Our most striking observation was that expression changes of genes involved in b-oxidation of fatty acids and glucose metabolism differentiate adaptive from maladaptive hypertrophy.. DNA
Trang 1expression between exercise-induced cardiac effects and maladaptive cardiac hypertrophy
Claes C Strøm1, Mark Aplin1, Thorkil Ploug2, Tue E H Christoffersen1, Jozef Langfort3,
Michael Viese2, Henrik Galbo2, Stig Haunsø1and Søren P Sheikh1
1 CHARC (Copenhagen Heart Arrhythmia Research Center), Department of Medicine B, H:S Rigshospitalet, University of Copenhagen Medical School, Denmark
2 Copenhagen Muscle Research Centre, Department of Medical Physiology, Panum Institute, University of Copenhagen, Denmark
3 Laboratory of Experimental Pharmacology, Polish Academy of Science, Warsaw, Poland
Keywords
adaptive; DNA microarray; gene expression;
hypertrophy; maladaptive
Correspondence
S P Sheikh, Laboratory of Molecular
Cardiology, Department of Medicine B,
H:S Rigshospitalet, University of
Copenhagen, 20 Juliane Mariesvej,
DK-2100 Copenhagen, Denmark
Fax: +45 3545 6500
Tel: +45 3545 6730
E-mail: sheikh@molheart.dk
(Received 10 October 2004, revised 15
March 2005, accepted 22 March 2005)
doi:10.1111/j.1742-4658.2005.04684.x
While cardiac hypertrophy elicited by pathological stimuli eventually leads
to cardiac dysfunction, exercise-induced hypertrophy does not This sug-gests that a beneficial hypertrophic phenotype exists In search of an under-lying molecular substrate we used microarray technology to identify cardiac gene expression in response to exercise Rats exercised for seven weeks on a treadmill were characterized by invasive blood pressure mea-surements and echocardiography RNA was isolated from the left ventricle and analysed on DNA microarrays containing 8740 genes Selected genes were analysed by quantitative PCR The exercise program resulted in car-diac hypertrophy without impaired carcar-diac function Principal component analysis identified an exercise-induced change in gene expression that was distinct from the program observed in maladaptive hypertrophy Statistical analysis identified 267 upregulated genes and 62 downregulated genes in response to exercise Expression changes in genes encoding extracellular matrix proteins, cytoskeletal elements, signalling factors and ribosomal pro-teins mimicked changes previously described in maladaptive hypertrophy Our most striking observation was that expression changes of genes involved in b-oxidation of fatty acids and glucose metabolism differentiate adaptive from maladaptive hypertrophy Direct comparison to maladaptive hypertrophy was enabled by quantitative PCR of key metabolic enzymes including uncoupling protein 2 (UCP2) and fatty acid translocase (CD36) DNA microarray analysis of gene expression changes in exercise-induced cardiac hypertrophy suggests that a set of genes involved in fatty acid and glucose metabolism could be fundamental to the beneficial phenotype of exercise-induced hypertrophy, as these changes are absent or reversed in maladaptive hypertrophy
Abbreviations
ACE, angiotensin converting enzyme; ALP, actinin a2 associated LIM protein; EST, expressed sequence tag; FABP4, fatty acid binding protein 4; FACL, fatty acid CoA ligase; FDR, false discovery rate; GCKR, glucokinase regulatory protein; HR, heart rate; LVEDP, left ventricular end diastolic pressure; MAP, mean arterial pressure; MBE, model based expression; MYL, fast myosin alkali light chain; PCA, principal component analysis; PDC, pyruvate dehydrogenase complex; PDP, pyruvate dehydrogenase phosphatase; Slc27a1, fatty acid transport protein 4; UCP2, uncoupling protein 2.
