Identification of immune related genes in ankylosing spondylitis based on machine learning

ZHOU Ruozhou; HU Xin; FAN Yu; FANG Zuozhong; TIAN Jian; DENG Guobing

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Journal of Hunan Normal University(Medical Science) ›› 2023, Vol. 20 ›› Issue (2) : 54-62.

Clinical Medicine

Identification of immune related genes in ankylosing spondylitis based on machine learning

ZHOU Ruozhou¹, HU Xin¹, FAN Yu¹, FANG Zuozhong¹, TIAN Jian², DENG Guobing¹

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Abstract

Objective To explore the diagnostic value and molecular mechanism of immune related characteristic genes in ankylosing spondylitis (AS). Methods Download the GSE73756 and GSE25101 datasets from the Gene Expression Omnibus (GEO) database. Combined the weighted gene overexpression network (WGCNA) and the Least absolute shrinkage and selection operator, LASSO) and the Support Vector Machine-recursive feature elimination (SVM-RFE) to screen characteristic genes and evaluate their diagnostic value in AS. Bioinformatics analysis such as functional and pathway enrichment analysis was performed. Results Finally, a total of 5 key immune related genes were identified: CD81, IL2RB, CSF3R, IL8, and CCL3L3. The diagnostic model constructed by the combination of five genes has high diagnostic value in both the training set and the test set. Conclusion CD81, IL2RB, CSF3R, IL8 and CCL3L3 may be the diagnostic biomarkers and potential therapeutic targets of AS.

Key words

ankylosing spondylitis / immune related genes / bioinformatics / machine learning / support vector machine

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ZHOU Ruozhou, HU Xin, FAN Yu, FANG Zuozhong, TIAN Jian, DENG Guobing. Identification of immune related genes in ankylosing spondylitis based on machine learning[J]. Journal of Hunan Normal University(Medical Science). 2023, 20(2): 54-62

