Volume 27, Issue 6 (11-2023)                   IBJ 2023, 27(6): 375-387 | Back to browse issues page

PMID: 38224029


XML Print


Abstract:  
Background: Renal transplantation plays an essential role in the quality of life of patients with end-stage renal disease. At least 12% of the renal patients receiving transplantations show graft rejection. One of the methods used to diagnose renal transplantation rejection is renal allograft biopsy. This procedure is associated with some risks such as bleeding and arteriovenous fistula formation. In this study, we applied a bioinformatics approach to identify serum markers for graft rejection in patients receiving a renal transplantation.
Methods: Transcriptomic data were first retrieved from the blood of renal transplantation rejection patients using the GEO database. The data were then used to construct the protein-protein interaction and gene regulatory networks using Cytoscape software. Next, network analysis was performed to identify hub-bottlenecks, and key blood markers involved in renal graft rejection. Lastly, the gene ontology and functional pathways related to hub-bottlenecks were detected using PANTHER and DAVID servers.
Results: In PPIN and GRN, SYNCRIP, SQSTM1, GRAMD1A, FAM104A, ND2, TPGS2, ZNF652, RORA, and MALAT1 were the identified critical genes. In GRN, miR-155, miR17, miR146b, miR-200 family, and GATA2 were the factors that regulated critical genes. The MAPK, neurotrophin, and TNF signaling pathways, IL-17, and human cytomegalovirus infection, human papillomavirus infection, and shigellosis were identified as significant pathways involved in graft rejection.
Conclusion: The above-mentioned genes can be used as diagnostic and therapeutic serum markers of transplantation rejection in renal patients.  The newly predicted biomarkers and pathways require further studies.
Type of Study: Full Length/Original Article | Subject: Related Fields

References
1. Kim IW, Kim JH, Han N, Kim S, Kim YS, Oh JM: Gene expression profiles for predicting antibody‑mediated rejection allograft rejection: Analysis of GEO datasets. International journal of molecular medicine 2018, 42: 2303-2311. [DOI:10.3892/ijmm.2018.3798]
2. Han S, Zhao W, Wang C, Wang Y, Song R, Haller H, Jiang H, Chen J. Preliminary investigation of the biomarkers of acute renal transplant rejection using integrated proteomics studies, gene expression omnibus datasets, and RNA sequencing. Frontiers in medicine 2022, 9: 905464. [DOI:10.3389/fmed.2022.905464]
3. Lee JR, Muthukumar T, Dadhania D, Ding R, Sharma VK, Schwartz JE, Suthanthiran M: Urinary cell mRNA profiles predictive of human kidney allograft status. Immunological reviews 2014, 258: 218-240. [DOI:10.1111/imr.12159]
4. Han Q, Zhang X, Ren X, Hang Z, Yin Y, Wang Z, Chen H, Sun L, Tao J, Han Z, Tan R, Gu M, Ju X. Biological characteristics and predictive model of biopsy-proven acute rejection (BPAR) after kidney transplantation: evidences of multi-omics analysis. Frontiers in genetics 2022; 13:844709. [DOI:10.3389/fgene.2022.844709]
5. Hariharan S, Mcbride MA, Cherikh WS, Tolleris CB, Bresnahan BA, Johnson CP. Post-transplant renal function in the first year predicts long-term kidney transplant survival. Kidney international 2002, 62: 311-318. [DOI:10.1046/j.1523-1755.2002.00424.x]