Trang 2Heart disease is a leading cause of death in the
West-ern world and is commonly associated with cardiac
hypertrophy Sustained cardiac hypertrophy leads to
cardiac dysfunction, heart failure, arrhythmia and
sudden death As a result, cardiac hypertrophy is an
independent risk factor for cardiac morbidity and
mortality [1]
Exercise-induced cardiac hypertrophy is distinct
from the hypertrophy seen in different pathological
settings, as it is not accompanied by cardiac
dysfunc-tion or increased morbidity [2,3] This intriguing
dis-tinction has led to the concepts of maladaptive and
adaptive forms of cardiac hypertrophy While gene
expression changes in maladaptive cardiac hypertrophy
have been extensively investigated, much less is known
about transcriptional regulation in exercise-induced
hypertrophy Identification of a set of genes unique to
this condition would enhance our understanding of the
molecular differences between maladaptive and
adap-tive cardiac hypertrophy
Exercise training increases the functional capacity of
the cardiovascular system The adaptations include
increases in cardiac mass and dimension, maximum
oxy-gen consumption and coronary blood flow [4] Also,
exercise results in a balanced growth of cardiomyocytes
with normal myofibril to mitochondrial ratio [5,6] In
the setting of maladaptive hypertrophy, a shift from
fatty acids to glucose as the main fuel in the
myocar-dium has been described, and is in part caused by
down-regulation of gene products involved in b-oxidation of
fatty acids [7] Whether this metabolic shift also occurs
in adaptive hypertrophy remains to be established
Although the physiological and morphological
chan-ges during cardiac adaptations to exercise are well
characterized, little is known about the underlying
molecular changes
Evidence that adaptive and maladaptive hypertrophic
cardiac phenotypes result from activation of distinct
sig-nalling pathways has come from studies demonstrating
that exercise-induced hypertrophy is not prevented by
angiotensin II receptor blockade or cyclosporine
treat-ment [8,9] Also, several authors have demonstrated that
expression of marker genes including atrial natriuretic
peptide, myosin heavy chain isoforms and thyroid
hormone receptor isoforms differ between adaptive
and maladaptive hypertrophy [10–12] A comprehensive
analysis of the gene expression changes in
exercise-induced cardiac hypertrophy, however, is lacking Such
an approach may identify shared and divergent
mole-cular networks between adaptive and maladaptive
hypertrophy and point to new therapeutic strategies
The microarray technology allows simultaneous
analysis of the expression level of thousands of genes
making this technology well suited for comprehensive analysis of gene expression changes in response to phy-siological challenges DNA microarrays have been use-ful in analysis of cellular responses to stimuli, animal models of human disease and cancer classification [13,14]
We used DNA microarrays to define gene expression changes that characterize exercise-induced cardiac hypertrophy We identified 305 genes with differential expression in response to cardiac exercise, the majority
of which have not previously been associated with exercise The most directly interpretable and poten-tially biologically important finding was a reversed metabolic shift in response to exercise suggesting that genes involved in fatty acid and glucose metabolism are key regulatory points that distinguish adaptive beneficial hypertrophy from more adverse maladaptive forms elicited by pathological stimuli
Results
Physiological response to exercise Several pieces of data indicated that exercised rats had cardiac hypertrophy as compared to the sedentary con-trol animals First, training resulted in an 25% increase in left and right ventricular masses when nor-malized to lean body weight (Table 1) and a 10% increase when compared to tibial length (data not shown) Other organ weights were unchanged (lungs, kidney and stomach) after normalization (Table 1) Absolute cardiac weights were increased but not signi-ficantly, while other organ weights were significantly
Table 1 Organ weights Values are mean ± SEM Weights (W) of heart (H), left ventricle (LV), right ventricle (RV), lungs (P), kidney (K) and stomach (S) divided by lean (L) body (B) weight (mgÆg 0.78 )1).
*P < 0.05.
