[1]朱思哲,叶成林.基于生物信息学分析构建免疫相关基因脓毒症预后模型[J].医学信息,2022,35(15):1-6，13.[doi:10.3969/j.issn.1006-1959.2022.15.001]
　ZHU Si-zhe,YE Cheng-lin.Identification of Immune-related Gene Prognostic Model for Sepsis Based on Bioinformatics Analysis[J].Journal of Medical Information,2022,35(15):1-6，13.[doi:10.3969/j.issn.1006-1959.2022.15.001]
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基于生物信息学分析构建免疫相关基因脓毒症预后模型()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年15期
页码:
1-6，13
栏目:
生物信息学
出版日期:
2022-08-01

文章信息/Info

Title:
Identification of Immune-related Gene Prognostic Model for Sepsis Based on Bioinformatics Analysis
文章编号:
1006-1959（2022）15-0001-07
作者:
朱思哲; 叶成林
（1.华中科技大学同济医学院附属同济医院临床免疫研究室，湖北 武汉 430030；2.武汉大学人民医院病理科，湖北 武汉 430060）
Author(s):
ZHU Si-zhe; YE Cheng-lin
(1.Department of Clinical Immunology,Tongji Hospital,Tongji Medical College,Huazhong University of Sciences and Technology,Wuhan 430030,Hubei,China;2.Department of Pathology,Renmin Hospital of Wuhan University,Wuhan 430060, Hubei,China)
关键词:
脓毒症; 免疫细胞浸润; 预后模型
Keywords:
Sepsis; Immune cell infiltration; Prognostic mode
分类号:
R631
DOI:
10.3969/j.issn.1006-1959.2022.15.001
文献标志码:
A
摘要:
目的 基于生物信息学分析构建免疫相关基因脓毒症预后模型。方法 从GEO数据库下载脓毒症相关的基因表达矩阵，基于CIBERSORTx数据库分析脓毒症组和正常组的免疫细胞浸润差异，通过R包limma进行差异分析；对差异基因和免疫相关基因取交集，并进行生物功能富集分析；通过LASSO回归、多因素COX回归筛选免疫相关独立预后基因，并构建脓毒症预后风险模型，通过训练集和验证集利用预后相关基因构建脓毒症诊断模型。结果 脓毒症组与正常组间存在12种表达差异的免疫细胞，共发现245个差异表达的免疫相关基因；生物功能富集分析显示，245个基因主要富集在免疫和感染相关信号通路；LASSO回归和多因素COX回归显示，DEFA4、CAMP、CX3CR1和PRKCA可作为脓毒症的独立预后因素，其中DEFA4和CAMP在脓毒症组高表达，CX3CR1和PRKCA在正常组中高表达（P＜0.05）；基于DEFA4、CAMP、CX3CR1和PRKCA成功构建脓毒症风险预后模型，DEFA4、CAMP、CX3CR1在训练集和验证集中的ROC曲线下面积（AUC）均＞0.750，PRKCA在训练集中的AUC为0.893，在验证集中为0.673。结论 基于DEFA4、CAMP、CX3CR1和PRKCA构建的风险预后模型具有良好的预测能力，同时DEFA4、CAMP、CX3CR1和PRKCA也具备脓毒症诊断能力，可能成为脓毒症新的生物标志物和靶点。
Abstract:
Objective To construct a prognostic model for immune-related genes in sepsis based on bioinformatics analysis.Methods The sepsis-related gene expression matrix was downloaded from GEO database. The difference of immune cell infiltration between sepsis group and normal group was analyzed based on CIBERSORTx database, and the difference was analyzed by R package limma. The intersection of differential genes and immune-related genes was collected, and the biological function enrichment analysis was performed. The immune-related independent prognostic genes were screened by LASSO regression and multivariate COX regression, and the prognostic risk model of sepsis was constructed. The prognostic-related genes were used to construct the diagnostic model of sepsis through training set and validation set.Results There were 12 immune cells with different expression between sepsis group and normal group, and 245 immune-related genes with different expression were found. Biofunctional enrichment analysis showed that 245 genes were mainly enriched in immune and infection-related signaling pathways. LASSO regression and multivariate COX regression showed that DEFA4, CAMP, CX3CR1 and PRKCA were independent prognostic factors for sepsis, while DEFA4 and CAMP were highly expressed in sepsis group, CX3CR1 and PRKCA were highly expressed in normal group (P<0.05). The risk prognosis model of sepsis was successfully constructed based on DEFA4, CAMP, CX3CR1 and PRKCA. The area under the ROC curve ( AUC ) of DEFA4, CAMP and CX3CR1 in the training set and the validation set was >0.750. The AUC of PRKCA in the training set was 0.893 and 0.673 in the validation set. Conclusion The risk prognosis model based on DEFA4, CAMP, CX3CR1 and PRKCA has good predictive ability. At the same time, DEFA4, CAMP, CX3CR1 and PRKCA also have the diagnostic ability of sepsis, which may become new biomarkers and targets for sepsis.

