Fig. 2B illustrates the relative differential expression of selected genes (58 out of 120) in Sham RV, Sham LV, MI RV and MI LV. Table 1 provides details of the extent of relative upregulation or downregulation in RV vs. LV (fold change), as well as the specific function of selected genes from this subgroup.


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  		Table 1 Details of selected cardiac-rhythm related genes

 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Limitations
 6. Conclusions
 Acknowledgments
 References
 
In both Sham and MI animals, a significant proportion of genes profiled using microarrays were expressed differentially in RV compared to LV. In Shams, 5.8% showed increased expression in RV (compared to LV) and 1.7% showed decreased expression. In MI animals, these trends were reversed, and a smaller proportion of genes were upregulated in the RV compared to LV (3.6% upregulated vs. 6.4% downregulated). Of 120 preselected known/putative cardiac rhythm-related genes, 11 exhibited significant differential expression in RV compared to LV in Shams, and 17 in MI animals, respectively. However, when altered myocardial gene expression was evaluated in individual chambers (MI RV vs. Sham RV; MI LV vs. Sham LV), only 91 genes (0.01% of total genes profiled) were found to exhibit significant differential expression.

The presence of electrophysiologic heterogeneity between RV and LV has been demonstrated in the normal heart. Using an in situ canine model of digitalis toxicity, Damato et al. first observed quantitative differences between automatic pacemaker rates of right and left bundle branch systems [11]. Subsequently, findings of functional dissimilarity between right and left ventricles were observed in the intact normal and infarcted canine heart [12], as well as right and left Purkinje strands [13]. More recently, Antzelevitch et al. reported significant differences in the magnitude of the monophasic action potential notch in right vs. left canine ventricular epicardium, which were attributable to relative downregulation of the Ca2+-activated outward K+ current (Ito) in RV vs. LV [14]. Our data indicate the existence of significant inter-ventricular genetic diversity in the normal heart, which may account for some of the unique electrophysiologic properties of each chamber. For instance, genes affecting Ca2+ regulation and transport that were differentially expressed in RV vs. LV included Ca2+-transporting ATPase (Atp2a2, upregulated 7-fold in RV Sham) and calmodulin 2 (Calm2, upregulated 9-fold in RV Sham).

In cardiac disease states, inter-ventricular electrophysiologic heterogeneity has been associated with arrhythmogenicity. In a canine model of chronic AV-block, Vos et al. observed a strong correlation between acquired torsade-de-pointes arrhythmia and inter-ventricular dispersion of repolarization [1]. They proposed that inter-ventricular dispersion of repolarization be added to bradycardia, prolonged repolarization and early afterdepolarizations as an important factor in the initiation of this arrhythmia. We, and others, have reported similar findings in canine models of tachycardia-induced dilated cardiomyopathy and fatal arrhythmia [2,15]. With ibutilide administration, we observed an increased dispersion of left-right ventricular action potential duration in CHF, which correlated with increased incidence of polymorphic ventricular tachycardia [2]. In the present study, surgically induced MI and progression to heart failure resulted in significant alterations in genetic expression in both LV and RV. While significant overlap between the chambers continues to exist, the trend for chamber-specific genetic expression reverses in heart failure. There is a shift in chamber-specific gene expression toward relative downregulation of genes in the RV compared to the LV. Gene expression profiling identified several potential candidate genes that may account for chamber-specific alterations in repolarization following myocardial infarction. These include the potassium channel, subfamily K, member 3 (Kcnk3; significantly upregulated in RV in Sham, but not MI), Ca2+ channel β1 subunit (Cacnb1; downregulated 5-fold in RV MI, not Sham) and voltage-dependent Ca2+ channel, {gamma} subunit 6 (Cacng6; upregulated 8-fold in RV MI, not Sham). A previous study in the rat infarct model detected differential expression of <200 genes (out of approximately 4000 genes profiled) following MI [16]. However, this analysis was restricted to the LV/interventricular septum, and comparisons with RV myocardial gene expression were not performed. Interestingly, in the present study, while myocardial infarction caused altered gene expression within individual chambers, the number of genes affected were small (n=91; 0.01% of total) compared to inter-chamber gene expression (Sham RV vs. LV 7.5% of total; MI RV vs. LV 10% of total).

