Emergency. 2018; 6 (1): e40 OR I G I N A L RE S E A RC H New Molecular Aspects of Cardiac Arrest; Promoting Car- diopulmonary Resuscitation Approaches Mona Zamanian-Azodi1, Mostafa Rezaei Tavirani1∗, Mohammad Rostami-Nejad2, Fatemeh Tajik-Rostami3 1. Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran. Received: May 2018; Accepted: July 2018; Published online: 2 July 2018 Abstract: Introduction: Cardiopulmonary resuscitation (CPR) is a method to improve survival of patients with cardiac arrest. This study aimed to identify the key genes affected five minutes after cardiac arrest, hoping to elevate the efficacy of CPR. Methods: In this bioinformatics study differentially expressed genes of six pigs were downloaded from GEO and screened. The significant and characterized genes were analyzed via calculating fold change and protein-protein interaction (PPI) networks. The crucial nodes were determined based on centrality parame- ters and their related biological processes were investigated via ClueGO. Results: 17 significant up-regulated (LogFC ≥ 2) and 22 down-regulated (LogFC < -0.5) genes were detected. Transthyretin (TTR logFC = 4.59) and Gonadotropin-releasing hormone receptor (GNRHR logFC = 3.84) had higher logFC among up-regulated and down-regulated genes, respectively. The critical genes including four up-regulated and five down-regulated genes were detected from network analysis. GNRHR and Prolactin precursor (PRL) were among the most im- portant down res 5 minutes after cardiac arrest and Beta-2 adrenergic receptor and Cadherin-1 were among the most important up regulated gens. Conclusion: The introduced potential biomarkers could reveal a new molecular aspect for CPR performance and pituitary gland protection was highlighted in this respect. Keywords: Cardiac Arrest; Cardiopulmonary Resuscitation; Protein Interaction Maps; Gene Ontology, Biomarkers © Copyright (2018) Shahid Beheshti University of Medical Sciences Cite this article as: Zamanian-Azodi M, Rezaei Tavirani M, Rostami-Nejad M, Tajik-Rostami F. New Molecular Aspects of Cardiac Arrest; Promoting Cardiopulmonary Resuscitation Approaches. 2018; 6(1): e40. 1. Introduction C ardiopulmonary resuscitation (CPR) is established and developed to increase perfusion in cardiac arrest patients and improve their survival (1). Although re- suscitation science has progressed remarkably, poor survival of cardiac arrest patients is a still a problem in medicine (2). There are evidence that the majority of survivors are neurologically damaged in the short term, which can lead to long term disorders (3). Post cardiac arrest syndrome as well as high rate of in hospital mortality after CPR are reported and discussed (4). ∗Corresponding Author: Mostafa Rezaei Tavirani; Shahid Beheshti University of Medical Sciences, Velenjak, Shahid Aarabi Avenue, Tehran, Iran. Email: tavi- rany@yahoo.com Tel: +982122439787 Attempts have been made to understand the molecular and cellular aspects of CPR, which can help to improve the qual- ity of life in patients who survive (5). In addition, treatment with chemical reagents could improve the outcome of CPR performance. For instance, it has been reported that nitric oxide inhalation improves CPR outcome in animal model (6). Recently, high throughput molecular investigations includ- ing proteomics and genomics have provided large amounts of data and have attracted the attention of researchers in var- ious fields of medicine and pharmacology. Martijn and Wik- lund published valuable microarray data about CPR in pigs, which is a useful molecular source about CPR (7). There are various methods that are useful for decreasing the vol- ume of data and highlighting the remarkable components (8). Protein-protein interaction (PPI) networks analysis is an attractive method to screen disease-related genes (9, 10). In this approach, the genes or proteins are organized in an in- teractome unit and the critical elements are identified (11, This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com M. Zamanian-Azodi et al. 2 12). In this study, the aim was to identify crucial CPR related genes among the large number of genes introduced by Mar- tijn and Wiklud (7) using PPI network analysis. The findings will promote molecular aspects of CPR, which is important to elevate the efficacy of CPR methods. 