Trang 3reduced A less intense training protocol resulted in
significant body weight reductions but no increase in
ventricular weights (data not shown) Secondly,
echo-cardiographic examination of the cardiac phenotype
revealed that exercised rats had increases in both left
ventricular wall thickness and left ventricular cavity
dimensions (Table 2) Anterior and posterior wall
thicknesses were both increased by 14% and left
ven-tricular area indexed to lean body mass increased 9%
Cardiac function at rest, as determined by fractional
area of change (Table 2), left ventricular end diastolic
pressure (LVEDP), and maximal rate of isovolumetric
pressure development and decay (Table 3), was
identi-cal in the two groups, which is consistent with
pre-vious findings [15] Mean arterial pressure showed
no differences between exercised and sedentary rats
(Table 3), but resting heart rate decreased 10% in
response to exercise The decrease in resting heart rate
probably results from an increase stroke volume and
increased parasympathetic tone
Thus, our exercise protocol resulted in a phenotype
of eccentric hypertrophy without impairment of
car-diac function
Distinct global gene expression profiles between
exercised and sedentary animals
We first analysed the data for differences in global
gene expression patterns between exercised and
con-trol animals using a principal component analysis
(PCA) This type of analysis serves to reduce the
number of variables in multivariate data with mini-mal loss of information The PCA analysis based on all 8740 genes clearly distinguished the gene expres-sion profiles of hearts of exercised animals from those of controls (Fig 1) This finding indicated the existence of a distinct gene expression program induced by exercise
Identification of individual genes that are differentially expressed in response to exercise Next, individual genes regulated by exercise were iden-tified as described in Experimental procedures (Fig 2) The vast majority of genes were unchanged At the applied threshold [predefined to a false discovery rate (FDR) of 5% or less], 329 genes were identified as dif-ferentially regulated in response to exercise (marked with grey in the figure) Of these, 267 genes were upregulated while 62 genes were downregulated The upregulated genes represented 179 known genes, 66 expressed sequence tags (EST) and 22 replicate genes Among the downregulated genes were 43 known genes,
17 ESTs and two replicate probe sets A subgroup of the genes is listed in Table 4 and the full list of genes
is given in supplementary Table S1
To demonstrate the specificity of the gene expression changes, we randomly divided samples into two groups
of equal size and repeated the SAM analysis (see Experimental procedures) This procedure was repeated
Table 2 Echocardiography Values are mean ± SEM AWT,
Anter-ior wall thickness; PWT, posterAnter-ior wall thickness; d, diastole; LVA,
left ventricular area; BW, lean body weight; FAC, fractional area of
shortening.
AWTd
(cm)
PWTd (cm)
LVAd ⁄ BW (mm 2 Æg)0.78)
FAC (%) Exercised 0.205 ± 0.007* 0.195 ± 0.007* 4.97 ± 0.12* 77 ± 1
Sedentary 0.180 ± 0.003 0.171 ± 0.004 4.57 ± 0.09 78 ± 1
*P < 0.05.
Table 3 Left ventricular pressures Values are mean ± SEM.
dP ⁄ dt-max, Maximal rates of isovolumetric pressure development;
dP ⁄ dt-min, maximal rates of isovolumetric pressure decay.
LVEDP
(mm Hg)
dP ⁄ dt-max (m HgÆs)1)
dP ⁄ dt-min (mHgÆs)1)
MAP (mm Hg)
HR (min)1)
Exercised 6.0 ± 0.7 7.9 ± 0.3 ) 10.1 ± 0.4 113 ± 2 347 ± 8*
Sedentary 4.1 ± 0.5 9.3 ± 0.6 ) 11.0 ± 0.6 111 ± 6 383 ± 9
*P < 0.05.
Fig 1 Global gene expression in the hearts of exercised rats is dif-ferent from that of sedentary controls A principal component analy-sis was performed on all genes (n ¼ 8740) to find trends in the microarray data The two first components (PC1 and PC2) from the analysis are shown in the figure Exercised rats clearly cluster sep-arate from the sedentary controls indicating the existence of a dis-tinct gene expression program induced by exercise.