6. Pallardó Mateu LM, Sancho Calabuig A, Capdevila Plaza L, Franco Esteve A. Acute rejection and late renal transplant failure: risk factors and prognosis. Nephrology dialysis transplantation 2004, 19: iii38-iii42. [DOI:10.1093/ndt/gfh1013]
7. Flechner SM, Kurian SM, Head SR, Sharp SM, Whisenant TC, Zhang J, Chismar JD, Horvath S, Mondala T, Gilmartin T. Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes. American Journal of Transplantation 2004, 4:1475-1489. [DOI:10.1111/j.1600-6143.2004.00526.x]
8. Sarwal M, Chua MS, Kambham N, Hsieh SC, Satterwhite T, Masek M, Salvatierra Jr O: Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. New England journal of medicine 2003, 349: 125-138. [DOI:10.1056/NEJMoa035588]
9. Sadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, Engelmann S, Vega-Warner V, Fang H, Halbritter J: A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. Journal of the American society of nephrology 2015, 26:1279-1289. [DOI:10.1681/ASN.2014050489]
10. Heathcote EJ: Diagnosis and management of cholestatic liver disease. Clinical gastroenterology and hepatology 2007; 5: 776-782. [DOI:10.1016/j.cgh.2007.05.008]
11. Kim EY, Ashlock D, Yoon SH. Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks. BMC bioinformatics 2019; 20:1-13. [DOI:10.1186/s12859-019-2897-z]
12. Dehghan Z, Mirmotalebisohi SA, Sameni M, Bazgiri M, Zali H: A motif-based network analysis of regulatory patterns in Doxorubicin effects on treating breast cancer, a systems biology study. Avicenna journal of medical biotechnology 2022; 14: 137. [DOI:10.18502/ajmb.v14i2.8889]
13. Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M: The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS computational biology 2007, 3: e59. [DOI:10.1371/journal.pcbi.0030059]
14. Ashtiani M, Salehzadeh Yazdi A, Razaghi Moghadam Z, Hennig H, Wolkenhauer O, Mirzaie M, Jafari M. A systematic survey of centrality measures for protein-protein interaction networks. BMC systems biology 2018; 12: 1-17. [DOI:10.1186/s12918-018-0598-2]
15. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC bioinformatics 2003; 4: 2. [DOI:10.1186/1471-2105-4-2]
16. Saberi F, Dehghan Z, Noori E, Taheri Z, Sameni M, Zali H. Identification of critical molecular factors and side effects underlying the response to thalicthuberine in prostate cancer: a systems biology approach. Avicenna journal of medical biotechnology 2023; 15: 53. [DOI:10.18502/ajmb.v15i1.11425]
17. Wingender E, Dietze P, Karas H, Knüppel R. TRANSFAC: a database on transcription factors and their DNA binding sites. Nucleic acids research 1996; 24: 238-241. [DOI:10.1093/nar/24.1.238]
18. Han H, Cho JW, Lee S, Yun A, Kim H, Bae D, Yang S, Kim CY, Lee M, Kim E, Lee S, Kang B, Jeong D, KimY, Jeon HN, Jung H, Nam S, Chung M, Kim JH, Lee I. TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic acids research 2018; 46(D1): D380-D386. [DOI:10.1093/nar/gkx1013]
19. Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, Chien CH, Wu MC, Huang CY, Tsou AP, Huang HD. miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic acids research 2011; 39(Database issue): D163-D169. [DOI:10.1093/nar/gkq1107]
20. Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. miRecords: an integrated resource for microRNA-target interactions. Nucleic acids research 2009; 37(Database issue): D105-D110. [DOI:10.1093/nar/gkn851]
