Whole-genome profiling highlights the molecular complexity underlying eccentric cardiac hypertrophy

Abstract

Objectives:

Heart failure is typically preceded by myocardial hypertrophy and remodeling, which can be concentric due to pressure overload (PO), or eccentric because of volume overload (VO). The molecular mechanisms that underlie these differing patterns of hypertrophy are distinct and have yet to be fully elucidated. Thus, the goal of this work is to identify novel therapeutic targets for cardiovascular conditions marked by hypertrophy that have previously been resistant to medical treatment, such as a pure VO.

Methods:

Concentric or eccentric hypertrophy was induced in rats for 2 weeks with transverse aortic constriction (TAC) or aortocaval fistula (ACF), respectively. Hemodynamic and echocardiographic analysis were used to assess the development of left ventricular (LV) hypertrophy and functional differences between groups. Changes in gene expression were determined by microarray and further characterized with Ingenuity Pathway Analysis.

Results:

Both models of hypertrophy increased LV mass. Rats with TAC demonstrated concentric LV remodeling while rats with ACF exhibited eccentric LV remodeling. Microarray analysis associated eccentric remodeling with a more extensive alteration of gene expression compared with concentric remodeling. Rats with VO had a marked activation of extracellular matrix genes, promotion of cell cycle genes, downregulation of genes associated with oxidative metabolism, and dysregulation of genes critical to cardiac contractile function. Rats with PO demonstrated similar categorical changes, but with the involvement of fewer individual genes.

Conclusions:

Our results indicate that eccentric remodeling is a far more complex process than concentric remodeling. This study highlights the importance of several key biological functions early in the course of VO, including regulation of matrix, metabolism, cell proliferation, and contractile function. Thus, the results of this analysis will inform the ongoing search for new treatments to prevent the progression to heart failure in VO.

Keywords

heart failure left ventricular function volume overload pressure overload

Introduction

Heart failure (HF) is highly prevalent in the developed world and places a tremendous burden on healthcare systems [Lloyd-Jones et al. 2010]. HF is generally associated with cardiac hypertrophy, which typically occurs in a concentric or eccentric pattern, depending on the nature of the underlying hemodynamic overload [Grossman et al. 1975]. Cardiac hypertrophy is considered to be an initially adaptive response that compensates for hemodynamic stress but eventually progresses to left ventricular (LV) dilatation and HF [Oka and Komuro, 2008]. The last few decades have witnessed great strides in the treatment of HF, but not all forms of the disease respond equally well to the treatments currently available [Borer and Bonow, 2003]. Conditions associated with eccentric remodeling driven by a pure volume overload (VO), such as mitral regurgitation, seem to be resistant to most mainstay HF treatments [Dell’Italia et al. 1997; Perry et al. 2002]. A greater understanding of the molecular mechanisms that underlie cardiac hypertrophy and remodeling in response to the distinctly different stresses of VO or pressure overload (PO), and how each form is similar and different from the other, will be required to develop new therapies [Houser et al. 2012]. In particular, one of the hallmark differences in both processes is that extracellular matrix (ECM) homeostasis is tilted toward production in PO and degradation in VO [Ryan et al. 2007; Chen et al. 2010, 2011].

Concentric hypertrophy is defined by an increase in the wall thickness to chamber diameter ratio [Lorell and Carabello, 2000] and typically develops in conditions marked by PO and elevated afterload, such as aortic stenosis or hypertension [Grossman et al. 1975]. Individual cardiomyocytes respond to the systolic stress of PO by adding sarcomeres in parallel and increasing cell diameter, and this hypertrophy is often accompanied by profound fibrosis [Houser et al. 2012]. Major indices of cardiac function are maintained during the early compensatory phase of PO despite some diastolic dysfunction, but eventually LV dilatation and systolic failure occur. This condition is commonly modeled in rats with transverse aortic constriction (TAC), which creates a stress similar to that of aortic stenosis.

Eccentric hypertrophy is characterized by a dilation of the LV chamber with cardiomyocyte elongation due to sarcomeres being added in series [Houser et al. 2012]. This definition has been recently challenged by the observation of eccentric LV chamber remodeling without an increase in cardiomyocyte length but with significant loss of interstitial collagen, suggesting the occurrence of cardiomyocyte rearrangement or slippage rather than elongation [Ryan et al. 2007]. A pure VO and eccentric hypertrophy can be induced in rats through the creation of an aortocaval fistula (ACF) [Stumpe et al. 1973], and rats with this intervention demonstrate increased filling pressures with LV wall thinning, dilatation, and HF within 8 weeks [Ruzicka et al. 1994; Brower et al. 1996; Ryan et al. 2007; Wei et al. 2012].

Previous studies have reported differences in gene expression profiles in concentric and eccentric cardiac hypertrophy at various stages in either process [Miyazaki et al. 2006; Toischer et al. 2010]. In the present study, the TAC and ACF models were studied at the formative stages of concentric and eccentric hypertrophy and the preservation of load-dependent ejection-phase indices of LV systolic function were carefully documented. Thus, we examined both processes in a relatively compensated state after achieving the typical divergent patterns of LV remodeling, but before LV systolic and diastolic functional decompensation. The results of our analysis are impressive because, despite apparent functional compensation, there was disparate activation of a variety of molecular pathways that have been implicated in cardiac dysfunction [Stumpe et al. 1973; Strom et al. 2004]. Herein we present results of a whole-genome analysis of rats with either PO or VO due to TAC or ACF, respectively, at the subacute 2-week time point. We found that eccentric remodeling has a particularly extensive involvement of matrix turnover, oxidative metabolism, cell proliferation, and ion handling.

Methods

Ethics statement

This study conforms to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication No. 85-23, revised 1996), and was approved by the University of Alabama at Birmingham’s Institutional Animal Care and Use Committee. All surgeries were performed under isoflurane anesthesia, and all efforts were made to minimize suffering.

TAC

PO was induced in adult male Sprague–Dawley rats (12 weeks of age, 200–250 g) with TAC as described previously [Strom et al. 2004; Houser et al. 2012]. Rats were anesthetized with isoflurane inhalation (1–2%) and a left thoracotomy was made at the second intercostal space and the ribs retracted. The transverse aorta was exposed by blunt dissection and a 3-0 silk suture was placed around the aorta between the innominate and left common carotid arteries. A piece of 18-gauge needle was laid on the aorta and the suture tied snugly around the vessel and the needle. The needle was then pulled out of the ligation and the ends of the suture trimmed. Retraction was then removed, the ribs closed with 5-0 silk suture, and the skin at the thoracotomy site was closed using metallic clips. TAC sham surgeries were performed in control animals and consisted of the same procedure outlined above without the aortic ligation.