References

[1] Taurog JD, Chhabra A, Colbert RA.Ankylosing Spondylitis and Axial Spondyloarthritis[J]. N Engl J Med, 2016, 375(13): 1303.
[2] Smith JA.Update on ankylosing spondylitis: current concepts in pathogenesis[J]. Curr Allergy Asthma Rep, 2015, 15(1): 489.
[3] Wenker KJ, Quint JM.Ankylosing Spondylitis[M]. Treasure Island (FL): StatPearls, 2022.
[4] Ranganathan V, Gracey E, Brown MA, et al.Pathogenesis of ankylosing spondylitis - recent advances and future directions[J]. Nat Rev Rheumatol, 2017, 13(6): 359-367.
[5] Ermoza K, Glatigny S, Jah N, et al.Tolerogenic XCR1(+) dendritic cell population is dysregulated in HLA-B27 transgenic rat model of spondyloarthritis[J]. Arthritis Res Ther, 2019, 21(1): 46.
[6] Min HK, Choi J, Lee SY, et al.Protein inhibitor of activated STAT3 reduces peripheral arthritis and gut inflammation and regulates the Th17/Treg cell imbalance via STAT3 signaling in a mouse model of spondyloarthritis[J]. J Transl Med, 2019, 17(1): 18.
[7] Giulietti M, Occhipinti G, Principato G, et al.Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysis[J]. Cell Oncol (Dordr), 2017, 40(2): 181-192.
[8] Erickson B J.Basic Artificial Intelligence Techniques: Machine Learning and Deep Learning[J]. Radiol Clin North Am, 2021, 59(6): 933-940.
[9] Langfelder P, Horvath S.WGCNA: an R package for weighted correlation network analysis[J]. BMC Bioinformatics, 2008, 9: 559.
[10] Tibshirani R.The lasso method for variable selection in the Cox model[J]. Stat Med, 1997, 16(4): 385-395.
[11] Matsuo K, Purushotham S, Jiang B, et al.Survival outcome prediction in cervical cancer: Cox models vs deep-learning model[J]. Am J Obstet Gynecol, 2019, 220(4): 381 e1-e14.
[12] Chen B, Khodadoust MS, Liu CL, et al.Profiling Tumor Infiltrating Immune Cells with CIBERSORT[J]. Methods Mol Biol, 2018, 1711: 243-259.
[13] Baysal O, Durmus B, Ersoy Y, et al.Relationship between psychological status and disease activity and quality of life in ankylosing spondylitis[J]. Rheumatol Int, 2011, 31(6): 795-800.
[14] Raychaudhuri SP, Deodhar A. The classification and diagnostic criteria of ankylosing spondylitis [J]. J Autoimmun, 2014, 48-49: 128-133.
[15] Poddubnyy D. Classification vs diagnostic criteria: the challenge of diagnosing axial spondyloarthritis [J]. Rheumatology (Oxford), 2020, 59(Suppl4): iv6-iv17.
[16] Ibn Yacoub Y, Amine B, Laatiris A, et al.Relationship between diagnosis delay and disease features in Moroccan patients with ankylosing spondylitis[J]. Rheumatol Int, 2012, 32(2): 357-360.
[17] Ritchlin C, Adamopoulos IE.Axial spondyloarthritis: new advances in diagnosis and management[J]. BMJ, 2021, 372: m4447.
[18] Sieper J, Poddubnyy D.Axial spondyloarthritis[J]. Lancet, 2017, 390(10089): 73-84.
[19] Danve A, O'dell J. The ongoing quest for biomarkers in Ankylosing Spondylitis[J]. Int J Rheum Dis, 2015, 18(8): 826-834.
[20] Aviña-Zubieta JA, Chan J, De Vera A M, et al. Risk of venous thromboembolism in ankylosing spondylitis: a general population-based study[J]. Ann Rheum Dis, 2019, 78(4): 480-485.
[21] Chen W, Li W, Zhang Z, et al.Lipocalin-2 Exacerbates Lupus Nephritis by Promoting Th1 Cell Differentiation[J]. J Am Soc Nephrol, 2020, 31(10): 2263-2277.
[22] Voruganti A, Bowness P.New developments in our understanding of ankylosing spondylitis pathogenesis[J]. Immunology, 2020, 161(2): 94-102.
[23] Ramakrishnaiah V, Thumann C, Fofana I, et al.Exosome-mediated transmission of hepatitis C virus between human hepatoma Huh7.5 cells[J]. Proc Natl Acad Sci U S A, 2013, 110(32): 13109-13113.
[24] Hosokawa K, Ishimaru H, Watanabe T, et al.Pax5 mediates the transcriptional activation of the CD81 gene[J]. Sci Rep, 2021, 11(1): 22919.
[25] Fujii Y, Arai Y, Nakagawa S, et al.CD81 inhibition with the cytoplasmic RNA vector producing anti-CD81 antibodies suppresses arthritis in a rat CIA model[J]. Biochem Biophys Res Commun, 2022, 604: 22-29.
[26] Waldmann TA.The shared and contrasting roles of IL2 and IL15 in the life and death of normal and neoplastic lymphocytes: implications for cancer therapy[J]. Cancer Immunol Res, 2015, 3(3): 219-227.
[27] Ring AM, Lin JX, Feng D, et al.Mechanistic and structural insight into the functional dichotomy between IL-2 and IL-15[J]. Nat Immunol, 2012, 13(12): 1187-1195.
[28] Al-Mayouf SM, Alreefi HA, Alsinan TA, et al.Lupus manifestations in children with primary immunodeficiency diseases: Comprehensive phenotypic and genetic features and outcome[J]. Mod Rheumatol, 2021, 31(6): 1171-1178.
[29] Maxson JE, Tyner JW.Genomics of chronic neutrophilic leukemia[J]. Blood, 2017, 129(6): 715-722.
[30] Szuber N, Elliott M, Tefferi A.Chronic neutrophilic leukemia: 2020 update on diagnosis, molecular genetics, prognosis, and management[J]. Am J Hematol, 2020, 95(2): 212-224.
[31] Bihari C, Baweja S, Shasthry SM, et al.CEACAM-1 Induced CSF3-receptor Downregulation in Bone Marrow Associated With Refractory Neutropenia in Advanced Cirrhosis[J]. J Clin Transl Hepatol, 2022, 10(1): 53-62.
[32] Xiong X, Liao X, Qiu S, et al.CXCL8 in Tumor Biology and Its Implications for Clinical Translation[J]. Front Mol Biosci, 2022, 9: 723846.
[33] Horn LA, Fousek K, Palena C.Tumor Plasticity and Resistance to Immunotherapy[J]. Trends Cancer, 2020, 6(5): 432-441.
[34] Ha H, Debnath B, Neamati N.Role of the CXCL8-CXCR1/2 Axis in Cancer and Inflammatory Diseases[J]. Theranostics, 2017, 7(6): 1543-1588.
[35] Kim YH, Lee EE, Sim HW, et al. CCL3L3-null status is associated with susceptibility to systemic lupus erythematosus [J]. Sci Rep, 2021, 11(1): 19172.Volorpercing eu feugiatie ectem aliquat.