Acta Medica Mediterranea, 2019, 35: 2315

IDENTIFICATION OF POTENTIAL KEY ASSOCIATED WITH CARDIAC FIBROSIS BY RNA SEQUENCING DATA ANALYSIS

Dandan Liu, Haizhu Wang, Xiao Han, Caiping Han, Fengbo Ren Department of Cardiology, Zhoukou Central Hospital, Zhoukou 466000, Henan, China

ABSTRACT

Introduction: Cardiac fibrosis is central to a broad constellation of cardiovascular diseases with similar pathophysiologic companions, and is associated with cardiac dysfunction, arrhythmogenesis, and adverse outcome. However, the option of effective treatment strategies is limited due to the insufficient understanding of the mechanisms for cardiac fibrosis. Materials and methods: The RNA sequencing data (GSE97358) comprising 84 TGF-β1-stimulated samples and 84 paired unstimulated samples of cultured primary human cardiac fibroblast from GEO database was used to explore crucial genes and pathways involved in cardiac fibrosis. The differentially expressed genes (DEGs) were identified using edgeR package in R. Pro- tein- interaction (PPI) network and module analyses were performed and visualized using STRING and Cytoscape. GO ( ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses were performed by clusterprofiler. The hub genes extracted from PPI were identified by the CytoHubba plug-in and the (TF)-hub gene network was further constructed by the iRegulon plug-in. Results: Totally, 647 DEGs were initially screened out in TGF-β1-stimulated primary human cardiac fibroblast. Twenty hub genes (9 up-regulated: S1PR5, F2RL3, GPR68, CXCR5, KISS1, GAL, LPAR5, HTR1D, PLCB4; 11 down-regulated: CXCL1, GPR65, CYSLTR2, EDNRA, CXCL6, F2R, GNG2 F2RL2, SSTR1, TAS2R1, HTR2B) were further identified. Wnt signaling and neu- roactive -receptor interaction signaling pathways enriched were ultimately identified as the key pathways involved in cardiac fibrosis. Seven TFs (RELB, FOS, SREBF2, PURA, TBX21, IRF1 and IRF4) were identified for the TF-hub gene networks. Conclusions: Our results may provide novel insights into the molecular mechanisms and treatments of cardiac fibrosis. How- ever, further molecular biological experiments are required to confirm these findings.

Keywords: cardiac fibrosis, differentially expressed genes, bioinformatics analysis, interaction network.