ACF

ACF surgery was performed as described previously in our laboratory to produce VO [Wei et al. 2003, 2012; Ryan et al. 2007]. Adult male Sprague–Dawley rats (12 weeks of age, 200–250 g) underwent general anesthesia with isoflurane inhalation (1–2%). The abdominal cavity was opened via a ventral midline incision. The inferior vena cava (IVC) and aorta were gently exposed and then occluded with finger pressure distal to the renal vasculature and proximal to the bifurcation of the aorta. An 18-gauge short-bevel needle was inserted into the ventral aspect of the aorta and then passed through adjacent medial walls of both vessels into the lumen of the IVC. The needle was withdrawn and the insertion wound in the aorta was closed with a drop of cyanoacrylate glue. Fistula patency was verified visually by swelling of the IVC and by the mixing of bright arterial and dark venous blood in the IVC. The peritoneal cavity was closed using 5-0 chromic gut stitches (Ethicon, Incorporated, Somerville, NJ) and the skin was closed using metallic clips. The control animals, ACF sham, underwent general anesthesia, abdominal incision, and vessel exposure without ACF.

Experimental protocol

TAC, ACF, or sham operations were performed in rats. Then 14 days after surgery, echocardiography and hemodynamics were performed in TAC (n = 11), TAC sham (n = 10), ACF (n = 11), and ACF sham (n = 11). At sacrifice, sections of LV were removed and flash-frozen in liquid nitrogen, stored in RNAlater (Qiagen, Germantown, MD) for RNA extraction, or placed in fixative for immunohistochemical analysis, as detailed in the following.

Echocardiography and hemodynamics

Echocardiography and hemodynamics were performed prior to sacrifice using the Agilent Sonos 5500 system (Philips, Bothell, WA) combined with simultaneous high-fidelity LV pressure catheter recordings (Millar Institute, Houston, TX). With the rat under isoflurane anesthesia, a high-fidelity LV pressure catheter was advanced into the LV cavity via a right carotid cut-down. LV pressure and echocardiography dimensions (wall thickness and chamber diameter) were obtained simultaneously.

LV volume was calculated from traced m-mode LV dimensions using the Teicholz formula [Nagatsu et al. 1994]:

V = [7 / (2.4 + LVID)] • [LVID]

where V = volume and LVID = LV internal dimension.

LV wall stress was calculated from traced m-mode LV dimensions and simultaneous LV pressure data using the equation below.

LV σ = [LVP • r] / [2 • LVwt]

where LV σ = LV wall stress, LVP = LV pressure, r = LV chamber radius and LVwt = LV wall thickness.

A 2F-combined conductance catheter–micromanometer (Millar, Houston, TX) was advanced retrogradely into the ascending aorta, where arterial pressure waveforms were collected before the catheter was advanced into the LV. Simultaneous pressure and volume measurements were collected at 1000 Hz both at baseline and during reduced loading conditions caused by a transient (3–5 s) occlusion of the IVC at the level of the apex of the heart by a balloon catheter inserted into the right femoral vein. End-systolic and end-diastolic volumes were calculated using the Bullet formula with long- and short-axis dimensions obtained using a B-mode video as described previously in our lab [Marsh et al. 2009]. These values were then used to calibrate the raw data from the conductance catheter. Pressure–volume relations were analyzed using cardiac pressure–volume analysis software (PVAN 3.0; Millar).

RNA extraction and purification

Total RNA for microarray and reverse transcriptase polymerase chain reaction (RT-PCR) analysis was extracted from LV tissue pieces using the Qiagen RNeasy Fibrous Kit (Germantown, MD) per the manufacturer’s protocol. RNA quality was assessed with the Bio-Rad Experion system (Hercules, CA).

Microarray data collection and analysis

Microarray hybridization and intensity data collection were performed as previously reported using Agilent Single-Color 4x44k Rat Whole Genome chips (Palo Alto, CA) on 4 rats per group (except TAC sham, n = 3) [Wagner et al. 2004; Chen et al. 2010, 2011]. Data analysis was performed with GeneSpring 12.1 (Agilent, Palo Alto, CA). A 50th percentile shift was applied to imported data after normalization within and between chips. Genes with significantly altered expression ≥1.5-fold were determined using unpaired t-tests with asymptotic p-value computation. No multiple testing corrections were applied.

Lists of differentially regulated genes were assessed with Ingenuity Pathway Analysis (IPA; Redwood City, CA) as published previously [Chen et al. 2010]. IPA mines the established literature for relationships between genes in the provided data set. Relationships deemed significant by a Fisher’s exact test were output as a network of associated genes. The score for each network considers the total number of network-ready genes in the IPA database, total number of genes in the data set, and the number of genes in the generated network. Descriptions for genes in Tables 5 –9 were obtained from GeneCards.org and www.ncbi.nlm.nih.gov/gene.

Real-time PCR validation

RT-PCR was performed on the same RNA samples used for microarray analysis. cDNA was reverse transcribed with the Bio-Rad iScript cDNA Synthesis kit (Hercules, CA) and 26 genes were quantified in animals from various groups (40 total comparisons) using iQ SybrGreen Supermix and the Bio-Rad iCycler (primer sequences shown in Table 1). Standard curves were created with PCR product synthesized with the same primers and iQ Supermix, purified with agarose gel electrophoresis, and isolated via gel extraction with the Qiagen Gel Extraction kit (Germantown, MD). Copy numbers of all targets were normalized by GAPDH expression and fold change was computed for comparison to microarray expression values.

Table 1.

Reverse transcriptase polymerase chain reaction primer sequences.