Discontinuous electrical propagation resulting from altered distribution of gap junctions is an important factor in promoting reentrant ventricular arrhythmias in cardiac disease states [17,18]. Significant alterations in the number and arrangement of gap junctions have been observed in ischemic heart disease [19–22]. Nakajima et al. recently reported differential deposition of collagen in atrium vs. ventricle in transgenic mice with elevated levels of active myocardial transforming growth factor-β1 [23]. In the rat MI model, Cleutjens et al. observed differential collagen remodeling in RV vs. LV with respect to time after infarction, as well as qualitative and quantitative differences [24]. Our data confirm the existence of such chamber-specific differences between the two ventricles, especially in MI animals. Candidate genes potentially related to extra-cellular discontinuities in cardiac muscle, include gap junction membrane channel protein {alpha}4 (Gja4; downregulated 6-fold in MI RV vs. LV), matrix metalloproteinase 24 (Mmp24; upregulated 13-fold in Sham RV vs. LV but no significant differential expression in MI), procollagen, type I, {alpha}1 (Col1a1; downregulated 6-fold in MI RV vs. LV) and procollagen, type I, {alpha}2 (Col1a2; upregulated 5-fold in MI RV vs. LV). Also, in the present study, when Mmp 24 expression was compared in Sham LV and MI LV, there was upregulation in MI LV (Fig. 2B). Upregulation of matrix metalloproteinase subtypes was previously shown to occur in the rat MI model, but has only been evaluated in LV myocardium [25].

LV hypertrophy has long been associated with an increased propensity for genesis of ventricular arrhythmia [26,27], but the molecular pathways leading to fatal arrhythmia remain uncertain. In a mouse model of aortic stenosis and hypertrophy, the expression of the cardiac sarcoplasmic reticulum Ca2+-ATPase gene (Atp2a2; encoding the protein isoforms SERCA2a and SERCA2b) may be a determinant of mortality. Lorell et al. observed a significantly lower mortality in transgenic animals expressing SERCA2a gene compared to wild-type mice [28]. In patients with heart failure who undergo reverse remodeling, SERCA2A can exhibit differential expression in RV vs. LV. Barbone et al.reported that structural reverse-remodeling and hemodynamic benefit from left-ventricular assist devices correlated with increased differential expression of normalized SERCA2A content in RV vs. LV [29]. These observations bear an interesting similarity to the findings in the present study, with Atp2a2 upregulation (7-fold) observed in RV vs. LV of Sham animals, but no chamber-specific expression in MI animals.


   5. Limitations
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
6. Conclusions
 Acknowledgments
 References
 
The technique of cDNA microarray gene profiling has evolved to universal acceptance [5,30–33]. However, expression data, i.e. mRNA levels, may not accurately reflect protein levels, since translational control and post-translation processing may occur [25]. In turn, the expression of a protein may not always have a physiological or pathological consequence. However, the identification of candidate genes on the basis of quantification of their expression level and the subsequent application of this knowledge to disease gene identification and transgenic technology is a logical step toward realization of the new genes-to-mechanisms paradigm [34–36]. The present investigation examined gene expression at a single time-point (4 weeks) following myocardial infarction. It is likely that the nature and extent of gene expression vary depending on the time duration at which it is evaluated. In the present study, we included the interventricular septum within the LV analysis. This was based on the findings of a previously published microarray study in a similar model, which did not find significant changes in gene expression in interventricular septum vs. LV free wall [16]. However, others have identified region-specific gene expression in comparisons of LV free wall vs. interventricular septum [37–39]. Finally, Ito current is an important contributor to repolarization duration, but expression of encoding genes was not evaluated with the microarrays employed in the present study.


   6. Conclusions
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
Acknowledgments
 References
 
We have identified significant differences in genetic expression between right and left ventricles, which may explain some of the distinct morphologic and physiologic properties of the two chambers in the normal rat heart. In our model, myocardial infarction resulted in further alteration of chamber-specific gene expression patterns. Inter-chamber differences in gene expression were observed to be significantly greater than intra-chamber alterations, underscoring the potential importance of understanding interactions in right vs. left ventricular pathophysiology. Detailed characterization of this inventory of candidate genes, which includes a group of known/putative cardiac rhythm-related genes, may be useful in understanding the role of chamber-specific electrophysiologic properties in normal as well as arrhythmogenic states such as heart failure.

Time for primary review 23 days.


   Acknowledgments
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
References
 
The authors greatly appreciate the technical assistance provided by Patrick Pattee, Matthew Rodland and Jean O’Malley.

This investigation was funded, in part, by a grant from the Collins Medical Trust to SSC.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Limitations
 6. Conclusions
 Acknowledgments
 References
 

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