DOI: 10.19193/0393-6384_2019_5_360

Received November 30, 2018; Accepted February 20, 2019

Introduction ed in response to some pathophysiologic stimuli, such as pressure and/or volume overload, metabol- Cardiac fibrosis is characterized by the net ac- ic disorder, ischemic insults or aging which may cumulation of extracellular matrix which involves result in interstitial and perivascular fibrosis (3,4). unbalanced collagen turnover and excessive dif- Yet, activated myofibroblasts are the main effector fuse collagen deposition in the interstitial spaces cells in response to these pathophysiologic stimu- of the myocardium(1). As documented by previous li in cardiac fibrosis (1). In this regard, some fibrot- studies, cardiac fibrosis is central to a broad con- ic factors, such as cytokines, chemokines, growth stellation of cardiovascular diseases with similar factors, hormones, and reactive oxygen species, pathophysiologic companions, and is associated are responsible for the activation of fibroblasts and with cardiac dysfunction, arrhythmogenesis, and the alteration of extracellular matrix(5). A growing adverse outcome(2). In many cases, cardiac fibrosis of studies have revealed multiple signaling path- is the result of a reparative process that is activat- ways and biological processes involved in cardiac 2316 Dandan Liu, Haizhu Wang et Al fibrosis, such as transforming growth factor-beta fibroblast from patients receiving coronary artery (TGF-β), Wnt/β-catenin, mitogen-activated protein bypass grafting(16). The RNA sequencing data were kinase (MAPK) signaling, epithelial-mesenchymal normalized and analyzed by the edgeR package transition (EMT), endothelial-mesenchymal transi- in R. Differentially expressed genes (DEGs) were tion (EndMT), inflammation, oxidative stress pro- identified with the cut-off criteria |log2FC| ≥1, cesses, etc(1,6-8). P-value < 0.05 and adjust P-value < 0.05. Although some conventional drugs, such as angiotensin-converting enzyme inhibitors (ACEIs), Functional and pathway enrichment analysis aldosterone antagonists, β-blocker, and statins, have To elucidate potential biological processes, been shown to alleviate cardiac fibrosis in clinical molecular functions and signaling pathways cor- trials(9-13), most of these traditional therapies are not related with the DEGs, the (GO, directed towards alleviating fibrosis but secondary http://www.geneontology.org) and Kyoto Ency- to the correction of the underlying cardiac dysfunc- clopedia of Genes and Genomes (KEGG, http:// tion mechanisms and do not effectively hamper the www.ge¬nome.ad.jp/kegg/) pathway enrichment progression of cardiac fibrosis (2). Despite the ad- analyses were performed(17,18), which were carried vance in exploring the pathogenesis and treatment, out with clusterProfiler for the up-regulated and the exact mechanisms of fibrosis accounting for the down-regulated genes respectively(19). The enriched cardiac dysfunction and adverse outcome are not GO and KEGG terms were considered significant fully understood. Therefore, careful dissections of with the cut-off criteria of adjust P-value < 0.05 the cell biological mechanisms are of primary im- portance in the development of effective therapies. Protein-protein interaction network con- In recent years, the advancement of microar- struction and module analysis ray and high throughput sequencing technologies In order to interpret the molecular mecha- has provided an efficient tool to decipher critical nisms of key cellular activities in cardiac fibrosis, genetic alternations in cardiac fibrosis and to iden- the online Search Tool for the Retrieval of Interact- tify various key genes, molecular pathways, bio- ing Genes (STRING, http://string-db.org/) database logical processes, and cellular behaviors (14-16). In was used to construct a protein-protein interaction the present study, a large-scale RNA sequencing (PPI) network of the DEGs(20), which was selected data (GSE97358) downloaded from Gene Expres- and visualized with confidence score ≥0.4(medium sion Omnibus (GEO) database were employed to confidence score). According to the degree of im- acquire the differentially expressed genes (DEGs). portance, significant modules of PPI network were We further explored the development of cardiac fi- screened out using the plug-in Molecular Complex brosis by a way of DEGs functional enrichment and Detection (MCODE) with the degree cutoff =2, interaction network analysis. The hub gene-tran- node score cutoff=0.2, k-core=5 and max dept =100 scription factor interaction network was also con- in the Cytoscape (version 3.6). Moreover, the func- structed. The present study aimed to identify crucial tion and pathway enrichment analyses were also genes and pathways involved in cardiac fibrosis by performed for DEGs in the significant modules. using bioinformatics analysis, which may result in a better understanding of the pathological mecha- Construction of hub gene-transcription fac- nisms of cardiac fibrosis. tor interaction network The hub genes were extracted from the PPI Materials and methods network and identified by using the Cytoscape plug-in CytoHubba which provides a user-friend- Identification of differentially expressed ly interface to explore important nodes in biolog- genes ical networks, and the Maximal Clique Centrality The public raw RNA sequencing data (MCC) method which has a better performance was (GSE97358) was obtained from GEO data- used(21). The transcription factor (TF) which may base (https://www. ncbi.nlm.nih.gov/gds/?ter - target hub genes were predicted by using the Cyto- m=GSE97358)(16). The dataset was deposit- scape plug-in iRegulon. As reported, iRegulon can ed by Schafer et al. in 2017 and comprised 84 enrich TF motifs based on their direct targets with TGF-β1-stimulated samples and 84 paired unstim- the position weight matrix method(22). The gene sets ulated samples of cultured primary human cardiac and TF-target pairs on iRegulon were derived from Identification of potential key genes associated with cardiac fibrosis by rna sequencing data analysis 2317