Trang 4several times No genes were identified as differentially
expressed in the randomized data sets as shown in
Fig 3
Confirmation of differential expression of
selected metabolic genes by quantitative PCR
From the interesting metabolic genes, six were chosen
for validation by quantitative PCR analysis CD36,
fatty acid binding protein 4 (FABP4), fatty acid
trans-port protein (Slc27a1), and glucokinase regulatory
pro-tein (GCKR) were upregulated and uncoupling propro-tein
2 (UCP2) was downregulated confirming the DNA
microarray data (Fig 4) Expression of fatty acid CoA
ligase (FACL) was not significantly upregulated in the
quantitative PCR analysis of exercise-induced
hyper-trophy
Expression of selected genes in maladaptive
hypertrophy
To compare expression of CD36 and UCP2 in
adap-tive and maladapadap-tive hypertrophy we analysed
expres-sion of CD36 and UCP2 in the noninfarcted region of
the left ventricle 3 weeks after myocardial infarction
as compared to sham-operated animals Contrary to
adaptive hypertrophy, where CD36 was upregulated
and UCP2 downregulated, CD36 expression was
unchanged and UCP2 expression increased (26%) in
maladaptive hypertrophy (Fig 5)
Discussion
In this work, we present a comprehensive analysis of transcriptional changes in response to exercise-induced cardiac hypertrophy, thereby for the first time provi-ding an overview of molecular clues to the adaptive cardiac phenotype We identified a distinct global gene expression pattern of myocardium adapting to the physiological challenge of exercise, and statistical ana-lysis identified 267 upregulated and 62 downregulated gene transcripts, providing a host of potential novel diagnostic and therapeutic targets for further investiga-tion
The exercise resulted in a relatively small increase in left ventricular mass (6%), which was in the same range as that found by others after isotonic exercise [10,16] When normalized to body weight or tibial length the increase in left ventricular mass was larger and significant Taken together with the fact that the absolute weights of all other organs were significantly reduced in the exercised animals, these data do support that the exercise regime elicited cardiac hypertrophy The reduction in body weight seen in the exercised animals most likely resulted from a combination of reduced body fat and growth retardation In line with this, a pilot series of less intense exercise resulted in a reduction in body weight (exercise 313 g vs sedentary
403 g), concurrent reductions in absolute cardiac weights, and no hypertrophy after normalization to body weight or tibial length
Fig 2 Identification of differentially
expres-sed genes A scatter plot of the observed
relative difference in gene expression vs.
the expected difference based on
permuta-tion of samples At the solid line, observed
values are identical to expected values The
applied threshold (delta ¼ 1.20) is shown as
dotted lines Corresponding values of
signifi-cance threshold (delta), FDRs, number of
genes identified as differentially expressed
and the expected number of false positives
are listed in the lower right quadrant.
Trang 5Table 4 Expression changes in response to exercise Gene names are listed with GenBank accession number; SAM score, fold change (FC) and P-values calculated by a Welch t-test are listed for comparison.
Metabolism
Extracellular matrix
Cytoskeletal
Non-muscle myosin alkali light chain, new-born, heart ventricle (MYL4) S77858 4.1 1.2 2.08E-03
Growth
Inflammation
Signalling
Trang 6Overall, gene expression patterns in adaptive cardiac
hypertrophy were quite similar to previously published
data from maladaptive cardiac hypertrophy A general
upregulation of signalling, cytoskeletal and extracellular
matrix genes was evident and the isoform shifts in
sarcomeric proteins resembled those of maladaptive
hypertrophy The most prominent difference from the
maladaptive response was differential expression of a set
of metabolic genes not previously associated with
exer-cise-induced cardiac hypertrophy While
downregula-tion of genes involved in lipid oxidadownregula-tion is typical of
maladaptive hypertrophy, we found upregulation of
sev-eral of these genes in adaptive hypertrophy Expression levels of glycolytic enzymes indicated both enhanced glycolysis and glucose oxidation to contrast the impair-ments of glucose oxidation in maladaptive hypertrophy
We also identified several differences in expression of
Fig 3 A scatter plot of the number of differentially expressed
genes compared to the number of false-positive genes at different
levels of delta The black line represents the actual data while the
three grey lines represent data from three random divisions of
samples into two groups The dotted black line represents unity,
where the number of called genes is identical to the number of
false positives.