2. Methods 2.1. Study design and setting This bioinformatics study was conducted via evaluating gene expression changes in the animal model of cardiac ar- rest 5 minutes after its incidence, for better programing of treatment approaches and CPR performance. The selected groups were from one genomic study conducted by Martijn and Wiklud (7). In the mentioned original study, three groups are available with different time courses and treatments. The protocol of the present study was approved by ethics com- mittee of Shahid Beheshti University of Medical Sciences. 2.2. Participants Data of differentially expressed genes of six pigs’ brain sam- ples (Sus scrofa) were downloaded from Gene Expression Omnibus (GEO). The animals were cardiac arrested as de- scribed in the report of Miclescu, Basu, and Wiklund (13). 3 animals in control group (0 minute after cardiac arrest) and 3 in case group (5 minutes after cardiac arrest) were considered for analysis. 2.3. Procedure After downloading and screening 250 differentially expressed genes from GEO, the next step was to construct a network of interactions. The hub-nodes were identified via mean ± 2 standard deviation cut off on degree values and the top 5% of the nodes based on betweenness centrality were con- sidered as bottleneck-genes. Common hub and bottleneck genes were introduced as hub-bottleneck nodes (the crucial genes). Detail of gene expression assay is explained in the report of Martijn and Wiklud (7). Box plot finding indicates that the mid points of data are in the same range; therefore, samples are comparable in terms of gene expression. 2.4. Statistical analysis The differentially expressed genes with a fold change (FC) above 2 (for up-regulated genes) and below -0.5 (for down- regulation) were selected for analysis. Considering p ≤ 0.01 and elimination of uncharacterized genes, the candidate genes were determined. The PPI network was constructed using Cytoscape software version 3.6.0 via its STRING plugin (14). ClueGO was used for gene ontology analysis of the in- troduced key genes. 3. Results: 3.1. Fold change analysis LogFC of the 59 differentially expressed genes is calcu- lated and shown in figure 1 (37 up-regulated and 22 down- regulated). Based on fold change analysis, 17 significant up-regulated (LogFC ≥ 2) and 22 significant down-regulated (LogFC < -0.5) genes were detected. Transthyretin (TTR logFC = 4.59) and Gonadotropin-releasing hormone receptor (GNRHR logFC = 3.84) had higher logFC among up-regulated and down-regulated genes, respectively. 3.2. PPI network analysis The PPI network contained 29 isolated nodes and a main connected component including 72 linked genes with 634 edges (figure 2). The critical genes including four up- regulated and five down-regulated genes were detected via network analysis and listed in table 1. GNRHR and Prolactin precursor (PRL) were among the most important down- regulated genes 5 minutes after cardiac arrest and Beta-2 adrenergic receptor and Cadherin-1 were among the most important up-regulated genes based on this analysis. GNRHR is highlighted as the top central gene following PPI network analysis; however, TTR was not remarkable in this analysis. 