21. Tong Z, Cui Q, Wang J, Zhou Y. TransmiR v2. 0: an updated transcription factor-microRNA regulation database. Nucleic acids research 2019; 47: D253-D258. [DOI:10.1093/nar/gky1023]
22. Cheng L, Wang P, Tian R, Wang S, Guo Q, Luo M, Zhou W, Liu G, Jiang H, Jiang Q. LncRNA2Target v2. 0: a comprehensive database for target genes of lncRNAs in human and mouse. Nucleic acids research 2019; 47: D140-D144. [DOI:10.1093/nar/gky1051]
23. López Giuliani AC, Hernández E, Tohmé MJ, Taisne C, Roldán JS, García Samartino C, Lussignol M, Codogno P, Colombo MI, Esclatine A, Delgui LR. Human cytomegalovirus inhibits autophagy of renal tubular epithelial cells and promotes cellular enlargement. Frontiers in cellular and infection microbiology 2020; 10: 474. [DOI:10.3389/fcimb.2020.00474]
24. Santangelo L, Giurato G, Cicchini C, Montaldo C, Mancone C, Tarallo R, Battistelli C, Alonzi T, Weisz A, Tripodi M. The RNA-binding protein SYNCRIP is a component of the hepatocyte exosomal machinery controlling microRNA sorting. Cell reports 2016; 17: 799-808. [DOI:10.1016/j.celrep.2016.09.031]
25. Whisenant TC, Peralta ER, Aarreberg LD, Gao NJ, Head SR, Ordoukhanian P, Williamson JR, Salomon DR. The activation-induced assembly of an RNA/protein interactome centered on the splicing factor U2AF2 regulates gene expression in human CD4 T cells. PloS one 2015; 10(12): e0144409. [DOI:10.1371/journal.pone.0144409]
26. Li L, Shen C, Nakamura E, Ando K, Signoretti S, Beroukhim R, Cowley GS, Lizotte P, Liberzon E, Bair S Root DE, Tamayo P, Tsherniak A, Cheng SC, Tabak B, Jacobsen A, Hakimi AA, Schultz N, Ciriello G, Sander C, Hsieh JJ,Kaelin WG. SQSTM1 is a pathogenic target of 5q copy number gains in kidney cancer. Cancer cell 2013; 24(6): 738-750. [DOI:10.1016/j.ccr.2013.10.025]
27. Zotti T, Scudiero I, Settembre P, Ferravante A, Mazzone P, D'Andrea L, Reale C, Vito P, Stilo R. TRAF6-mediated ubiquitination of NEMO requires p62/ sequestosome-1. Molecular immunology 2014; 58(1): 27-31. [DOI:10.1016/j.molimm.2013.10.015]
28. Liu Y, Fu S, Zhang Z, Wang S, Cheng X, Li Z, Ding Y, Sun T, Ma M. GRAMD1A is a biomarker of kidney renal clear cell carcinoma and is associated with immune infiltration in the tumour microenvironment. Disease markers 2022; 2022: 5939021. [DOI:10.1155/2022/5939021]
29. Laraia L, Friese A, Corkery DP, Konstantinidis G, Erwin N, Hofer W, Karatas H, Klewer L, Brockmeyer A, Metz M, Schölermann B, DwivediM, Li L, Rios-Munoz P, Köhn M, Winter R, Vetter IR, Ziegler S, Janning P, Wu YW, Waldmann H. The cholesterol transfer protein GRAMD1A regulates autophagosome biogenesis. Nature chemical biology 2019; 15(7): 710-720. [DOI:10.1038/s41589-019-0307-5]
30. Chen X, Wang L, Deng Y, Li X, Li G, Zhou J, Cheng D, Yang Y, Yang Q, Chen G, Wang G. Inhibition of autophagy prolongs recipient survival through promoting CD8+ T cell apoptosis in a rat liver transplantation model. Frontiers immunology 2019; 10: 1356. [DOI:10.3389/fimmu.2019.01356]
31. Günther OP, Shin H, Ng RT, McMaster WR, McManus BM, Keown PA, Tebbutt SJ, Lê Cao KA. Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study. Omics: a journal of integrative biology 2014; 18(11): 682-695. [DOI:10.1089/omi.2014.0062]
32. Chen YD, Ong SB, Ren J. Role of mitochondria-endoplasmic reticulum contacts in cardiovascular disorders. Oxidative medicine and cellular longevity 2021; Available at: https://www.hindawi.com/journals/ omcl/si/685876/.