Fig 4 Expression of selected metabolic genes by quantitative PCR confirming the microarray data Expression was normalized to GAPDH Bars represent SEM and *P < 0.05.
Table 4 (Continued).
Guanine nucleotide binding protein, alpha inhibiting polypeptide 3 AI228247 3.3 1.1 8.47E-03
Trang 7signalling proteins between adaptive and maladaptive
hypertrophy including important modulators of
adren-ergic signalling
Perhaps the most striking and potentially
physiologi-cally meaningful observation was the shift in metabolic
gene expression This finding is especially interesting as
it differentiates adaptive from maladaptive
hypertro-phy and could be the molecular mechanism underlying
earlier findings of a balanced growth of
cardiomyo-cytes with a normal ratio of mitochondria to cell
num-ber [10,17] and normal myofibril to mitochondrial
ratio [5,6] in adaptive hypertrophy
In our study, several genes involved in b-oxidation
of lipids (CD36, FACL, fatty acid binding protein)
were upregulated Genes involved in b-oxidation are
downregulated in maladaptive cardiac hypertrophy
[18,19] One gene, CD36 or Fat, encoding a fatty acid
translocase, was upregulated in response to exercise
but not regulated after maladaptive hypertrophy
CD36 has recently been shown to be responsible for
the defect in fatty acid metabolism seen in
spontane-ously hypertensive rats [20], and myocardial recovery from ischaemia is impaired in CD36 knockout mice [21] Thus the differential expression of CD36 between maladaptive and adaptive hypertrophy might be of key importance for the difference in clinical outcome in the two conditions
Glucose utilization through glycolysis is enhanced in hypertrophic hearts [22,23] However, there is no cor-responding increase in rates of glucose oxidation [22,23] The consequent low coupling of glucose oxida-tion to glycolysis is funcoxida-tionally relevant, as it contri-butes to the contractile dysfunction in hypertrophic hearts [23] The multienzyme pyruvate dehydrogenase complex (PDC) catalyses the oxidative decarboxylation
of pyruvate and contributes strongly to flux control of myocardial glucose oxidation The activity of PDC is continuously regulated by balance of inhibiting pyru-vate dehydrogenase kinase and activating pyrupyru-vate dehydrogenase phosphatase (PDP) reactions [24] We found upregulation of the PDP gene, thus, suggesting
an increased glucose oxidation in exercise-induced hypertrophy GCKR was upregulated; this has been shown to increase both glucokinase protein and enzy-matic activity levels, leading to improved glucose toler-ance and lowered plasma glucose in diabetic mice [25]
In accordance with these data, we found upregulation
of glucokinase (hexokinase 1) in hearts of exercised rats Further evidence of enhanced glycolysis came from the upregulation of 6-phosphofructo-2-kinase⁄ fructose-2,6-bisphosphatase that stimulates 6-phospho-fructo-1-kinase [26], a key enzyme of glycolysis, which was also upregulated in our experiments Collectively, these findings support the notion that cardiac capacity for glucose utilization is in fact increased by adapta-tion to exercise and that a transcripadapta-tional explanaadapta-tion for this aspect of functional improvement exists
We found significant downregulation of UCP2 in response to exercise, while UCP2 was upregulated in maladaptive hypertrophy Uncoupling proteins dissipate the proton electrochemical gradient formed during mito-chondrial respiration and generate heat production instead of ATP [27] Thus, ATP production through oxidative phosphorylation might be more effective in adaptive than in maladaptive hypertrophy due to differ-ences in UCP2 expression In line with this, UCP2 was recently found to be upregulated in several different transgenic models of cardiomyopathy induced by chro-nic b-adrenergic receptor signalling [28] The upregula-tion of UCP2 was partly reversed by b-adrenergic receptor blockade In response to volume overload, UCP2 expression was increased and this increase was partly reversed by an angiotensin converting enzyme (ACE)-inhibitor [29] UCP2 has previously been found
Fig 5 Expression of UCP2 and CD36 by quantitative PCR in
mal-adaptive hypertrophy 3 weeks after myocardial infarction (mi).