Gene name	Accession	Primer forward sequence 5’-3’	Primer reverse sequence 5’-3’
ACSLI	NM_012820	TGTGGGGTGGAAATCATCGG	TTGGGGTTGCCTGTAGTTCC
ADRA1D	NM_024483	CACCCTCAGCAGTACCAAGG	GTGGAGAACAGGGAGCCAAG
CACNA1D	NM_017298	ACGCGAACGAGGCAAACTAT	TTGCCAAGACAGGACGGTTT
CCNE1	NM_001100821	GCTTCGGGTCTGAGTTCCAA	GATCGGACTGAGAGGTCGGA
CD14	NM_021744	CAGAATCTACCGACCATGAAGC	CGCATAGAAAAGCGCTGGAC
CDKN1A	NM_080782	TATGTACCAGCCACAGGCAC	GCGAAGTCAAAGTTCCACCG
CDKN1C	NM_182735	CGACTGAGAGCAAGCGAACA	CATGGTCGAAGGCTGGCTAA
CHRNA1	NM_024485	TGTCACCCACTTTCCCTTCG	GGCTGGTCACTTTCCGGATT
COX7C	NM_001134705	GTTCCGGATAGCAAGGTCGT	GCAAATTCTTCCCCGGACCC
CTGF	NM_022266	CTTCCCGAGAAGGGTCAAGC	TTCCAGTCGGTAGGCAGCTA
F2RL1	NM_005242	GAATGCACCGGGACCCAAC	AAAGACGGTGGTCAGCTTCC
FBP2	NM_053716	TGCCACAATGACGGACAGAA	CCCGCAATCCCATACAGGTT
FN1	NM_019143	TCACCAACCTTAATCCGGGC	ATCGGAAACCGTGGATTGCT
GAPDH	NM_017008	GGCAGCCCAGAACATCATCC	GTTTCTCCAGGCGGCATGTC
KLK1	NM_031523	CATCACACCTGACGGATTGGA	CCTTGCAAGTGTCTTTGCCC
LCT4S	NM_053639	GCTGTGTATCGGACAAGGCT	CACGGCTGCAACAGCATATC
LTBP2	NM_021586	GGAGTTCTGCTGCAAGCCTA	GCGAGGAACAGCGGAAAGTA
MAOA	NM_033653	ACGAGCAGCTAGAGAGGTGT	ATCTTGAGCAGACCAGGCAC
NDUFC2	NM_001009290	GGGCCATGAGCCCTTAAGATT	TGGCGATGCAAACCTGCTT
PER2	NM_031678	ATGCTCGCCATCCACAAGAA	TCAAAGGGCCTACCCTGACT
PLN	NM_022707	ACAGAAGCCAAGGCCTCCTA	TCCTGATAGCCGAGCGAGTA
S100A1	NM_001007636	ACTGAACTCTCCAGCTTCCTG	GTCCACTTCCCCATCTCCATT
SLN	NM_001013247	GTCTTTGCTTCTCTTCAGGACG	CATGGCCCCTCAGTATTGGT
TIMP1	NM_053819	CTCGGACCTGGTTATAAGGGC	CCGGAAACCTGTGGCATTTC
TNFRSF11B	NM_012870	CAGCAGAGAAGCACCTAGCA	TGTCCAAGAACACCAGGAGTG
TNNT1	NM_134388	GACCGTATTGAGAGGCGTCG	AGGTAGCCCCCAAAATGAGC
UCP3	NM_013167	GTGCTCGGTACCATCCTGAC	CTGGAGTGGTCCGTTCCTTT

Immunohistochemistry

Rat hearts were immersion-fixed in 10% neutral buffered formalin and paraffin-embedded. Then 5 µm sections were mounted on + slides, deparaffinized in xylene and rehydrated in a graded series of ethanol. Heat-induced epitope retrieval was performed with citrate buffer (Vector Laboratories, #H-3300, Burlingame, CA). Sections were blocked with 5% goat serum (in 1% bovine serum/phosphate-buffered saline [PBS]), followed by overnight incubation at 4°C with primary antibody (Ki67: 1:50, Pierce/LabVision RM-9106, Fremont, CA; Aurora B Kinase, 1:500, Abcam ab2254, Cambridge, MA; Desmin: 1:100, Abcam ab6322; Myosin: 1:100, Abcam ab15). Sections were incubated with Alexa Fluor 488- or 594-conjugated secondary antibody (Life Technologies/Molecular Probes, Eugene, OR) to visualize proliferation (red) and cardiomyocyte (green) markers in the tissue, as indicated in figure legends. Nuclei were stained with DAPI (1.5 µg/ml, Vector Laboratories #H-1500, Burlingame, CA). Image acquisition was performed on a Leica DM6000 epifluorescence microscope with SimplePCI software (Compix, Inc., Cranberry Township, PA). Images were adjusted appropriately to remove background fluorescence.

Statistics

All data are presented as means ± standard error of mean (SEM). Morphologic, echocardiographic, and hemodynamic changes between each surgery group and its respective sham group were tested for significance with a Student’s t-test using SigmaStat statistical software (Systat, Chicago, Illinois). p values less than 0.05 were considered significant.

Results

LV morphometry

After 2 weeks of TAC there was an 18% increase in LV mass/BW, while ACF produced a 27% increase in LV mass/BW (Table 2). In addition, ACF rats also demonstrated increases in right ventricular (RV), right + left atria, and lung weights, which are consistent with the physiology of ACF; these parameters were unchanged in rats with TAC. All groups had similar body weights at the time of sacrifice.

Table 2.

Morphometric weights.

	TAC sham	TAC	ACF sham	ACF
BW at sacrifice (g)	331±7	325±7	302±6	317±7
HW/BW (g/kg)	3.10±0.05	3.62±0.10*	3.13±0.08	4.28±0.06*
LVW/BW (g/kg)	2.10±0.04	2.47±0.07*	2.15±0.07	2.72±0.05*
RVW/BW (g/kg)	0.68±0.02	0.74±0.06	0.65±0.03	0.90±0.02*
Atria wt/BW (g/kg)	0.28±0.01	0.34±0.04	0.31±0.01	0.54±0.02*
Lung wt/BW (g/kg)	5.00±0.16	4.95±0.17	4.70±0.17	5.67±0.21*

Values are expressed as mean ± standard error of mean.

p < 0.05 versus age-matched shams.

ACF, aortocaval fistula; BW, body weight; HW, heart weight; LVW, left ventricle weight; RVW, right ventricle weight; TAC, transverse aortic constriction.

LV hemodynamics and echocardiography

There were no significant differences in heart rate, mean arterial pressure, dP/dt_max, or dP/dt_min between groups (Table 3). The ACF group demonstrated an increased LV end-diastolic pressure versus ACF sham, while LV end-diastolic pressure did not differ between TAC and TAC sham rats. There was a commensurate decrease in LV end-diastolic and end-systolic dimensions in TAC, while LV end-diastolic dimension increased in ACF versus respective shams. There were opposite trends in LV contractility (LV Ees), with a decrease in ACF and an increase in TAC.

Table 3.

Hemodynamic and echocardiographic results.

	TAC sham	TAC	ACF sham	ACF
HR (bpm)	279±21	288±9	285±15	330±15
MAP (mmHg)	94±7	88±6	80±6	81±5
LVEDP (mmHg)	6±2	7±1	4±1	6±1*
+dP/dt (mmHg/s)	6342±246	6096±459	5666±315	7228±746
–dP/dt (mmHg/s)	−6375±614	−5992±451	−5627±479	−6805±694
LVESD (mm)	4.49±0.35	3.29±0.31*	4.16±0.27	4.66±0.24
LVEDD (mm)	7.82±0.18	6.70±0.34*	7.24±0.26	8.94±0.19*
IVS (mm)	1.55±0.05	2.08±0.14*	1.60±0.10	1.61±0.09
Ees (mmHg/ml)	0.11±0.02	0.17±0.04	0.16±0.04	0.12±0.04

Values are expressed as mean ± standard error of the mean.

p < 0.05 versus age-matched shams.

ACF, aortocaval fistula; TAC, transverse aortic constriction; HR, heart rate; MAP, mean arterial pressure; LVEDP, left ventricular end-diastolic pressure; +dP/dt, left ventricular pressure derivative maximum; –dP/dt, left ventricular pressure derivative minimum; LVESD: left ventricular end-systolic dimension; LVEDD: left ventricular end-diastolic dimension; IVS, interventricular septum; Ees: end-systolic elastance.