33. Roedder S, Sigdel T, Hsieh SC, Cheeseman J, Metes D, Macedo C, Reed EF, Gritsch H, Zeevi A, Shapiro R, Kirk AD, Sarwal MM. Expression of mitochondrial-encoded genes in blood differentiate acute renal allograft rejection. Frontiers in medicine 2017; 4: 185. [DOI:10.3389/fmed.2017.00185]
34. Wang S, Feng X, Wang Y, Li Q, Li X. Dysregulation of tumour microenvironment driven by circ-TPGS2/miR-7/TRAF6/NF-κB axis facilitates breast cancer cell motility. Autoimmunity 2021; 54(5): 284-293. [DOI:10.1080/08916934.2021.1931843]
35. Kumar R, Cheney KM, McKirdy R, Neilsen PM, Schulz RB, Lee J, Cohen J, Booker GW, Callen DF. CBFA2T3-ZNF652 corepressor complex regulates transcription of the E-box gene HEB. Journal of biological chemistry 2008; 283(27): 19026-19038. [DOI:10.1074/jbc.M709136200]
36. Yin Q, McBride J, Fewell C, Lacey M, Wang X, Lin Z, Cameron J, Flemington EK. microRNA-155 is an Epstein-Barr virus-induced gene that modulates Epstein-Barr virus-regulated gene expression pathways. Journal of virology 2008; 82: 5295-5306. [DOI:10.1128/JVI.02380-07]
37. Le J, Durand CM, Agha I, Brennan DC. Epstein-Barr virus and renal transplantation. Transplantation reviews 2017; 31: 55-60. [DOI:10.1016/j.trre.2016.12.001]
38. Cai J, Jiao X, Fang Y, Yu X, Ding X. The orphan nuclear receptor RORα is a potential endogenous protector in renal ischemia/reperfusion injury. FASEB journal 2019; 33(4): 5704-57015. [DOI:10.1096/fj.201802248R]
39. Liu SQ, Jiang S, Li C, Zhang B, Li QJ. miR-17-92 cluster targets phosphatase and tensin homology and Ikaros Family Zinc Finger 4 to promote TH17-mediated inflammation. Journal of biological chemistry 2014; 289(18): 12446-12456. [DOI:10.1074/jbc.M114.550723]
40. Mycko MP, Cichalewska M, Cwiklinska H, Selmaj KW. miR-155-3p drives the development of autoimmune demyelination by regulation of heat shock protein 40. Journal of neuroscience 2015; 35: 16504-16515. [DOI:10.1523/JNEUROSCI.2830-15.2015]
41. Chung BH, Yang CW, Cho ML. Clinical significance of Th17 cells in kidney transplantation. The korean journal of internal medicine 2018; 33(5): 860-866. [DOI:10.3904/kjim.2018.095]
42. Yoshimoto R, Mayeda A, Yoshida M, Nakagawa S. MALAT1 long non-coding RNA in cancer. Biochimica et biophysica acta (BBA)-gene regulatory mechanisms 2016; 1859(1): 192-199. [DOI:10.1016/j.bbagrm.2015.09.012]
43. Paterson MR, Geurts AM, Kriegel AJ. miR-146b-5p has a sex-specific role in renal and cardiac pathology in a rat model of chronic kidney disease. Kidney international 2019; 96(6): 1332-1345. [DOI:10.1016/j.kint.2019.07.017]
44. Peng Y, Fang X, Yao H, Zhang Y, Shi J. miR-146b-5p regulates the expression of long noncoding RNA MALAT1 and its effect on the invasion and proliferation of papillary thyroid cancer. Cancer biotherapy and radiopharmaceuticals 2021; 36(5): 433-440. [DOI:10.1089/cbr.2019.3322]
45. Groeneweg KE, Au YW, Duijs JM, Florijn BW, van Kooten C, de Fijter JW, Reinders ME, van Zonneveld AJ, Bijkerk R. Diabetic nephropathy alters circulating long noncoding RNA levels that normalize following simultaneous pancreas-kidney transplantation. American journal of transplantation 2020; 20(12): 3451-3461. [DOI:10.1111/ajt.15961]
46. Xiong M, Jiang L, Zhou Y, Qiu W, Fang L, Tan R, Wen P, Yang J. The miR-200 family regulates TGF-β1-induced renal tubular epithelial to mesenchymal transition through Smad pathway by targeting ZEB1 and ZEB2 expression. American journal of physiology-renal physiology 2012; 302(3): F369-F379. [DOI:10.1152/ajprenal.00268.2011]