UCP2 was significantly upregulated while CD36 expression was
unchanged contrasting the findings in adaptive hypertrophy
Expres-sion was normalized to GAPDH Bars represent SEM and
*P < 0.05.
Trang 8to be downregulated in response to exercise [30] Thus,
upregulation of UCP2 seems a general feature of
mal-adaptive cardiac remodelling, and the well documented
beneficial effects of ACE-inhibitors and b-adrenergic
receptor-blockade are accompanied by decreased UCP2
expression These findings indicate that the
downregula-tion of UCP2 in adaptive hypertrophy constitutes a
molecular feature of ‘adaptiveness’ and that
upregula-tion of UCP2 may be a key factor underlying defective
energetics in diseased hearts
In accordance with previous reports we did not find
activation of the typical neonatal gene expression
pat-tern found in pathological hypertrophy, which includes
uprelation of atrial natriuretic peptide, B-type
natriure-tic peptide, a-skeletal and smooth muscle actin, and
b-myosin heavy chain [16] However, exercise-induced
hypertrophy was accompanied by a marked
upregula-tion of genes involved in extracellular matrix
remode-ling (biglycan, matrix gla protein, cathepsins, cystatins,
integrin a7 and laminin receptor) These genes are
con-sistently upregulated in pathological models of cardiac
hypertrophy indicating that these genes are necessary
to the cardiac growth response [18,31,32] In contrast
to pathological models of cardiac hypertrophy we
found no increase in collagen mRNA expression
We found upregulation of a number of cytoskeletal
genes Several of these genes were previously described
to be upregulated in pathological hypertrophy
(MYL 1, 4 and 6, sarcosin, talin, actin-related protein
complex 1b and ArgBP2) [31,33] Upregulation of
acti-nin a2 associated Lim11/rat Isl-1/Mec3 (LIM) protein
(ALP) in cardiac hypertrophy has not been described
previously but ALP–⁄ – mice develop cardiomyopathy
[34] In the only microarray study on exercise-induced
cardiac hypertrophy reported to date, MYL 4
upregu-lation was also found and confirmed by 2D gel
electro-phoresis [35] The study only employed three DNA
microarrays in each group and did not use a statistical
method to identify differentially expressed genes
We found prominent upregulation of proteins
involved in protein synthesis (eukaryotic translation
elongation factor 1 alpha 1, eukaryotic translation
elongation factor 2, RNA polymerase II polypeptide G
and several ribosomal proteins) These findings are
consistent with the increased demand for protein
syn-thesis in response to cardiac hypertrophy
In accordance with previous studies on
maladap-tive hypertrophy [18,36] we found upregulation of
inflammatory genes (superoxide dismutase 3,
comple-ment component 1qb and 1c, lysozyme and others)
indicating that inflammation is a general feature of
cardiac hypertrophy We cannot exclude the
possibil-ity that the strong physical stress induced by the
exercise contributed to the inflammatory response and exercise of more moderate extent with slower and continuous time course may induce hypertrophy without inflammation
Several of the differentially regulated signalling pro-teins have also been reported to change in maladaptive hypertrophy (Cbp⁄ p300-interacting transactivator, pro-tein tyrosine phosphatase 4a1, annexin 1 and cyclic nucleotide 3¢-phosphodiesterase) [18,32,33] Adrenergic signalling is important in cardiac hypertrophy and we found differential expression of several genes involved
in adrenergic signal transduction (catechol-O-methyl transferase, GRK2, AKAP4 and Gai3) GRK2 desen-sitizes G-protein coupled receptors and is upregulated [37] in maladaptive hypertrophy We found downregu-lation of GRK2 in adaptive hypertrophy pointing to a potentially important difference in adrenergic signal-ling between maladaptive and adaptive hypertrophy
In conclusion, we have used DNA microarrays to map gene expression in adaptive hypertrophy While expression of extracellular matrix proteins and sarco-meric proteins was similar to the changes known to occur in maladaptive hypertrophy, we found striking differences in expression of genes involved in metabo-lism between adaptive and maladaptive hypertrophy
Experimental procedures
Animal handling and training procedure
Twenty-four male Wistar rats (Taconic M & B, Ejby, Denmark) weighing 285 ± 10 g (mean ± SD; n¼ 24) were randomly assigned to either a seven-week treadmill running program (n¼ 12) or served as sedentary controls (n ¼ 12) The animals had free access to food (standard rodent pel-lets) and water Rats in the running group were exercised
on a custom-built 12-lane treadmill with an 8 inclination for 2 hÆday)1, 5 daysÆweek)1, for 7½ weeks between 12 : 00 and 17 : 30 Each training session started with a 20-min warm-up at 11 mÆmin)1 the first week gradually increasing