ENCODE ChIP-seq data, and the TRANSFAC Gene ontology and pathway enrichment and JASPER databases. In the present study, the analysis potential TFs corresponding to the hub genes were Through GO analysis, the enriched go terms identified by the motif enrichment analysis with the were classified into biological process (BP) and criteria that the between orthologous genes ≥0.05 molecular function (MF). As shown in Figure 1, and false discovery rate (FDR) on motif similarity 13 terms in BP ontology for up-regulated DEGs ≤ 0.001, and normalized enrichment score (NES) were enriched, such as extracellular matrix or- >5. Finally, the hub gene-transcription factor inter- ganization (17 genes), extracellular structure or - action networks were visualized by the Cytoscape ganization (17 genes), muscle system process (19 software. genes), cardiac muscle tissue development (19 genes) and muscle contraction (15 genes), etc. In Statistical analysis the MF ontology, 6 terms for up-regulated DEGs Statistical analyses were performed using R were enriched, including receptor regulator activ- software v3.4.3 (R Foundation for Statistical Com- ity (22 genes), receptor ligand activity (21 genes), puting, Vienna, Austria). As for DEGs, the genes binding (6 genes), growth factor activity were considered significant with the cut-off criteria (9 genes), G-protein coupled receptor binding (11 |log2FC| ≥1, P-value < 0.05 and adjust P-value < genes) and hormone activity (7 genes). In term of 0.05. As for GO and KEGG terms, the terms were the down-regulated DEGs, 58 terms concerning considered significant with the cut-off criteria of BP ontology were enriched, including response to adjust P-value < 0.05. mechanical stimulus (15 genes), cellular response to interferon-gamma (12 genes), primary alcohol Results metabolic process (8 genes), retinol metabolic pro- cess (6 genes), response to interferon-gamma (12 Identification of DEGs genes), chronic inflammatory response (5 genes), Based the cut-off criteria, a total of 647 DEGs etc. For the MF ontology, 8 terms were significant- were identified in TGF-β1-stimulated primary hu- ly enriched including cytokine binding (9 genes), man cardiac fibroblast compared to the unstimu- cytokine activity (13 genes), oxidoreductase activi- lated, consisting of 341 down-regulated and 306 ty, acting on the aldehyde or oxo group of donors (6 up-regulated genes. The heatmap for the DEGs are genes), drug transmembrane transporter activity (4 shown in Figure 1. genes), cytokine receptor binding (13 genes), drug transporter activity (4 genes), substrate-specific channel activity (16 genes) and cation channel ac- tivity (13 genes). According to the KEGG pathway enrichment analysis(Figure 1), up-regulated genes were signif- icantly enriched in Wnt signaling pathway(IGF1/ LEFTY2/WNT2/WNT7B/WNT11/WNT9A/ WNT4/WNT5B/INHBE), signaling pathways regulating pluripotency of stem cells (IGF1/ LEFTY2/WNT2/WNT7B/ WNT11 /WNT9A/ WNT4/WNT5B/INHBE), Cushing syndrome (CDKN2B/KCNK3/PLCB4/WNT2/ WNT7B/ Figure 1: The heatmap, protein-protein interaction(PPI), GO WNT11/WNT9A/WNT4/WNT5B), hippo sign- (gene ontology) and KEGG(Kyoto Encyclopedia of Genes and aling pathway (WNT2/ WNT7B/ WNT11/ WN- Genomes) enrichment analyses for the differentially expressed T9A/WNT4/WNT5B/NKD1/GDF7), mTOR genes (DEGs). A. heatmap for the DEGs(341 down-regulated signaling pathway (IGF1/WNT2/WNT7B/ and 306 up-regulated). Red: up-regulation; Green: down-regu- WNT11/WNT9A/WNT4/WNT5B), basal cell lation. B. PPI network for the DEGs with confidence score ≥0.4, carcinoma (WNT2/WNT7B/WNT11/WNT9A/ the disconnected nodes were hidden. C. GO(biological process WNT4/WNT5B), melanogenesis (PLCB4/ and molecular function) and KEGG enrichment analyses for WNT2/WNT7B/WNT11/WNT9A/ WNT4/ up-regulated DEGs. D. GO(biological process and molecular WNT5B), breast cancer (IGF1/WNT2/WNT7B/ function) and KEGG enrichment analyses for down-regulated DEGs. WNT11/WNT9A/FGF21/WNT4/WNT5B), gas- 2318 Dandan Liu, Haizhu Wang et Al tric cancer (CDKN2B/WNT2/WNT7B/WNT11/ pled receptor binding, frizzled binding, G-protein WNT9A/FGF21/WNT4/WNT5B). Down-regu- coupled receptor activity, peptide receptor late genes were mainly enriched in retinol metab- activity, G-protein coupled amine receptor activi- olism (ADH1B/ADH4/ALDH1A1/AOX1/RDH5/ ty were enriched in MF ontology. Neuroactive li- DHRS9/ CYP26B1/CYP27C1), tyrosine metab- gand- receptor interaction (ADORA2B/ ADRA2A/ olism (ADH1B/ADH4/ALDH1A3/AOX1/HPD/ ADRB2/CYSLTR2/DRD1/EDNRA/F2R/F2RL2/ MAOA), cytokine-cytokine receptor interaction F2RL3/HTR1D/ HTR2B/LHB/ MC4R/RXFP1/ (TNFRSF8/CXCL1/IL1B/IL1R1/IL1RN/IL6R/ S1PR5/SSTR1/VIPR1) and Wnt signaling path- INHBB/ CXCL6/CX3CL1/TNFRSF1B/IL1R2/ way (PLCB4/ WNT11/WNT2/ WNT2B/WNT4/ GDF5/TNFSF14/ACKR4/IL20RA/IL26/IL34), WNT5B/WNT7B/WNT9A) were enriched in the drug metabolism- cytochrome P450 (ADH1B/ KEGG pathway analysis. ADH4/ALDH1A3/AOX1/FMO2/GSTA1/GSTA2/ MAOA), calcium signaling pathway (ADORA2B/ Hub genes selection and gene-transcription ADRB2/ATP2B4/CAMK2B/CD38/EDNRA/ F2R/ factor interaction network HTR2B/P2RX7/PDE1A/CYSLTR2). The top 20 genes higher degrees selected by the MCC method of CytoHubba plug-in were PPI network construction and module analysis identified as the hub genes and sequentially or - PPI network was constructed on the basis of dered as follows: GNG2, LPAR5, KISS1, PLCB4, the STRING database and are displayed in Figure F2R, HTR2B, GPR65, GPR68, CYSLTR2, F2RL2, 1. Of which, the disconnected nodes were hidden. F2RL3, EDNRA, CXCL1, CXCR5, CXCL6, GAL, Subsequently, the network complex was further HTR1D, TAS2R1, S1PR5 and SSTR1 (Figure 3A). analyzed, and the most significant module was screened out according to the cut-off criteria by us- ing MCODE.