Changes in LV remodeling and function in PO and VO

TAC rats had significantly reduced LV end-diastolic dimensions and increased LV end-diastolic posterior wall thickness, resulting in a significant decrease in LV end-diastolic wall stress (Figure 1). In contrast, ACF rats demonstrated significantly increased LV end-diastolic dimensions that were not associated with a change in wall thickness or LV end-diastolic wall stress. In TAC, a significant decrease in LV end-systolic wall stress was associated with an increase in LV contraction velocity (VCf_r) (Figure 2), while ACF rats displayed no significant changes in LV end-systolic wall stress, VCf_r, or fractional shortening compared with ACF shams. However, ACF did lead to increases in stroke volume, stroke work, ejection fraction, and cardiac output compared with shams (Figure 3), all of which were unchanged by TAC at 2 weeks.

Figure 1.

Changes in diastolic parameters. The left ventricular (LV) end-diastolic posterior wall dimension (A) was increased in transverse aortic constriction (TAC) rats after 2 weeks of pressure overload (PO) due to the wall thickening characteristic of concentric hypertrophy. LV end-diastolic dimension (LVEDD) (B) was significantly decreased in rats with TAC, and significantly increased in rats with aortocaval fistula (ACF), relative to respective shams. Diastolic wall stress (C) was markedly reduced in rats by two weeks of TAC compared with age-matched shams, but was unchanged in ACF rats relative to sham. *p < 0.05 versus shams.

Figure 2.

Changes in systolic parameters. Rats with pressure overload (PO) for 2 weeks due to transverse aortic constriction (TAC) demonstrated decreased systolic wall stress (A) and increased velocity of circumferential fiber shortening (VCf_r) (B) compared with age-matched shams. These parameters were unchanged in rats with volume overload (VO) subsequent to aortocaval fistula (ACF), and neither model had significant differences in fractional shortening compared with sham (C). *p < 0.05 versus shams.

Figure 3.

Cardiac performance. Rats with volume overload (VO) due to 2 weeks of aortocaval fistula (ACF) demonstrated increased stroke volume (A), stroke work (B), ejection fraction (C), and cardiac output (D) compared with age-matched shams. Two weeks of pressure overload (PO) did not change these values in transverse aortic constriction (TAC) rats compared with age-matched shams. *p < 0.05 versus shams.

Real-time PCR validation of microarray

RT-PCR quantification of 25 target genes (Tables 1 and 4) from the various group comparisons (ACF versus ACF sham, TAC versus TAC sham, ACF sham versus TAC sham) showed close agreement with fold changes derived from microarray analysis, with a resulting Pearson correlation coefficient of 0.92 (Figure 4).

Table 4.

Array and RT-PCR fold change correlation.

Gene	Comparison	Array	RT-PCR
Adra1b	ACF versus ACF sham	−1.73894	−1.7227
Maoa	ACF versus ACF sham	2.113849	2.090136
Lct4s	ACF versus ACF sham	2.277367	2.312222
CD14	TAC versus TAC sham	1.505799	1.550106
Lct4s	TAC versus TAC sham	1.641463	1.589542
S100A1	ACF versus ACF sham	−1.757	−1.6763
UCP3	ACF versus ACF sham	−1.926	−2.01854
ACSLI	ACF versus ACF sham	−1.693	−1.78819
FN1	ACF versus ACF sham	1.532	1.645914
CTGF	ACF versus ACF sham	1.92	2.043639
CCNE1	ACF sham versus TAC sham	−1.642	−1.47456
TIMP1	ACF versus ACF sham	1.502	1.317415
ACSLI	TAC versus TAC sham	−1.578	−1.77761
Tnnt1	ACF versus ACF sham	−1.66469	−1.97162
KLK1	ACF versus ACF sham	1.622	1.292981
CD14	ACF versus ACF sham	2.210828	1.876451
CaCNa1d	ACF versus ACF sham	−1.61831	−1.25078
CDKN1A	ACF sham versus TAC sham	1.574	1.189511
Cox7c	TAC versus TAC sham	−2.07347	−1.6556
CCNE1	ACF versus ACF sham	2.09	2.509384
UCP3	TAC versus TAC sham	2.049	1.59089
LTBP2	ACF versus ACF sham	3.533185	3.998361
PLN	ACF versus ACF sham	−1.678	−1.21045
FBP2	ACF versus ACF sham	−2.13637	−2.62921
TIMP1	ACF sham versus TAC sham	1.523112	1.020874
F2rl1	ACF sham versus TAC sham	−1.7808	−1.26104
Tnnt1	TAC versus TAC sham	−2.12183	−2.66072
CDKN1C	ACF versus ACF sham	−2.02036	−1.30359
PER2	ACF sham versus TAC sham	−4.433	−3.63813
CTGF	TAC versus TAC sham	2.272	1.45776
CCNE1	TAC versus TAC sham	−1.87	−2.7927
NDufc2	TAC versus TAC sham	−2.35008	−1.35561
F2rl1	ACF versus ACF sham	2.461942	1.435942
Cox7c	ACF versus ACF sham	−2.31346	−1.2825
UCP3	ACF sham versus TAC sham	2.24	3.441482
TNFR SF11B	ACF versus ACF sham	4.183	2.92923
SLN	TAC versus TAC sham	6.264	7.912885
NDufc2	ACF versus ACF sham	−3.46182	−1.08633
Chnra1	ACF versus ACF sham	−5.1729	−8.18864
CDKN1A	TAC versus TAC sham	1.782	6.686286

Fold changes of gene expression in group comparisons were determined by microarray and

RT-PCR and correlated, producing a Pearson correlation coefficient of 0.92.

ACF, aortocaval fistula; RT-PCR, reverse transcriptase polymerase chain reaction; TAC, transverse aortic constriction.

Figure 4.

Comparison of gene expression differences determined by microarray and reverse transcriptase polymerase chain reaction (RT-PCR) and number of differentially regulated genes. (A) Differences in transcript expression of 25 target genes in various groups were validated by RT-PCR in strongly correlated with fold change determined by microarray (r² = 0.92). (B) The 10 most highly correlated genes. (C) The number of differentially regulated genes, and overlap between the two models of hypertrophy, are shown in a Venn diagram. Rats with transverse aortic constriction (TAC) for 2 weeks had alterations in expression of 479 genes. Two weeks of aortocaval fistula (ACF) resulted in differential expression of 1225 genes. A total of 193 genes were common to TAC and ACF.

Gene expression changes in PO and VO

In the microarray and IPA analyses, TAC and ACF were compared with their respective shams. The microarray identified 479 genes that were differentially regulated at least 1.5-fold in TAC compared with age-matched shams, with 113 of those genes being upregulated and 366 downregulated (Figure 4). In ACF, 1225 genes were altered significantly with 307 upregulated and 918 downregulated compared with respective shams. A total of 193 differentially expressed genes were common to both forms of hypertrophy.