to 18 mÆmin)1 the last 3 weeks Running speed was set to
15 mÆmin)1 the first week, gradually increasing to level at 32.5 mÆmin)1 the final 2½ weeks, while the duration was reduced from 100 min to 80 min for the final 2½ weeks After 1 week of training one rat had a small injury to one
of its feet and was therefore withdrawn from further exer-cise and excluded from the study The experiments were approved by the Animal Experimentation Inspectorate of the Danish Ministry of Justice and the investigation con-forms 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) The day after completion of the training protocol, all animals were
Trang 9sub-jected to echocardiography and hemodynamic examination
under isoflurane anesthesia before being killed Hearts were
excised, rinsed in ice-cold saline, weighed, dissected into left
and right ventricles, frozen in liquid nitrogen and stored at
)80 C until mRNA extraction
As exercise resulted in a significantly reduced body
weight (BW) when compared to sedentary controls,
normal-ization of organ weights to BW would result in apparent
hypertrophy of all organs in the training animals For valid
comparison of experimental groups, organ weights were
instead normalized to lean body mass, estimated as BW0.78
[38], rendering only weights of total heart and left and right
ventricles different between groups, while lung, kidney and
stomach were not
Echocardiography
Echocardiography was performed during anesthesia with
1–1.5% isoflurane using a Vivid Five Echocardiograph
(GE Medical Systems Ultrasound, Little Chalfont, UK)
Recordings were stored digitally for off-line analysis Left
ventricular cavity and wall dimensions were measured in 2D
short axis recordings at the level of the papillary muscles
Hemodynamic examination
A microtip transducer catheter (Millar Instruments,
Hous-ton, TX, USA) was introduced from the right carotid
artery and placed in the left ventricle for measurements of
LVEDP and maximal rates of isovolumetric pressure
devel-opment (dP⁄ dtmax) and decline (dP⁄ dtmin) After retraction
from the left ventricle, mean arterial pressure (MAP) was
measured Simultaneous elecrocardiography was performed
from subcutaneously placed needle electrodes and heart rate
(HR) was calculated
Myocardial infarction
Myocardial infarction was induced by ligating the left
cor-onary artery Sham-operated animals served as controls
[39] After 3 weeks, animals were killed and total RNA was
isolated from the noninfarcted part of the left ventricle as
described in [36] Despite large thinned fibrotic scars, the
weight of the left ventricle was increased in infarcted ani-mals compared to controls, indicating left ventricular hypertrophy of the noninfarcted ventricle
Gene expression profiling
The GeneChip RGU34A from Affymetrix containing 8740 probe sets (and 59 control probe sets which were excluded from further analysis) was used for all hybridizations The probe sets represent approximately 6000 known rat genes, the rest being ESTs (see http://www.affymetrix.com for a more detailed description) Standard protocols for chip hybridizations available at http://www.affymetrix.com were used Briefly, cDNA was synthesized from total RNA extracted from the tissue samples by Trireagent (Molecular Research Center, Inc., OH, USA) cDNA was then used for in vitro transcription to produce biotin-labelled cRNA The cRNA was fragmented before hybridization RNA from individual animals was hybridized to each chip and six randomly chosen samples were analysed from each group Chip hybridizations were performed at a core facil-ity with ample experience in microarray handling to ensure quality Raw data are available at http://www.ncbi.nlm nih.gov/geo as series number GSE739 (access by username: revstro90, password: revstro90)
Array data analysis
Array data were normalized using the nonlinear invariant rank fitting method of Li and Wong available at http:// www.dchip.org [40] Model based expression (MBE) values were calculated for each gene using dChip (perfect match only model) Differentially expressed genes were identified using SAM available at http://www-stat stanford.edu⁄ tibs ⁄ SAM ⁄ [41] Briefly, SAM is a statistical approach to identify differentially expressed genes by con-trolling the FDR The FDR is the percentage of genes iden-tified by chance SAM identifies the differentially regulated genes by assimilating a set of gene specific t-tests Each gene is assigned a score by dividing the average difference
in gene expression between groups by the pooled SD Genes with scores greater than threshold delta (Fig 2, grey) are deemed potentially significant By permutation of the
Table 5 Primer sets used in quantitative PCR Sequences are shown in the 5¢)3¢ orientation.