47. Zhuo M, Yuan C, Han T, Cui J, Jiao F, Wang L. A novel feedback loop between high MALAT-1 and low miR-200c-3p promotes cell migration and invasion in pancreatic ductal adenocarcinoma and is predictive of poor prognosis. BMC cancer 2018; 18(1): 1032. [DOI:10.1186/s12885-018-4954-9]
48. Huang D, Chen D, Hu T, Liang H. GATA2 promotes oxidative stress to aggravate renal ischemia-reperfusion injury by up-regulating Redd1. Molecular immunology 2023; 153: 75-84. [DOI:10.1016/j.molimm.2022.09.012]
49. Cuarental L, Sucunza Sáenz D, Valiño Rivas L, Fernandez Fernandez B, Sanz AB, Ortiz A, Vaquero JJ, Sanchez-Niño MD. MAP3K kinases and kidney injury. Nefrología (Engl ed.) 2019; 39(6): 568-580. [DOI:10.1016/j.nefro.2019.03.004]
50. Vafadari R, Hesselink DA, Cadogan MM, Weimar W, Baan CC. Inhibitory effect of tacrolimus on p38 mitogen-activated protein kinase signaling in kidney transplant recipients measured by whole-blood phosphospecific flow cytometry. Transplantation 2012; 93(12): 1245-1251. [DOI:10.1097/TP.0b013e318250fc62]
51. Ramanan P, Razonable RR. Cytomegalovirus infections in solid organ transplantation: a review. Infection & chemotherapy 2013; 45(3): 260-271. [DOI:10.3947/ic.2013.45.3.260]
52. Paolo MD, Papi L, Gori F, Turillazzi E. Natural Products in Neurodegenerative Diseases: A Great Promise but an Ethical Challenge. International journal of medical sciences 2019; 20(20): 5170. [DOI:10.3390/ijms20205170]
53. Molnar A, Szkibinszkij E, Lenart L, Hosszu A, Kovacs I, Wagner L, Rimaszombati F, Novozanszki S, Szabo A, Fekete A. P1669 prognostic importance of brain -derived neurothrophic factor (BDNF) in renal transplantation. Nephrology dialysis transplantation 2020; 35(Supplement 3): gfaa142. P1669. [DOI:10.1093/ndt/gfaa142.P1669]
54. Lu R, Herrera BB, Eshleman HD, Fu Y, Bloom A, Li Z, Sacks DB, Goldberg MB. Shigella effector OspB activates mTORC1 in a manner that depends on IQGAP1 and promotes cell proliferation. PLoS pathogens 2015; 11(10): e1005200. [DOI:10.1371/journal.ppat.1005200]
55. Appannanavar SB, Goyal K, Garg R, Ray P, Rathi M, Taneja N. Shigellemia in a post renal transplant patient: a case report and literature review. The journal of infection in developing countries 2014; 8(2):237-239. [DOI:10.3855/jidc.3000]
56. Nailescu C, Nelson RD, Verghese PS, Twombley KE, Chishti AS, Mills M, Mahan JD, Slaven JE, Shew ML. Human papillomavirus vaccination in male and female adolescents before and after kidney transplantation: a pediatric nephrology research consortium study. Frontiers in pediatrics 2020; 8: 46. [DOI:10.3389/fped.2020.00046]
57. Larsen HK., Thomsen LT, Hædersdal M, Lok TT, Hansen JM, Sorensen SS. Risk of anogenital warts in renal transplant recipients compared with immuno-competent controls: a cross-sectional clinical study. Acta dermato-venereologica 2021; 101(7): 137. [DOI:10.2340/00015555-3858]
58. Chin-Hong PV: Human papillomavirus in kidney transplant recipients. Seminars in nephrology 2016; 36(5): 397-404. [DOI:10.1016/j.semnephrol.2016.05.016]
59. .Basile DP, Ullah MM, Collet JA, Mehrotra P. T helper 17 cells in the pathophysiology of acute and chronic kidney disease. Kidney research and clinical practice 2021; 40(1): 12-28. [DOI:10.23876/j.krcp.20.185]
60. Xu S, Cao X. Interleukin-17 and its expanding biological functions. Cellular & molecular immunology 2010; 7: 164-174. [DOI:10.1038/cmi.2010.21]
61. Ernandez T, Mayadas TN. The changing landscape of renal inflammation. Trends in molecular medicine 2016; 22: 151-163. [DOI:10.1016/j.molmed.2015.12.002]

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.