Transcriptome analysis for identifying hub genes and prognosis biomarkers of mRNA/lncRNA in septic shock

Abstract

Background: Septic shock is a life-threatening disease with high mortality rates, and the relevant hub genes and biomarkers are poorly understood. We aimed to identify hub genes and prognostic biomarkers of mRNAs/lncRNAs in septic shock to rapidly and accurately diagnose infection, identify patients at a high risk of developing septic shock, and predict prognosis.

Methods: Gene expression profiles of 279 patients with septic shock and 100 healthy controls were analyzed using bioinformatics methods. We screened for differentially expressed genes (DEGs), identified hub genes, and investigated the correlations between mRNA/lncRNA expression and disease severity/prognosis. Protein level validation was performed using blood proteomic data from an independent cohort study.

Results: The protein-protein interaction network constructed using upregulated DEGs contained 102 nodes and 222 edges, with LTF, MMP8, MMP9, CEACAM8, CTSG, LCN2, and PRTN3 identified as hub genes. There was a possible association between LCN2 mRNA upregulation and increased severity of septic shock (odds ratio: 1.518; 95% confidence interval: 0.999-2.305; P = 0.050), approaching statistical significance, and BCL2A1 mRNA upregulation correlated with higher mortality risk (odds ratio: 1.178; 95% confidence interval: 1.035-1.341; P = 0.013). No significant prognostic correlation was observed for lncRNAs. The validation cohort confirmed significant upregulation of MMP9, CTSG, LCN2, LTF, and MMP8 proteins in patients with septic shock, with MMP9, LCN2, CTSG, and LTF exhibiting strong diagnostic performance (area under the curve >0.8).

Conclusion: Seven hub genes related to septic shock were identified, including MMP9, LCN2, CTSG, and LTF, which could potentially function as candidate biotargets and biomarkers for the diagnosis and prognostic prediction of septic shock, though further validation is needed. Notably, LCN2 showed a trend toward association with disease severity, while BCL2A1 correlated with mortality risk.

Keywords

Biomarker / lncRNA / mRNA / Septic shock / Transcriptome

Conflict of interest statement

The authors declare no conflict of interest.

Author contributions

Gong C participated in concept, design, data acquisition, data analysis, manuscript preparation, and manuscript editing. Zhang W participated in design, literature search, data acquisition, data analysis, statistical analysis, and manuscript preparation. Lu X, Yu S, Ge Z, and Qin M participated in data analysis, statistical analysis, and manuscript editing. Zhu H participated in manuscript review. Li Y participated in manuscript editing and review. Gong C and Zhang W contributed equally to the study.

Funding

This work was supported by theNationalHigh Level Hospital Clinical Research Funding [grant number 2022-PUMCH-B-109] and the Chinese Academy ofMedical Science Innovation Fund for Medical Sciences (CIFMS) [grant number 2021-I2M-1-020].

Ethical approval of studies and informed consent

The study followed the principles of the Declaration of Helsinki as revised in 2013. The use of public databases does not require ethical approval or informed consent. For our own cohort, it was approved by the ethics committee of Peking Union Medical College Hospital (K2424) on April 10, 2023, and written informed consent was obtained from all participants.

Acknowledgments

We would like to extend our sincere gratitude to Professor Xiaomin Hu and Ms. Siqi Sun (both from Peking Union Medical College Hospital) for their invaluable support and assistance with proteomic data analysis. We would like to thank the funds and all original authors who provided publicly available data.

References

[1] Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016; 315(8):801-810. doi:10.1001/jama.2016.0287

[2] Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021; 47(11):1181-1247. doi:10.1007/s00134-021-06506-y

[3] Salomão R, Ferreira BL, Salomão MC, Santos SS, Azevedo LCP, Brunialti MKC. Sepsis: evolving concepts and challenges. Braz J Med Biol Res. 2019; 52(4):e8595. doi:10.1590/1414-431x20198595

[4] Fleischmann-Struzek C, Mellhammar L, Rose N, et al. Incidence and mortality of hospital- and ICU-treated sepsis: results from an updated and expanded systematic review and meta-analysis. Intensive Care Med. 2020; 46(8):1552-1562. doi:10.1007/s00134-020-06151-x

[5] Huang M, Cai S, Su J. The pathogenesis of sepsis and potential therapeutic targets. Int J Mol Sci. 2019; 20(21):5376. doi:10.3390/ijms20215376

[6] Haak BW, Prescott HC, Wiersinga WJ. Therapeutic potential of the gut microbiota in the prevention and treatment of sepsis. Front Immunol. 2018; 9:2042. doi:10.3389/fimmu.2018.02042

[7] Zhou J, Dong S, Wang P, Su X, Cheng L. Identification of nine mRNA signatures for sepsis using random forest. Comput Math Methods Med. 2022; 2022:5650024. doi:10.1155/2022/5650024

[8] Bourcier S, Hindlet P, Guidet B, Dechartres A. Reporting of organ support outcomes in septic shock randomized controlled trials: a methodologic review-the sepsis organ support study. Crit Care Med. 2019; 47(7):984-992. doi:10.1097/ccm.0000000000003746