参考文献/References:

[1]Fernando SM,Rochwerg B,Seely AJE.Clinical implications of the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)[J].CMAJ,2018,190(36):E1058-E1059.[2]Rudd KE,Johnson SC,Agesa KM,et al.Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study[J].Lancet,2020,395(10219):200-211.[3]Venkatesh B,Finfer S,Cohen J,et al.Adjunctive Glucocorticoid Therapy in Patients with Septic Shock[J].N Engl J Med,2018,378(9):797-808.[4]Barichello T,Sayana P,Giridharan VV,et al.Long-Term Cognitive Outcomes After Sepsis: a Translational Systematic Review[J].Mol Neurobiol,2019,56(1):186-251.[5]Hamidzadeh K,Christensen SM,Dalby E,et al.Macrophages and the Recovery from Acute and Chronic Inflammation[J].Annu Rev Physiol,2017,79:567-592.[6]Cao C,Yu M,Chai Y.Pathological alteration and therapeutic implications of sepsis-induced immune cell apoptosis[J].Cell Death Dis,2019,10(10):782.[7]Jensen IJ,Li X,Mcgonagill PW,et al.Sepsis leads to lasting changes in phenotype and function of memory CD8 T cells[J].Elife,2021,10:e70989.[8]Gyawali B,Ramakrishna K,Dhamoon AS.Sepsis: The evolution in definition, pathophysiology, and management[J].SAGE Open Med,2019,7:2050312119835043.[9]Cecconi M,Evans L,Levy M,et al.Sepsis and septic shock[J].Lancet,2018,392(10141):75-87.[10]Brady J,Horie S,Laffey JG.Role of the adaptive immune response in sepsis[J].Intensive Care Med Exp,2020,8(Suppl 1):20.[11]Mishra R,Patel HK,Singasani R,et al.Tuberculosis septic shock, an elusive pathophysiology and hurdles in management: A case report and review of literature[J].World J Crit Care Med,2019,8(5):72-81.[12]Souza MC,Fonseca DM,Kanashiro A,et al.Chronic Toxoplasma gondii Infection Exacerbates Secondary Polymicrobial Sepsis[J].Front Cell Infect Microbiol,2017,7:116.[13]Coakley JD,Breen EP,Moreno-Olivera A,et al.Dysregulated T helper type 1 (Th1) and Th17 responses in elderly hospitalised patients with infection and sepsis[J].PLoS One,2019,14(10):e0224276.[14]Guo J,Tao W,Tang D,et al.Th17/regulatory T cell imbalance in sepsis patients with multiple organ dysfunction syndrome: attenuated by high-volume hemofiltration[J].Int J Artif Organs,2017,40(11):607-614.[15]Xue M,Xie J,Liu L,et al.Early and dynamic alterations of Th2/Th1 in previously immunocompetent patients with community-acquired severe sepsis:a prospective observational study[J].J Transl Med,2019,17(1):57.[16]Hu H,Di B,Tolbert WD,et al.Systematic mutational analysis of human neutrophil alpha-defensin HNP4[J].Biochim Biophys Acta Biomembr,2019,1861(4):835-844.[17]Majewski K,Zelechowska P,Brzezinska-Blaszczyk E.Circulating cathelicidin LL-37 in adult patients with pulmonary infectious diseases[J].Clin Invest Med,2017,40(1):E34-E39.[18]Alagarasu K,Patil PS,Shil P,et al.In-vitro effect of human cathelicidin antimicrobial peptide LL-37 on dengue virus type 2[J].Peptides,2017,92:23-30.[19]Man AL,Gicheva N,Regoli M,et al.CX3CR1+ Cell-Mediated Salmonella Exclusion Protects the Intestinal Mucosa during the Initial Stage of Infection[J].J Immunol,2017,198(1):335-343.[20]Marelli G,Belgiovine C,Mantovani A,et al.Non-redundant role of the chemokine receptor CX3CR1 in the anti-inflammatory function of gut macrophages[J].Immunobiology,2017,222(2):463-472.[21]Madouri F,Chenuet P,Beuraud C,et al.Protein kinase Ctheta controls type 2 innate lymphoid cell and TH2 responses to house dust mite allergen[J].J Allergy Clin Immunol,2017,139(5):1650-1666.

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更新日期/Last Update: 1900-01-01