Figure 3: The network for hub genes and transcription factors. A. The first 20 DEGs of the MMC method were chosen using CytoHubba plug-in to construct the hub ge- nes network. The more forward ranking is represented by a redder color. B. The network of transcription factors and hub genes by iRegulon plug-in. Yellow: transcription fac- tors; White: hub genes

Figure 2: Top 4 modules from the PPI network by MCO- The mircoarray-based expressions of the hub DE plug-in. (module 1, module 2, module 3, module 4). genes were displayed in Table 1. Using the iReg- Red: up-regulated genes; Green: down-regulated genes. ulon plug-in, sixteen of twenty hub genes may be targeted by seven TFs (identity between orthol- As a result, four most significant modules ogous genes ≥ 0.05, FDR on motif similarity ≤ containing 42 nodes were identified (Figure 2). 0.001, and NES > 5). The TF-hub genes networks Then we performed GO and KEGG pathway en- were illustrated as Figure 3B, of which the seven richment analyses for these genes in the selected TFs(RELB, FOS, SREBF2, PURA, TBX21, IRF1 modules. The results showed that these genes were and IRF4) were listed. mainly associated with, in term of BP ontology, G-protein coupled receptor signaling pathway, Discussion coupled to cyclic nucleotide second messenger, positive regulation of cytosolic calcium ion con- Cardiac fibrosis is frequently observed in pa- centration involved in smooth muscle contraction, tients with hypertension, adriamycin-related, is- regulation of tube diameter; while G-protein cou- chemic, dilated, diabetic and hypertrophic cardio- Identification of potential key genes associated with cardiac fibrosis by rna sequencing data analysis 2319 myopathy particularly evident in the progression to tion, extracellular structure organization, and mus- heart failure. Implementation of anti-fibrotic strat- cle contraction at the level of BP and receptor regu- egies has been proposed as a promising therapeutic lator activity, receptor ligand activity and G-protein approach for patients with these diseases. coupled receptor binding at the level of MF. The down-regulated DEGs were mainly en- Gene symbol Log FC adj.P.Val 2 riched in response to response to mechanical stim- Up-regulated ulus and cellular response to interferon-gamma S1PR5 2.28 1.45×10-17 at the level of BP and cytokine binding, cytokine