[9] Ditty JL, Kvaal CA, Goodner B, et al. Incorporating genomics and bioinformatics across the life sciences curriculum. PLoS Biol. 2010; 8(8):e1000448. doi:10.1371/journal.pbio.1000448

[10] Du W, Sun J, Gu J, Zhang S, Zhang T. Bioinformatics analysis of LINC00426 expression in lung cancer and its correlation with patients' prognosis. Thorac Cancer. 2020; 11(1):150-155. doi:10.1111/1759-7714.13228

[11] Zhang G, Tang X, Liang L, et al. DNA and RNA sequencing identified a novel oncogene VPS35 in liver hepatocellular carcinoma. Oncogene. 2020; 39(16):3229-3244. doi:10.1038/s41388-020-1215-6

[12] Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res. 2013;41(Database issue):D991-D995. doi:10.1093/nar/gks1193

[13] Chen T, Liu YX, Huang L. ImageGP: an easy-to-use data visualization web server for scientific researchers. Imeta. 2022; 1(1):e5. doi:10.1002/imt2.5

[14] Gene Ontology Consortium. The Gene Ontology resource: enriching a GOld mine. Nucleic Acids Res. 2021; 49(D1):D325-D334. doi:10.1093/nar/gkaa1113

[15] Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach for understanding genome variations in KEGG. Nucleic Acids Res. 2019; 47(D1):D590-D595. doi:10.1093/nar/gky962

[16] Szklarczyk D, Gable AL, Nastou KC, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021; 49(D1):D605-D612. doi:10.1093/nar/gkaa1074

[17] Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13(11):2498-2504. doi:10.1101/gr.1239303

[18] 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

[19] Scardoni G, Petterlini M, Laudanna C. Analyzing biological network parameters with CentiScaPe. Bioinformatics. 2009; 25(21):2857-2859. doi:10.1093/bioinformatics/btp517

[20] Assenov Y, Ramírez F, Schelhorn SE, Lengauer T, Albrecht M. Computing topological parameters of biological networks. Bioinformatics. 2008; 24(2):282-284. doi:10.1093/bioinformatics/btm554

[21] Reinhart K, Daniels R, Kissoon N, Machado FR, Schachter RD, Finfer S. Recognizing sepsis as a global health priority - a WHO resolution. N Engl J Med. 2017; 377(5):414-417. doi:10.1056/NEJMp1707170

[22] Adhikari NK, Fowler RA, Bhagwanjee S, Rubenfeld GD. Critical care and the global burden of critical illness in adults. Lancet. 2010; 376(9749):1339-1346. doi:10.1016/s0140-6736(10)60446-1

[23] Cecconi M, Evans L, Levy M, Rhodes A. Sepsis and septic shock. Lancet. 2018; 392(10141):75-87. doi:10.1016/s0140-6736(18)30696-2

[24] Kalil AC, Opal SM. Sepsis in the severely immunocompromised patient. Curr Infect Dis Rep. 2015; 17(6):487. doi:10.1007/s11908-015-0487-4

[25] Li Y, Zhang H, Shao J, et al. Bioinformatics analysis for identifying pertinent pathways and genes in sepsis. Comput Math Methods Med. 2021; 2021:2085173. doi:10.1155/2021/2085173

[26] Tabone O, Mommert M, Jourdan C, et al. Endogenous retroviruses transcriptional modulation after severe infection, trauma and burn. Front Immunol. 2018; 9:3091. doi:10.3389/fimmu.2018.03091

[27] Venet F, Schilling J, Cazalis MA, et al. Modulation of LILRB2 protein and mRNA expressions in septic shock patients and after ex vivo lipopolysaccharide stimulation. Hum Immunol. 2017; 78(5-6):441-450. doi:10.1016/j.humimm.2017.03.010

[28] Alcalay M, Orleth A, Sebastiani C, et al. Common themes in the pathogenesis of acute myeloid leukemia. Oncogene. 2001; 20(40):5680-5694. doi:10.1038/sj.onc.1204642

[29] Scandura JM, Boccuni P, Cammenga J, Nimer SD. Transcription factor fusions in acute leukemia: variations on a theme. Oncogene. 2002; 21(21):3422-3444. doi:10.1038/sj.onc.1205315

[30] Roumier C, Fenaux P, Lafage M, Imbert M, Eclache V, Preudhomme C. New mechanisms of AML 1 gene alteration in hematological malignancies. Leukemia. 2003; 17(1):9-16. doi:10.1038/sj.leu.2402766

[31] Koschmieder S, Halmos B, Levantini E, Tenen DG. Dysregulation of the C/EBPalpha differentiation pathway in human cancer. J Clin Oncol. 2009; 27(4):619-628. doi:10.1200/jco.2008.17.9812

[32] Martínez-Paz P, Aragón-Camino M, Gómez-Sánchez E, et al. Distinguishing septic shock from non-septic shock in postsurgical patients using gene expression. J Infect. 2021; 83(2):147-155. doi:10.1016/j.jinf.2021.05.039