The top-ranking gene network produced by IPA for TAC (network score = 15) was related to behavior, neurological disease, and cellular function and maintenance (Figure 5). Genes in the top ACF network had roles in organismal injury and abnormalities, cellular growth and proliferation, and tissue morphology, and yield a score of 22 (Figure 6).

Figure 5.

Transverse aortic constriction (TAC) gene network. Diagram of regulatory relationships between key genes with altered expression due to the pressure overload (PO) of TAC. Green nodes are downregulated, red nodes are upregulated. White nodes denote key mediators or regulators that were not significantly altered in expression.

Figure 6.

Aortocaval fistula (ACF) gene network. Diagram of relationships between notable genes with altered expression after 2 weeks of ACF. Green nodes are downregulated, red nodes are upregulated. White nodes denote key mediators or regulators that were not significantly altered in expression.

Upon careful inspection of the differentially regulated genes in TAC and ACF, we found involvement of four key biological categories. Rats with ACF for 2 weeks showed marked differences in expression of ECM genes, generally upregulated compared with sham, whereas rats with PO demonstrated minimal changes in ECM genes (Table 5). Both forms of hypertrophy diminished the expression of genes involved with oxidative metabolism of fatty acids and glucose, but the decreases were much more extensive in VO (Table 6). ACF rats also had marked activation of cell proliferation pathways compared with sham rats; however in TAC rats, the few differentially regulated genes pertaining to the cell cycle were primarily inhibitory (Table 7). Finally, several key regulators of myocyte contractility were substantially decreased in both models compared with their respective shams, but ACF rats had greater involvement of this category compared with TAC rats (Table 8).

Table 5.

Extracellular matrix homeostasis: VO versus PO differences of key genes.

Gene	VO versus sham	PO versus sham	Gene function
	Fold (p value)	Fold (p value)
Ltbp2	3.5 (1.39×10^–4)	NS	Induced by and activates TGF-beta1 signaling
Plau	3.2 (0.01)	NS	Protease involved in ECM degradation
C6	3.2 (0.003)	NS	Key mediator of innate and adaptive immunity
Cilp	2.7 (0.003)	NS	Plays a role in cartilage scaffolding
Thbs4	2.6 (0.03)	NS	Mediates cell–cell and cell–matrix interactions
Col8a1	2.5 (6.50×10^–4)	NS	Component of the basement membrane
Has1	2.3 (0.02)	NS	Active in wound healing and tissue repair
Cthrc1	2.2 (0.006)	NS	Arterial injury and vascular remodeling
Matn4	2.2 (0.008)	NS	Major component of cartilage ECM
Loxl1	2.1 (6.89×10^–4)	NS	Crosslinks collagens and elastin
Mfap5	2.1 (6.47×10^–5)	NS	Component of the elastin-associated microfibrils
Plod2	2.1 (0.004)	NS	Key enzyme in collagen synthesis
Pcdhb5	2.1 (0.01)	NS	Calcium-dependent cell-adhesion protein
Lox	2.0 (0.02)	NS	Crosslinks ECM proteins
Col14a1	2.0 (0.007)	NS	Adhesive role; integrates collagen bundles
Fbln2	2.0 (5.65×10^–5)	NS	Regulates elastic fiber assembly
Vcan	2.0 (6.10×10^–5)	NS	Connects cells with ECM; signaling
Cntn2	2.0 (0.03)	NS	GPI-anchored cell adhesion molecule
CTGF	1.9 (0.001)	2.2 (0.0002)	Mediates adhesion and growth of fibroblasts
Ecm1	1.7 (0.03)	NS	Inhibits MMP9 proteolytic activity.
Fbn1	1.7 (0.01)	NS	Provides force-bearing structural support
Bgn	1.6 (5.62×10^–4)	NS	Assembly of collagen; muscle regeneration
Emilin2	1.6 (0.01)	NS	Anchors smooth muscle cells to elastic fibers
Nid1	1.6 (5.48×10^–4)	NS	Binds laminin, collagen IV, and perlecan
Adamtsl3	1.6 (0.01)	NS	An ECM-regulating ADAMTS-like protease
CD68	1.5 (0.001)	NS	Monocyte/macrophage marker
Fn1	1.5 (0.004)	NS	Key ECM and cell-adhesion component
Loxl3	1.5 (0.02)	NS	LOX family member, crosslinks ECM proteins
Timp1	1.5 (3.43×10^–4)	NS	Inhibitor of many MMPs, but not MT1-MMP
Epyc	−1.5 (0.01)	NS	Regulates fibrillogenesis via fibril/ECM linking
Slpi	−1.5 (0.01)	NS	Inhibitor of mast cell proteases
Pcdhb6	NS	−1.6 (0.02)	A calcium-dependent cell-adhesion protein
Col11a2	−1.6 (0.05)	NS	Controls lateral growth of collagen II fibrils
Tmprss9	−1.6 (0.006)	NS	Transmembrane serine protease, activates PLAU
Fbn2	NS	−1.6 (6.80×10^–5)	Structural component of Ca-binding microfibrils
Pcdh17	−1.6 (0.008)	NS	A calcium-dependent cell-adhesion protein
Fgf9	−1.6 (0.002)	NS	Regulates many processes, such as tissue repair
Fmod	−1.7 (0.02)	NS	Affects the rate of collagen fibril formation
Cadm4	−1.7 (0.008)	NS	Ca- and Mg-independent cell adhesion
Fgf1	−1.8 (0.02)	NS	Regulates angiogenesis and other processes
Col24a1	−1.8 (0.02)	NS	Regulates type I collagen fibrillogenesis
Col4a1	−1.9 (6.85×10^–4)	NS	Key ECM component
Ppl	NS	−2.1 (0.04)	Links desmosomes and intermediate filaments
Adamts1	−2.1 (0.007)	−2.1 (0.01)	Metalloprotease which cleaves aggrecan
Spon1	−2.6 (0.002)	−1.8 (0.002)	Cell adhesion protein

A multitude of extracellular matrix genes are dysregulated in VO. Genes are listed with fold-change relative to sham, and p-values in parentheses.

ECM, extracellular matrix; MMP, matrix metalloproteinase; NS, nonsignificant; PO, pressure overload; TGF, transforming growth factor; VO, volume overload.

Table 6.

Loss of oxidative metabolism: VO versus PO differences of key genes.