F2RL3 1.86 5.44×10-14 activity and oxidoreductase activity at the level of MF. Meanwhile, KEGG pathway enrichment GPR68 1.56 8.00×10-16 analysis showed that the up-regulated DEGs were CXCR5 1.42 6.69×10-6 mostly involved in Wnt signaling pathway, signal- ing pathways regulating pluripotency of stem cells, KISS1 1.42 1.61×10-3 Cushing syndrome and hippo signaling pathway, GAL 1.33 5.15×10-9 while the down-regulated DEGs were significantly LPAR5 1.24 2.05×10-6 enriched in cytokine-cytokine receptor interaction, retinol metabolism, drug metabolism- cytochrome HTR1D 1.12 2.84×10-13 P450 and calcium signaling pathway. PLCB4 1.01 2.94×10-14 Finally, Wnt signaling pathway and neuroac- Down-regulated tive ligand-receptor interaction signaling pathway

CXCL1 -1.00 2.54×10-2 were identified as the major pathways by the im- portant module analyses of DEGs. Also, twenty GPR65 -1.03 2.25×10-9 hub genes and a network with potential TFs were CYSLTR2 -1.05 2.68×10-4 predicted. These enriched pathways and hub genes may provide insights into the molecular mechanism EDNRA -1.12 1.62×10-11 of cardiac fibrosis, and can therefore be beneficial CXCL6 -1.13 7.30×10-3 for the development of new therapeutic strategies.

F2R -1.20 6.84×10-18 In recent years, multiple potential mecha- nisms accounting for the cardiac fibrosis have been -12 GNG2 -1.22 1.08×10 proposed by many individuals in-vivo and in-vit- F2RL2 -1.24 1.13×10-6 ro studies, while most studies lack systematization

SSTR1 -1.27 1.23×10-5 and large- scale samples. RNA-sequencing profile provides a global view of and ena- -8 TAS2R1 -1.29 1.67×10 bles identification of critical genes and pathways in HTR2B -1.85 1.03×10-8 cardiac fibrosis with a comprehensive perspective. FC, fold change As suggested by the current study with 84 human cardiac fibroblast samples treated with or without Table 1: The 20 hub up-regulated and down-regulated genes. TGF-β1 stimulating, Wnt signaling pathway was demonstrated to be a major pathway associated However, the rationale for these approach- with cardiac fibrosis, which was in line with the es remains poorly developed due to the lack of a findings by previous studies. The Wnt/β-catenin comprehensive understanding of the etiology and axis is known to promote fibroblast activation and pathogenesis. Therefore, it is of vital importance to proliferation during cardiac fibrosis via multiple explore the etiological and molecular mechanisms downstream effectors such as T-cell factor (TCF)/ of cardiac fibrosis for therapy and prevention. In lymphocyte enhancing factor (LEF) group of tran- the present study, we investigated potential genes scription factors, stem cell factor, accreted Friz- correlated with cardiac fibrosis using bioinformat- zled-related , GSK-3β,Wnt1-induced se- ics analysis. A total of 647 DEGs including 341 creted protein-1, Rho/ROCK and Rac/JNK, planar down-regulated and 306 up-regulated genes were cell polarity and Hippo pathway(23). Activation of initially identified. Furthermore, results from GO Wnt signaling pathway has been shown to be caus- analysis indicated that the up-regulated DEGs were al to epicardial fibrosis in pediatric failed heart al- mostly involved in extracellular matrix organiza- lografts with diastolic dysfunction(24). 2320 Dandan Liu, Haizhu Wang et Al