4. Discussion There are many investigations about events occurring after a cardiac arrest and intervention approaches in this regard. Many factors could play a role in the quality of life after CPR. One of the key factors is timing (7). To improve the medical care in this state, understanding the pathophysiology of CA is critical. Investigating molecular mechanisms could assist in reaching this goal. Molecular changes are the main corre- sponding features of any organism’s profile (11, 12). In this respect, one way is to analyze gene expression profile of pa- tients with cardiac arrest to set new diagnosis and treatment strategies. In our bioinformatics study, animal model of car- diac arrest was selected for further evaluations to provide a molecular view of cardiac arrest for promoting CPR proce- dure. Comparison of samples depicted that there are genes with significant expression values, in which up-regulation is dominant. These vast expression changes within 5 minutes post cardiac arrest express that there are complex molecu- lar changes in this state. Further analysis evaluates the role and contribution of these genes to pathophysiology 5 min- utes after cardiac arrest, which can lead to organ injury. TTR and GNRHR were the most up-regulated and down-regulated genes in the study, respectively. Plasma TTR with high concentration level is responsible for transportation of thyroxine and retinol, but within the mam- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com 3 Emergency. 2018; 6 (1): e40 Figure 1: Log fold change (FC) of the 59 differentially expressed genes. Blue color: up-regulated genes; red color: down-regulated genes. Table 1: List of central genes (hub-bottleneck nodes) of the main connected component (only including query genes) Genes Description Degree Centrality* GNRHR Gonadotropin-releasing hormone receptor 22 0.05 PRL Prolactin precursor 21 1.00 ADRB2 Beta-2 adrenergic receptor 20 0.77 LHB Lutropin subunit beta 18 0.04 AMCF-II Alveolar macrophage chemotactic factor 2 17 0.19 CDH1 Cadherin-1 14 0.02 MMP-13 Matrix Metalloproteinase-13 13 o.57 INSR Insulin receptor 12 0.00 IGF2 Insulin-like growth factor II 11 0.13 *Normalized betweenness centrality; Red color: up-regulation; Green color: down-regulation. malian central nervous system it may play another role (16). It seems that, the vast expression change of TTR may be cor- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com M. Zamanian-Azodi et al. 4 Figure 2: The main connected component of Protein-protein interaction network of the cardiac arrested pigs. The bigger size and the blue color nodes refer to higher degree value. The uncharacterized nodes are shown in the bottom right corner. related to the possible decrement of thyroxin hormone, the concentration of which is controlled by the pituitary gland. GNRHR and its GNRH are important endocrine elements in regulation of reproduction (17). Nine crucial genes are recog- nized as vital elements of cardiac arrest PPI network, which are divided in the two sub-groups of up-regulated and down- regulated genes (see table 1). It seems that biological inter- actions between the nine highlighted genes may play signif- icant roles in cardiac arrest and could be important for CPR. It is reasonable to consider ADRB2, CDH1, IGF2, INSR, PRL, LHB, and GNRHR as candidate biomarker panel of cardiac arrest after 5 minutes. It is reported that ADRB2 affects the lungs to change fluid clearance (18). Various types of activity such as role in differ- ent cancers, axon growth, and brain metabolism are reported for CDH1 gene (19-22). Insulin-like growth factor II is an em- bryonic growth factor and its expression is reported in most tissues. The relationship between IGF2 and a number of can- cers and cardiomyopathy has been investigated (23, 24). A glucose-insulin-potassium infusion is considered for cardiac arrest; however, it does not have an effect on reduction of mortality (25). It seems that insulin (or its receptor) is linked to cardiac arrest (26). PRL and GNRH are the two important hormones of pituitary gland and their well-known function is to play a critical role in lactation and fertility (27, 28). Subunit beta of gonadal lutropin is responsible for receptor binding of the hormone (29). As mentioned, the crucial