Gene	VO versus sham	PO versus sham	Gene function
	Fold (p value)	Fold (p value)
Pink1	−1.5 (0.002)	NS	Has initiating role in stress-induced mitophagy
Ant1	−1.5 (0.01)	NS	Mitochondrial ADP/ATP exchanger
Pdha1	−1.5 (0.002)	NS	Key enzyme regulating glucose oxidation
Acot2	−1.5 (0.003)	NS	Regulates acyl-CoA / free fatty acid balance
Acox1	−1.5 (0.006)	NS	Catalyzes first step of fatty acid beta oxidation
Pcca	−1.5 (3.02×10^–4)	NS	Produces key metabolic intermediates
Bckdhb	−1.6 (0.009)	NS	Key enzyme in amino acid catabolism
Eci1	−1.6 (0.005)	NS	Key mitochondrial fatty acid oxidation enzyme
Sdhb	−1.6 (0.004)	NS	Component of electron transport chain
Prkag3	−1.6 (1.73×10^–4)	NS	AMPK (cellular low-energy sensor) component
Decr1	−1.7 (0.003)	NS	Participates in beta oxidation of fatty acids
Acot1	−1.7 (0.02)	NS	Regulates acyl-CoA / free fatty acid balance
Lsr	−1.7 (3.73×10^–4)	NS	Regulates cellular uptake of free fatty acids
Adssl1	−1.7 (0.01)	−1.8 (0.02)	Synthesizes AMP from IMP precursor
Acsl1	−1.7 (0.03)	−1.6 (0.01)	Activates fatty acids for beta oxidation
Acaa2	−1.7 (0.05)	NS	Key enzyme in fatty acid beta oxidation
Hadha	−1.7 (0.003)	NS	Catalyzes last steps of fatty acid beta oxidation
Ech1	−1.7 (0.01)	NS	Participates in beta oxidation
Gckr	NS	−1.8 (0.02)	Inhibitor of glucokinase
Ucp3	−1.9 (0.04)	2.1 (0.02)	Uncouples oxidative phosphorylation
Mrpl18	−1.9 (0.01)	−1.9 (0.05)	Participates in mitochondrial protein synthesis
Pecr	−2.0 (0.001)	−1.6 (0.001)	Involved in fatty acid synthesis
Cox7c	−2.1 (0.002)	−2.3 (0.005)	Last oxidase in electron transport chain
Fbp2	−2.1 (0.004)	NS	Regulates gluconeogenesis
Fabp12	−2.3 (0.006)	NS	Involved in lipid transport
Atp5hl1	−2.3 (8.28×10^–4)	NS	ATP synthase complex component
Ndufs2	−3.5 (9.50×10^–5)	−2.4 (0.008)	Core of electron transport chain Complex I
Acsbg1	−7.5 (9.16×10^–6)	NS	Activates fatty acids for beta oxidation

Genes contributing to oxidative metabolism of fatty acids and glucose are downregulated in rats with PO and VO. Genes are listed with fold-change relative to sham, and p-value in parentheses.

ADP, adenosine diphosphate; AMP, adenosine monophosphate; AMPK, AMP-activated protein kinase; ATP, adenosine triphosphate; IMP, inosine monophosphate; NS, nonsignificant; PO, pressure overload; VO, volume overload.

Table 7.

Cell cycle and proliferation: VO versus PO differences of key genes.

Gene	VO versus sham	PO versus sham	Gene function
	Fold (p value)	Fold (p value)
Ccne1	2.1 (6.19×10^–4)	−1.9 (0.05)	Essential for control of the G1/S transition
Fstl1	1.9 (6.24×10^–4)	NS	Inhibits BMP receptor complex assembly
Cenpw	1.9 (0.006)	NS	Has a central role in mitotic progression
Mms22l	1.9 (0.01)	NS	Repairs genetic damage during DNA synthesis
Mcm8	NS	1.9 (0.04)	Has roles in DNA repair and synthesis
Prim1	1.8 (0.01)	1.6 (0.008)	Synthesizes primers for DNA replication
Brip1	1.8 (0.03)	NS	Has a role in DNA repair
Cdkn1a	NS	1.8 (0.005)	Mediator of p53 antiproliferative effects
Kif4	1.7 (0.03)	NS	Positions chromosomes during mitosis
Mcm3	1.7 (0.02)	NS	Required for initiation of DNA synthesis
Top2a	1.7 (0.02)	NS	Required for separation of chromosomes
Plk2	1.7 (0.003)	NS	Participates in mitotic checkpoints after stress
Tpx2	1.7 (0.005)	NS	Required for mitotic spindle assembly
Ska1	1.7 (0.05)	NS	Required for chromosome segregation
Kntc1	1.7 (0.009)	NS	Prevents premature exit from mitosis
Mybl2	1.7 (0.02)	NS	Mediates signaling between various cyclins
Cenpm	1.7 (0.01)	NS	Required for centromere assembly
Traf4af1	1.6 (0.008)	NS	Essential component of the mitotic spindle
Kif20a	1.6 (0.02)	NS	Mitotic kinesin required for cytokinesis
Chaf1b	1.6 (0.01)	NS	Mediates chromatin assembly in DNA replication
E2f8	1.6 (0.02)	NS	Regulates expression of cell cycle genes
Gadd45b	NS	1.6 (0.04)	Inhibits cell growth and proliferation after stress
Prc1	1.6 (0.007)	NS	Key regulator of cytokinesis
Rrm2	1.6 (0.04)	NS	Synthesizes deoxynucleotides for DNA synthesis
Cdca2	1.6 (0.03)	NS	Regulators chromosome structure during mitosis
Ccnb1	1.5 (0.04)	NS	Controls G2/M (mitosis) transition
Plk1	1.5 (0.02)	NS	Performs multiple key activities during M phase
Racgap1	1.5 (0.02)	NS	Regulates initiation of cytokinesis
Cdc7	1.5 (0.004)	NS	Regulates the G1/S phase transition
Cenpt	1.5 (0.02)	NS	Has a fundamental role in kinetochores
Hic1	−1.5 (0.01)	NS	Represses cyclin expression in quiescent cells
Ccni	−1.5 (0.03)	NS	Associated with cardiomyocyte growth arrest
Mcm10	NS	−1.7 (0.03)	A DNA replication initiation factor
G0s2	−1.8 (0.03)	NS	May have a role in maintaining quiescence
Cdkn1c	−2.0 (0.005)	NS	Negative regulator of cell proliferation
Pot1b	−2.6 (0.004)	NS	Protects and assists in elongation of telomeres

Cell proliferation genes are markedly induced by two weeks of VO compared with sham rats, whereas gene changes in PO oppose cell cycle progression. Genes are listed with fold-change relative to sham, and p-value in parentheses.

BMP, bone morphogenetic protein; NS, nonsignificant; PO, pressure overload; VO, volume overload.

Table 8.

Dysregulation of contraction: VO versus PO differences of key genes.

Gene	VO versus sham	PO versus sham	Gene function
	Fold (p value)	Fold (p value)
Sln	NS	6.2 (0.003)	Slows SERCA activity
Myh3	−1.5 (0.02)	NS	An embryonic myosin heavy chain
Tpm1	−1.6 (0.008)	NS	Key mediator of calcium regulation of contraction
S100a1	−1.8 (0.003)	NS	Stimulates calcium-induced calcium release
Cacna1d	−1.6 (0.05)	NS	Long-lasting voltage gated calcium channel
Ttn	−1.7 (0.01)	NS	Key structural component of striated muscle
Pln	−1.7 (0.009)	NS	Inhibits SERCA unless phosphorylated
Tnnt1	−1.7 (0.03)	−2.1 (1.33×10^–5)	Mediates calcium control of contraction
Myl1	NS	−2.2 (0.03)	Regulatory light chain of myosin

Genes with key roles in myocyte contractility are downregulated in rats with ACF. Genes are listed with fold-change relative to sham, and p-value in parentheses.

