Mechanism of COVID-19-Related Proteins in Spinal Tuberculosis: Immune Dysregulation.
Mechanism of COVID-19-Related Proteins in Spinal Tuberculosis: Immune Dysregulation.
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脊柱结核中 COVID-19 相关蛋白的机制：免疫失调
DOI：
10.3389/fimmu.2022.882651
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
--
作者：
本文的目的是探讨脊柱结核（STB）中 COVID-19 相关蛋白免疫失调的机制。收集临床数据以构建列线图模型。使用C指数、校准曲线、ROC曲线和DCA曲线来评估模型的预测能力和准确性。此外，还收集了 10 个椎间盘样本进行蛋白质鉴定。利用生物信息学分析差异表达蛋白（DEP），包括免疫细胞分析、基因本体（GO）和KEGG通路富集分析以及蛋白质-蛋白质相互作用网络（PPI）。列线图预测 STB 的风险范围为 0.01 至 0.994。训练集中的 C 指数和 AUC 分别为 0.872 和 0.862。外部验证集的结果与训练集一致。免疫细胞评分表明，STB 组织中的原始 B 细胞显着低于非 TB 脊髓组织。 Hub 蛋白通过 Degree、Closeness 和 MCC 方法计算。主要的KEGG途径包括冠状病毒病-COVID-19。 COVID-19相关蛋白和枢纽蛋白的交叉点中有9个关键蛋白。初始 B 细胞与 RPL19 之间呈负相关。 COVID-19 相关蛋白与免疫基因相关。淋巴细胞是STB诊断的预测因素。免疫细胞在 STB 中表现出低表达。九种与 COVID-19 相关的蛋白质参与了 STB 机制。这九个关键蛋白可能通过调节免疫基因的表达来抑制STB的免疫机制。
The purpose of this article was to investigate the mechanism of immune dysregulation of COVID-19-related proteins in spinal tuberculosis (STB). Clinical data were collected to construct a nomogram model. C-index, calibration curve, ROC curve, and DCA curve were used to assess the predictive ability and accuracy of the model. Additionally, 10 intervertebral disc samples were collected for protein identification. Bioinformatics was used to analyze differentially expressed proteins (DEPs), including immune cells analysis, Gene Ontology (GO) and KEGG pathway enrichment analysis, and protein-protein interaction networks (PPI). The nomogram predicted risk of STB ranging from 0.01 to 0.994. The C-index and AUC in the training set were 0.872 and 0.862, respectively. The results in the external validation set were consistent with the training set. Immune cells scores indicated that B cells naive in STB tissues were significantly lower than non-TB spinal tissues. Hub proteins were calculated by Degree, Closeness, and MCC methods. The main KEGG pathway included Coronavirus disease-COVID-19. There were 9 key proteins in the intersection of COVID-19-related proteins and hub proteins. There was a negative correlation between B cells naive and RPL19. COVID-19-related proteins were associated with immune genes. Lymphocytes were predictive factors for the diagnosis of STB. Immune cells showed low expression in STB. Nine COVID-19-related proteins were involved in STB mechanisms. These nine key proteins may suppress the immune mechanism of STB by regulating the expression of immune genes.
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影响因子：
3.9
作者：
Karami H;Derakhshani A;Ghasemigol M;Fereidouni M;Miri-Moghaddam E;Baradaran B;Tabrizi NJ;Najafi S;Solimando AG;Marsh LM;Silvestris N;De Summa S;Paradiso AV;Racanelli V;Safarpour H
通讯作者：
Safarpour H
影响因子：
14.2
作者：
Batirel, A.;Erdem, H.;Vahaboglu, H.
通讯作者：
Vahaboglu, H.
DOI：
10.1165/rcmb.2019-0261oc
发表时间：
2020-04-01
影响因子：
6.4
作者：
La Manna, Marco Pio;Orlando, Valentina;Caccamo, Nadia
通讯作者：
Caccamo, Nadia
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影响因子：
6.7
作者：
Hu S;Du X;Huang Y;Fu Y;Yang Y;Zhan X;He W;Wen Q;Zhou X;Zhou C;Zhong XP;Yang J;Xiong W;Wang R;Gao Y;Ma L
通讯作者：
Ma L
DOI：
10.1016/j.ijid.2021.02.107
发表时间：
2021-12
期刊：
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
影响因子：
--
作者：
Chakaya J;Khan M;Ntoumi F;Aklillu E;Fatima R;Mwaba P;Kapata N;Mfinanga S;Hasnain SE;Katoto PDMC;Bulabula ANH;Sam-Agudu NA;Nachega JB;Tiberi S;McHugh TD;Abubakar I;Zumla A
通讯作者：
Zumla A