genes are directly related to pitu- itary gland. Thus, this finding implies that the protection of this vital gland could be critical during CPR. Hence, simul- taneous treatment intervention is suggested for CPR promo- tion. On the other hand, the biological processes that are re- lated to the pituitary gland may be damaged in the survivors. It is possible that a young survivor loses fertility or experi- ences some related disorders. The other significant point is the possible role of these critical genes in increasing the per- centage of successful administration of CPR. Complemen- tary research on survivors is required to support the findings of this study. 5. Conclusion The finding indicates that pituitary gland is a sensitive part during cardiac arrest and its protection should be considered in CPR guidelines. 6. Appendix 6.1. Acknowledgements This project is supported by Shahid Beheshti University of Medical Sciences. 6.2. Author contribution All authors meet the standard criteria of authorship based on the recommendations of the international committee of medical journal editors. 6.3. Funding This project is supported by Shahid Beheshti University of Medical Sciences. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com 5 Emergency. 2018; 6 (1): e40 6.4. Conflict of interest The authors declare that they have no conflict of interest. References 1. Cave DM, Gazmuri RJ, Otto CW, Nadkarni VM, Cheng A, Brooks SC, et al. Part 7: CPR techniques and devices. Cir- culation. 2010;122(18 suppl 3):S720-S8. 2. Yeung J, Meeks R, Edelson D, Gao F, Soar J, Perkins GD. The use of CPR feedback/prompt devices during train- ing and CPR performance: a systematic review. Resusci- tation. 2009;80(7):743-51. 3. Zhao H, Li C-S, Gong P, Tang Z-R, Hua R, Mei X, et al. Molecular mechanisms of therapeutic hypothermia on neurological function in a swine model of cardiopul- monary resuscitation. Resuscitation. 2012;83(7):913-20. 4. Minamishima S, Bougaki M, Sips PY, De Yu J, Mi- namishima YA, Elrod JW, et al. Hydrogen sulfide im- proves survival after cardiac arrest and cardiopulmonary resuscitation via a nitric oxide synthase 3–dependent mechanism in mice. Circulation. 2009;120(10):888-96. 5. Bottiger BW, Motsch J, Braun V, Martin E, Kirschfink M. Marked activation of complement and leukocytes and an increase in the concentrations of soluble endothelial adhesion molecules during cardiopulmonary resuscita- tion and early reperfusion after cardiac arrest in humans. Critical care medicine. 2002;30(11):2473-80. 6. Minamishima S, Kida K, Tokuda K, Wang H, Sips PY, Ko- sugi S, et al. Inhaled Nitric Oxide Improves Outcomes Af- ter Successful Cardiopulmonary Resuscitation in Mice- Clinical Perspective. Circulation. 2011;124(15):1645-53. 7. Martijn C, Wiklund L. Effect of methylene blue on the genomic response to reperfusion injury induced by car- diac arrest and cardiopulmonary resuscitation in porcine brain. BMC medical genomics. 2010;3(1):27. 8. Navlakha S, Kingsford C. The power of protein interac- tion networks for associating genes with diseases. Bioin- formatics. 2010;26(8):1057-63. 9. Nguyen T-P, Liu W-c, Jordan F. Inferring pleiotropy by network analysis: linked diseases in the human PPI net- work. BMC systems biology. 2011;5(1):179. 10. Karbalaei R, Allahyari M, Rezaei-Tavirani M, Asadzadeh- Aghdaei H, Zali MR. Protein-protein interaction analy- sis of Alzheimers disease and NAFLD based on systems biology methods unhide common ancestor pathways. Gastroenterology and Hepatology from bed to bench. 2018;11(1):27. 11. Safari-Alighiarloo N, Taghizadeh M, Rezaei-Tavirani M, Goliaei B, Peyvandi AA. Protein-protein interaction net- works (PPI) and complex diseases. Gastroenterology and Hepatology from bed to bench. 2014;7(1):17. 12. Peyvandi H, Peyvandi AA, Safaei A, Azodi MZ, Rezaei- Tavirani M. Introducing Potential Key Proteins and Path- ways in Human Laryngeal Cancer: A System Biology Approach. Iranian Journal of Pharmaceutical Research: IJPR. 2018;17(1):415. 