NS, nonsignificant; PO, pressure overload; SERCA, sarcoplasmic endoplasmic/endoplasmic reticulum Ca²⁺-ATPase; VO, volume overload.

Table 9.

Gene symbols not defined in the text.

Symbol	Gene name
Acox1	acyl-CoA oxidase 1, palmitoyl
Acsl1	acyl-CoA synthetase long-chain family member 1
Acsbg1	acyl-CoA synthetase bubblegum family member 1
Ccnb1	cyclin B1
Ccne1	cyclin E1
Cdc7	cell division cycle 7
Cdkn1a	cyclin-dependent kinase inhibitor 1A (p21, Cip1)
Cenpm	centromere protein M
Cenpw	centromere protein W
Chaf1b	chromatin assembly factor 1, subunit B (p60)
Col8a1	collagen, type VIII, alpha 1
Cox7c	cytochrome c oxidase subunit VIIc
CREB1	cAMP responsive element binding protein 1
CTGF	connective tissue growth factor
Ecm1	extracellular matrix protein 1
Emilin2	elastin microfibril interfacer 2
Fbln2	fibulin 2
Fbp2	fructose-1,6-bisphosphatase 2
Gadd45b	growth arrest and DNA-damage-inducible, beta
Kif20a	kinesin family member 20A
Lox	lysyl oxidase
Loxl1	lysyl oxidase-like 1
Loxl3	lysyl oxidase-like 3
Mcm3	minichromosome maintenance complex component 3
Mcm8	minichromosome maintenance complex component 8
Mfap5	microfibrillar associated protein 5
MMP9	matrix metallopeptidase 9 (gelatinase B, 92kDa type IV collagenase)
Nid1	nidogen 1
Pdha1	pyruvate dehydrogenase (lipoamide) alpha 1
Pecr	peroxisomal trans-2-enoyl-CoA reductase
PKP2	plakophilin 2
Plau	plasminogen activator, urokinase
Plod2	procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2
Prc1	protein regulator of cytokinesis 1
Prim1	primase, DNA, polypeptide 1 (49kDa)
Racgap1	Rac GTPase activating protein 1
Rrm2	ribonucleotide reductase M2
SCNA1	sodium channel, voltage-gated, type I, alpha subunit (Nav1.1)
Sdhb	succinate dehydrogenase complex, subunit B, iron sulfur (Ip)
SGK1	serum/glucocorticoid regulated kinase 1
TIMP1	tissue inhibitor of metalloproteinases 1
Vcan	versican

Markers of cell proliferation in PO and VO

There was substantial expression of Ki67 in cardiomyocytes and interstitial cells from both TAC and ACF hearts (Figure 7). However, Aurora B Kinase, a marker of cell division, was seen only in the ACF group. PO rats had an average of 49 Ki67⁺ nuclei per cm² while VO rats averaged 40 Ki67⁺ nuclei per cm², compared with 10 positive nuclei per cm² in both sham groups. Despite this indication of nuclear division in myocytes, there was no increase in the number of nuclei per cardiomyocyte in ACF or TAC (data not shown).

Figure 7.

Markers of cell proliferation after hemodynamic overload. Expression of the proliferation marker Ki67 (red in (A), (B), and (C)) was detected in nuclei (DAPI, blue) of myocytes (desmin, labeled green in (A) and (B)) and interstitial cells (vimentin, labeled green in (C)) from hearts with both forms of hypertrophy, as shown in representative images from (A) transverse aortic constriction (TAC) and (B) aortocaval fistula (ACF) heart sections. Sham rats (C) demonstrated common expression of Ki67 in interstitial cells, but expression was rare in myocytes. Aurora B Kinase (red, (D) and (E)) was also detected in myocytes (green, myosin in (D) and desmin in (E)) and interstitial cells (unlabeled in (D), labeled green with vimentin in (E)) of the ACF group (D), but not in TAC (not shown) or shams (E). Expression of Ki67 in myocyte nuclei was significantly increased in both forms of hypertrophy relative to respective shams (F). *p < 0.05 versus shams. Calibration bars indicate scale.

Discussion

In this study we compared concentric and eccentric cardiac hypertrophy at the subacute 2-week time point. We found approximately three times as many genes differentially regulated in rats with VO-induced eccentric remodeling compared with rats with the concentric remodeling of PO, suggesting greater molecular complexity in VO. A striking difference was the extensive upregulation of ECM genes in VO compared with PO, despite the known opposing directions of ECM homeostasis in eccentric and concentric hypertrophy. The widespread pattern of ECM upregulation in VO included genes involved in collagen crosslinking (Lox, Loxl1, Loxl3 Plod2) [Molnar et al. 2003; Van Der Slot et al. 2003], elastin formation and its crosslinking with collagen (Fbln2, Loxl1, Mfap5, Emilin2) [Gibson et al. 1998; Molnar et al. 2003; Timpl et al. 2003; Colombatti et al. 2011], and cell–cell or cell–matrix interactions (Col8a1, Vcan, Nid1, Fn1, Thbs4) [Mayer et al. 1998; Hou et al. 2000; Jane-Lise et al. 2000; Narouz-Ott et al. 2000; Wight, 2002]. At the same time, there was an increase in ECM proteases such as urokinase (Plau) that activates MMP-9 [Zhao et al. 2008], but this increase was counterbalanced by inhibitors of MMPs (TIMP1, Ecm1) [Li et al. 2000; Fujimoto et al. 2006]. In particular, upregulation of TIMP 1 and fibronectin (FN1) have been associated with cardiac fibrosis [Jane-Lise et al. 2000; Varo et al. 2000]. Osteoprotegerin was increased 4-fold and has been reported to have a protective effect in fibrosis in the failing heart [Ueland et al. 2005]. Taken together, the marked upregulation in ECM genes and preservation of collagen at 2 weeks of ACF (data not shown) was most likely a response to the net loss of interstitial collagen known to occur at earlier time points [Ryan et al. 2007; Chen et al. 2010]. In contrast, as concentric hypertrophy progresses beyond 2 weeks, interstitial collagen is preserved [Stewart et al. 2010] and ECM genes were generally unchanged after 2 weeks of PO. How the global increase in ECM gene expression in ACF translates into a subsequent decrease in ECM at 5 weeks remains an open question [Chen et al. 2011].