Studies have also confirmed an essential role is the most up-regulated hub gene in response to for Wnt/β-catenin signaling in mediating cardiac TGF-β1 stimulating, further investigation seems fibrosis of hypertensive heart disease (25-27). Moreo- necessary to clarify underlying biological links ver, the neuroactive ligand-receptor interaction sig- between S1PR5 and cardiac fibrosis. F2RL3 (F2R naling pathway was also demonstrated to be signif- like or trypsin receptor 3), also known as icantly associated with cardiac fibrosis. Although PAR4 (pro-apoptotic WT1 regulator), was reported few study have systematically reported a role of to play a role in blood coagulation and inflamma- the pathway in the pathogenesis of cardiac fibrosis, tion, and its hypomethylation was a strong predic- there was evidence showing a cardioprotection ef- tor of mortality from cardiovascular diseases in fect of neuroactive ligand-receptor interaction sig- smoking populations(33). The expression of PAR4 naling pathway induced by sevoflurane in patients was also found elevated with in fibrosis diabetic undergoing coronary artery bypass graft surgery(28). cardiomyopathy but subsequently reduced with ar- Moreover, transcriptomic study revealed gatroban treatment (34). Moreover, the activation of that te activation of neuroactive ligand-recep- PAR4 has been shown to contribute to the patho- tor interaction signaling pathway mediated by a genesis of various pulmonary diseases including herb compound danhong injection was found to fibrosis caused by serine proteinases(35). have a neuroprotective effect against cerebral is- Therefore, it is biologically plausible to spec- chemia/reperfusion-induced injury(29), while mi- ulate the role of F2RL3 (PAR4) in the cardiac fi- croRNAs-mediated inhibition of neuroactive li- brosis. For the most down-regulated hub gene gand-receptor interaction signaling pathway was HTR2B(5-hydroxytryptamine (serotonin) recep- implicated in α-synuclein toxicity in early stage tor 2B), also known as 5-HT2B, the protein and of drosophila parkinson's disease model(30). In the mRNA expression was ever found to be enhanced present study, most differentially expressed genes in the pulmonary fibrosis in rats(36), while an- in the neuroactive ligand-receptor interaction sig- other study have demonstrated a cardioprotective naling pathway were down-regulated following function of the HTR2B in an integrated model of TGF-β1 stimulating, suggesting a possible role of hypertensive diastolic dysfunction with preserved the inhibition of this pathway in the TGF-β1-in- ejection fraction by inhibiting cardiac fibrosis and duced cardiac fibrosis. Therefore, the current study remodeling(37). The inconsistence may be due to provided a potential new insight into the molecular a tissue-specific effect with unknown mechanism. mechanism of cardiac fibrosis. Nevertheless, this In line with the previous study(37), our results also finding was only based on the bioinformatics anal- indicated that cardiac fibrosis may be associated ysis, which required further in-depth verification with TGF-β1-induced inhibition of HTR2B. There by well-designed in-vivo and in-vitro experiments. were also some studies focusing on the association We also constructed the PPI network with between other hub genes concerned and cardiac fi- DEGs to illustrate the overview of their function- brosis, but less information was provided. Molec- al connections, and constructed the hub gene- ular biology experiments are required to determine TF network to explore the molecular mecha- the functions of these hub genes in cardiac fibrosis nism of cardiac fibrosis. Twenty DEGs including the future. GNG2, LPAR5, KISS1, PLCB4, F2R, HTR2B, Furthermore, the TF-hub gene regulatory GPR65, GPR68, CYSLTR2, F2RL2, F2RL3, ED- network has presented several potentially impor- NRA, CXCL1, CXCR5, CXCL6, GAL, HTR1D, tant TFs (RELB, FOS, SREBF2, PURA, TBX21, TAS2R1, S1PR5 and SSTR1 were identified as IRF1 and IRF4) in cardiac fibrosis. RELB (RELB the hub genes. Of which, S1PR5(sphingosine-1- proto-oncogene, NF-kB subunit) is one of the five phosphate receptor 5) was an important member family members of the dimeric transcription fac- of endothelial differentiation gene receptor family tor nuclear factor kappa B (NFκB) (38). Previous which were described as an important mediator in study have indicated that RELB was involved in the balance between the production of extracellular TAX1BP1-mediated cardioprotective effect against matrix (ECM) and its degradation(31). cardiac hypertrophy and fibrosis by regulating au- Studies have also demonstrated a role for tophagy in STZ-induced diabetic cardiomyopathy endothelial differentiation gene receptors in cyst- in mice, while RELB knockdown disrupted the ic fibrosis(32), however, the exact role of S1PR5 in protective effect(39). The role of FOS (Fos proto-on- the fibrosis remains unclear. Noteworthily, S1PR5 cogene, AP-1 transcription factor subunit) in car - Identification of potential key genes associated with cardiac fibrosis by rna sequencing data analysis 2321 diac fibrosis has been frequently reported particu- 3) Kong P, Christia P, Frangogiannis NG. The pathogenesis larly in angiotensin II-induced cardiac hypertrophy of cardiac fibrosis. 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