13. Miclescu A, Basu S, Wiklund L. Cardio-cerebral and metabolic effects of methylene blue in hypertonic sodium lactate during experimental cardiopulmonary resuscitation. Resuscitation. 2007;75(1):88-97. 14. Bai B, Xie B, Pan Z, Shan L, Zhao J, Zhu H. Identification of candidate genes and long non-coding RNAs associ- ated with the effect of ATP5J in colorectal cancer. Inter- national journal of oncology. 2018;52(4):1129-38. 15. Mlecnik B, Galon J, Bindea G. Comprehensive functional analysis of large lists of genes and proteins. Journal of proteomics. 2018;171:2-10. 16. Herbert J, Wilcox JN, Pham K-TC, Fremeau RT, Zeviani M, Dwork A, et al. Transthyretin A choroid plexus-specific transport protein in human brain: The 1986 S. Weir Mitchell Award. Neurology. 1986;36(7):900-. 17. Jiang Z, Gibson JP, Archibald AL, Haley CS. The porcine gonadotropin-releasing hormone receptor gene (GN- RHR): genomic organization, polymorphisms, and as- sociation with the number of corpora lutea. Genome. 2001;44(1):7-12. 18. Snyder EM, Turner ST, Johnson BD. β2-adrenergic recep- tor genotype and pulmonary function in patients with heart failure. Chest. 2006;130(5):1527-34. 19. Graziano F, Humar B, Guilford P. The role of the E- cadherin gene (CDH1) in diffuse gastric cancer suscep- tibility: from the laboratory to clinical practice. Annals of oncology. 2003;14(12):1705-13. 20. Pannone G, Santoro A, Feola A, Bufo P, Papagerakis P, Lo Muzio L, et al. The role of E-cadherin down-regulation in oral cancer: CDH1 gene expression and epigenetic blockage. Current Cancer Drug Targets. 2014;14(2):115- 27. 21. Konishi Y, Stegmuller J, Matsuda T, Bonni S, Bonni A. Cdh1-APC controls axonal growth and patterning in the mammalian brain. Science. 2004;303(5660):1026-30. 22. Rodriguez-Rodriguez P, Almeida A, BolaÃśos JP. Brain en- ergy metabolism in glutamate-receptor activation and excitotoxicity: role for APC/C-Cdh1 in the balance gly- colysis/pentose phosphate pathway. Neurochemistry in- ternational. 2013;62(5):750-6. 23. Steegers-Theunissen RP, Obermann-Borst SA, Kremer D, Lindemans J, Siebel C, Steegers EA, et al. Periconcep- tional maternal folic acid use of 400 µg per day is related to increased methylation of the IGF2 gene in the very young child. PLoS One. 2009;4(11):e7845. 24. Brade T, Kumar S, Cunningham TJ, Chatzi C, Zhao X, Cav- allero S, et al. Retinoic acid stimulates myocardial expan- sion by induction of hepatic erythropoietin which acti- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com M. Zamanian-Azodi et al. 6 vates epicardial Igf2. Development. 2011;138(1):139-48. 25. Mehta SR, Yusuf S, Diaz R, Zhu J, Pais P, Xavier D, et al. Effect of glucose-insulin-potassium infusion on mor- tality in patients with acute ST-segment elevation my- ocardial infarction: the CREATE-ECLA randomized con- trolled trial. Jama. 2005;293(4):437-46. 26. Stellpflug SJ, Harris CR, Engebretsen KM, Cole JB, Holger JS. Intentional overdose with cardiac arrest treated with intravenous fat emulsion and high-dose insulin. Clinical toxicology. 2010;48(3):227-9. 27. La Rosa S, Celato N, Uccella S, Capella C. Detection of gonadotropin-releasing hormone receptor in normal hu- man pituitary cells and pituitary adenomas using im- munohistochemistry. Virchows Archiv. 2000;437(3):264- 9. 28. Freeman ME, Kanyicska B, Lerant A, Nagy G. Prolactin: structure, function, and regulation of secretion. Physio- logical reviews. 2000;80(4):1523-631. 29. Cosowsky L, Rao SV, Macdonald GJ, Papkoff H, Camp- bell RK, Moyle WR. The groove between the α-and β- subunits of hormones with lutropin (LH) activity ap- pears to contact the LH receptor, and its conformation is changed during hormone binding. Journal of Biological Chemistry. 1995;270(34):20011-9. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: www.jemerg.com Introduction Methods Results: Discussion Conclusion Appendix References