Both TAC and ACF had an increase in CTGF, which was consistent with Ki67-positive fibroblasts and myocytes [Kothapalli and Grotendorst, 2000; Hayata et al. 2008]. However, in VO there was more extensive upregulation of genes associated with all phases of cell proliferation, including genes involved in G1/S phase transition and DNA replication (Ccne1, Cdc7, Mcm3, Mcm8, Prim1, Chaf1b, Rrm2) [Koff et al. 1992; Kaufman et al. 1995; Shiratori et al. 1995; Maiorano et al. 2006; Malumbres, 2011; Lu et al. 2012], G2/mitosis (Ccnb1) [Galaktionov and Beach, 1991], centromere assembly (Cenpm, Cenpw) [Foltz et al. 2006; Kim et al. 2009], and regulators of cytokinesis (Kif20a, Prc1, Racgap1) [Jiang et al. 1998; Hirose et al. 2001; Gruneberg et al. 2004]. Inhibitors of cell growth and proliferation were upregulated in PO (Cdkn1a, Gadd45b) [Harper et al. 1993; Vairapandi et al. 2002] and unchanged in VO. Most importantly, and consistent with the gene expression pattern, the cell division marker Aurora B kinase was found only in VO. These findings support the well-established association of inflammation with cell proliferation [Lien et al. 2006]. However, the current study cannot determine whether the increased cell cycle events were from resident myocytes or interstitial cells, or an influx of stem cells.

The connection between inflammation and cardiac remodeling is well established [Kuwahara et al. 2004; Weber, 2004; Lien et al. 2006] and was prominent in VO, given the induction of Cathepsin S (CTSS) [Cheng et al. 2006], complement 6 (C6) [Ito et al. 1996], and the macrophage marker CD68 [Barry, 1994]. Secretory leukocyte peptidase inhibitor (Slpi), an endogenous inhibitor of several cathepsins [Taggart et al. 2001] and other immune cell proteases [Walter et al. 1996], was downregulated. We have previously reported an intense inflammatory cell infiltration at 24 hours and 2 weeks in the ACF model [Chen et al. 2010, 2011], and this is consistent with the upregulation of gene clusters involved in ECM turnover and cell proliferation identified by our microarray. It is of interest that we have previously shown proliferation is absent after 5 weeks of ACF but there is further LV hypertrophy [Chen et al. 2011]. However, at 5 weeks of ACF collagen is decreased and does not keep pace with cardiac hypertrophy, despite upregulation of the renin–angiotensin system [Ruzicka et al. 1994; Wei et al. 2012].

Approximately 40% of the genes with altered expression in PO were also altered in VO. These genes primarily pertain to lipid metabolism and their downregulation in both models implies they have roles common to cardiac hypertrophy [Strom et al. 2004; Chen et al. 2011]. There was downregulation of ACSL1, which synthesizes long-chain acyl-CoA for fatty acid oxidation, and Pecr which is involved in fatty acid synthesis [Das et al. 2000]. Deletion of ACSL1 induces hypertrophy in mice [Ellis et al. 2011]. The decrease of metabolic gene expression in VO also included genes involved in fatty acid oxidation, such as Acox1 and Acsbg1 [Finck. and Kelly, 2002], and genes involved in glucose oxidation including Fbp2 and the pyruvate dehydrogenase complex component Pdha1 [Kitamura and Uyeda, 1987; Patel and Korotchkina, 2006]. The reduced expression of several components of the electron transport chain (Sdhb and Cox7c) [Hederstedt and Rutberg, 1981; Kadenbach and Merle, 1981; Procaccio et al. 1998] further demonstrates a global loss of oxidative metabolism in VO. The effect on cardiac metabolism was more extensive in ACF than in TAC and may be related to the greater sympathetic nervous system activation that is required in VO to maintain a high stroke volume [Kitamura and Uyeda, 1987].

IPA further highlighted alterations in genes associated with ECM and cell proliferation in VO (Figure 6). Nuclear factor kappa-B (NF-kB) is a key regulator of ECM with its role in activation of fibronectin and TIMP1 [Reddy et al. 2008; Bommarito et al. 2011]. In contrast, the PO IPA network implicates genes essential for preservation of contractility (Figure 5), consistent with the increased LV VCf_r and LV end-systolic pressure volume relation. While α-adrenergic receptor (Adra1d) is downregulated in rats with TAC, upregulation SGK1 potentiates α-receptor signaling and promotes hypertrophy [Lister et al. 2006]. SGK1 also alters sodium channel expression in concentric hypertrophy [Das et al. 2012], and upregulation of SCNA1/Nav1.1 promotes exaggerated action potentials in pressure-overloaded hearts [Xi et al. 2009]. Rho family members are also identified in PO and can mediate the upregulation of the sodium/calcium exchanger NCX1 [Maeda et al. 2005]. In contrast, the ACF IPA network suggests Protein Kinase C as a mechanism for the downregulation of genes participating in contraction, specifically S100A1, a key calcium handling protein [Most et al. 2006]. Downregulation of CREB1 can also alter ion channel and pump expression profiles and alter action potential properties [Schulte et al. 2012]. The downregulation of Gja1 (Connexin 43) [Guerrero et al. 1997] and PKP2 [Cerrone et al. 2012], both desmosomal proteins, can also lead to aberrant cardiomyocyte ion handling. Thus, the IPA network genes in PO and VO are consistent with LV systolic function at this time point.

A limitation of the current study is that the 2-week stage for TAC and ACF may not be equivalent with regard to peak molecular responses. In addition, the animal models employed in this study create an abrupt hemodynamic change, whereas the human conditions they attempt to recapitulate are often chronic and develop over years or decades [Houser et al. 2012]. Despite these limitations, both TAC and ACF reached a stable point defined by LV remodeling, with a greater emphasis on ECM remodeling genes in ACF. Also, while the assessment of transcript levels provided by microarray analysis is highly informative, the results may not always extend to the final biological outcome due to post-transcription regulatory mechanisms, such as microRNAs [Duisters et al. 2009; Da Costa Martins and De Windt, 2012]. In addition, there are numerous post-translational modifications that can influence protein function [Molkentin, 2000; Blankesteijn et al. 2008; Laczy et al. 2009; Marber et al. 2011].

While it is clearly important to understand mechanisms and factors that are universally involved in cardiac hypertrophy, the fact that some forms of HF and hypertrophy are refractory to mainstay treatments strongly suggests the need to also consider mechanisms that differ between concentric and eccentric remodeling. The vast upregulation of ECM genes in eccentric remodeling is paradoxical given the eventual loss of ECM in pure VO. The results presented here should prompt further investigation into the feasibility of shifting ECM homeostasis toward a more positive balance, which is the opposite effect of renin–angiotensin system blockade, and further explains the failure of this drug therapy to arrest the remodeling process in a pure VO.

Footnotes

Acknowledgements

We wish to thank Dr Michelle Amaral and Dr David Crossman for access to GeneSpring, and Dr Marcus Bamman for access to IPA.

Funding

This work was supported by the National Heart, Lung, and Blood Institute (NHLBI; grant number RO1-HL-54816 to L. J. Dell’Italia) and a NHLBI Specialized Centers of Clinically Orientated Research Grant in Cardiac Dysfunction (grant number P50-HL-077100).

Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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