[33] Xu Z, Jiang M, Bai X, Ding L, Dong P, Jiang M. Identification and verification of potential core genes in pediatric septic shock. Comb Chem High Throughput Screen. 2022; 25(13):2228-2239. doi:10.2174/1386207325666220310110902

[34] DiStefano MT, Goehringer S, Babb L, et al. The Gene Curation Coalition: a global effort to harmonize gene-disease evidence resources. Genet Med. 2022; 24(8):1732-1742. doi:10.1016/j.gim.2022.04.017

[35] Gaudet P, Livstone MS, Lewis SE, Thomas PD. Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium. Brief Bioinform. 2011; 12(5):449-462. doi:10.1093/bib/bbr042

[36] Lupetti A, Paulusma-Annema A, Welling MM, Senesi S, van Dissel JT, Nibbering PH. Candidacidal activities of human lactoferrin peptides derived from the N terminus. Antimicrob Agents Chemother. 2000; 44(12):3257-3263. doi:10.1128/aac.44.12.3257-3263.2000

[37] Chapple DS, Hussain R, Joannou CL, et al. Structure and association of human lactoferrin peptides with Escherichia coli lipopolysaccharide. Antimicrob Agents Chemother. 2004; 48(6):2190-2198. doi:10.1128/aac.48.6.2190-2198.2004

[38] Nozaki A, Ikeda M, Naganuma A, et al. Identification of a lactoferrin-derived peptide possessing binding activity to hepatitis C virus E 2 envelope protein. J Biol Chem. 2003; 278(12):10162-10173. doi:10.1074/jbc.M207879200

[39] National Center for Biotechnology Information (2022). PubChem pathway summary for pathway R-HSA-5663205, infectious disease, source: reactome. Assessed May 31, 2022. https://pubchem.ncbi.nlm.nih.gov/pathway/Reactome:R-HSA-5663205

[40] Lee EJ, Han JE, Woo MS, et al. Matrix metalloproteinase-8 plays a pivotal role in neuroinflammation by modulating TNF-α activation. J Immunol. 2014; 193(5):2384-2393. doi:10.4049/jimmunol.1303240

[41] Wong HR, Salisbury S, Xiao Q, et al. The pediatric sepsis biomarker risk model. Crit Care. 2012; 16(5):R174. doi:10.1186/cc11652

[42] Wong HR, Cvijanovich NZ, Anas N, et al. Improved risk stratification in pediatric septic shock using both protein and mRNA biomarkers. PERSEVERE-XP. Am J Respir Crit Care Med. 2017; 196(4):494-501. doi:10.1164/rccm.201701-0066OC

[43] Jog NR, Rane MJ, Lominadze G, Luerman GC, Ward RA, McLeish KR. The actin cytoskeleton regulates exocytosis of all neutrophil granule subsets. Am J Physiol Cell Physiol. 2007; 292(5):C1690-C1700. doi:10.1152/ajpcell.00384.2006

[44] Berling B, Kolbinger F, Grunert F, et al. Cloning of a carcinoembryonic antigen gene family member expressed in leukocytes of chronic myeloid leukemia patients and bone marrow. Cancer Res. 1990; 50(20):6534-6539.

[45] Ribon M, Mussard J, Semerano L, Singer BB, Decker P. Extracellular chromatin triggers release of soluble CEACAM8 upon activation of neutrophils. Front Immunol. 2019; 10:1346. doi:10.3389/fimmu.2019.01346

[46] Yu H, Liu Y, Wang M, et al. Myeloperoxidase instigates proinflammatory responses in a cecal ligation and puncture rat model of sepsis. Am J Physiol Heart Circ Physiol. 2020; 319(3):H705-H721. doi:10.1152/ajpheart.00440.2020

[47] Demaret J, Venet F, Friggeri A, et al. Marked alterations of neutrophil functions during sepsis-induced immunosuppression. J Leukoc Biol. 2015; 98(6):1081-1090. doi:10.1189/jlb.4A0415-168RR

[48] Shields-Cutler RR, Crowley JR, Miller CD, Stapleton AE, Cui W, Henderson JP. Human metabolome-derived cofactors are required for the antibacterial activity of siderocalin in urine. J Biol Chem. 2016; 291(50):25901-25910. doi:10.1074/jbc.M116.759183

[49] Wu M, Mi B, Liu L, et al. Genetic polymorphisms, biomarkers and signaling pathways associated with septic shock: from diagnosis to therapeutic targets. Burns Trauma. 2024;12:tkae006. doi:10.1093/burnst/tkae006

[50] Zhang Y, Li B, Ning B. Evaluating IL-6 and IL-10 as rapid diagnostic tools for gram-negative bacteria and as disease severity predictors in pediatric sepsis patients in the intensive care unit. Front Immuno. 2022; 13:1043968. doi:10.3389/fimmu.2022.1043968

[51] Tang BM, McLean AS, Dawes IW, Huang SJ, Cowley MJ, Lin RC. Gene-expression profiling of gram-positive and gram-negative sepsis in critically ill patients. Crit Care Med. 2008; 36(4):1125-1128. doi:10.1097/CCM.0b013e3181692c0b