Trang 10samples and recalculation of the scores, the FDR is
estima-ted at different values of delta Log2MBE values were
ana-lysed using a two-class unpaired approach with an FDR of
less than 5% For comparison, we calculated P-values for
each gene by a Welch t-test, which allows for inequality of
variances between groups P-values ranged from 2.0· 10)7
to 0.02
Quantitative PCR
RNA was extracted de novo from all the cardiac tissue
sam-ples (exercised, n¼ 11; sedentary, n ¼ 12) Reverse
tran-scription was performed using the Omniscript RT Kit
(Qiagen, Valencia, CA, USA) on 2 lg total RNA samples
and random hexamer primers according to manufacturer’s
instructions Primers were designed using PRIMER3 (MIT
and available online at http://www-genome.wi.mit.edu/cgi/
bin/primer/primer3.cgi/primer3_www.cgi) and sequence
information retrieved from the NCBI database Intron
spanning pairs were used to avoid amplification of genomic
sequences, and primer specificity and emergence of only
one product of the predicted size were ascertained by
agarose gel electrophoresis and real-time melting curve
ana-lysis of all PCR products Each sample reaction contained
cDNA synthesized from 10 ng heart RNA Standard curve
reactions contained cDNA pooled from all samples and
diluted 1 : 2, 1 : 4, 1 : 10, 1 : 50 and 1 : 100 (corresponding
to 50, 25, 10, 2 and 1 ng of total heart RNA, respectively)
DNA amplification was carried out using the RotorGene
(Corbett Research, Sydney, Australia) and the SYBR green
PCR Master Mix (Quantitect, Berkely, CA, USA) The
reactions were set up in 0.1 mL microtubes in a total
vol-ume of 20 lL with 1 lL of template Standard curves in
duplicate were included in every run, and quantification of
individual samples performed by normalization to
GAP-DH Constant GADPH expression between exercised and
sedentary animals was confirmed by northern blotting (data
not shown) At least three independent runs were
per-formed for every target transcript The primer sets used in
quantitative PCR are shown in Table 5
Statistical analysis
Array data were analysed as described above All other
comparisons were made by an unpaired Student’s t-test
P-values¼ 0.05 were considered significant
Acknowledgements
We thank the staff at the Microarray Center,
Rigshos-pitalet, Denmark, for performing the microarray
hy-bridizations and scannings We thank Peter Schjerling
for Northern blots of GAPDH and Pernille Gundelach
and Katrine Kastberg for technical assistance The
work was supported by the John and Birthe Meyer Foundation, the Danish Heart Foundation
(01-1-2-59-22907, 99-1-2-31-22684), the Villadsen Family Founda-tion, the Foundation of 17.12.1981, the University of Copenhagen, Rigshospitalet, the Novo-Nordisk Foun-dation and the Danish National Research FounFoun-dation
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