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Wang Q, Su Z, Zhang J, Yan H, Zhang J. Unraveling the copper-death connection: Decoding COVID-19's immune landscape through advanced bioinformatics and machine learning approaches. Hum Vaccin Immunother 2024; 20:2310359. [PMID: 38468184 PMCID: PMC10936617 DOI: 10.1080/21645515.2024.2310359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/23/2024] [Indexed: 03/13/2024] Open
Abstract
This study aims to analyze Coronavirus Disease 2019 (COVID-19)-associated copper-death genes using the Gene Expression Omnibus (GEO) dataset and machine learning, exploring their immune microenvironment correlation and underlying mechanisms. Utilizing GEO, we analyzed the GSE217948 dataset with control samples. Differential expression analysis identified 16 differentially expressed copper-death genes, and Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) quantified immune cell infiltration. Gene classification yielded two copper-death clusters, with Weighted Gene Co-expression Network Analysis (WGCNA) identifying key module genes. Machine learning models (random forest, Support Vector Machine (SVM), Generalized Linear Model (GLM), eXtreme Gradient Boosting (XGBoost)) selected 6 feature genes validated by the GSE213313 dataset. Ferredoxin 1 (FDX1) emerged as the top gene, corroborated by Area Under the Curve (AUC) analysis. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) revealed enriched pathways in T cell receptor, natural killer cytotoxicity, and Peroxisome Proliferator-Activated Receptor (PPAR). We uncovered differentially expressed copper-death genes and immune infiltration differences, notably CD8 T cells and M0 macrophages. Clustering identified modules with potential implications for COVID-19. Machine learning models effectively predicted COVID-19 risk, with FDX1's pivotal role validated. FDX1's high expression was associated with immune pathways, suggesting its role in COVID-19 pathogenesis. This comprehensive approach elucidated COVID-19-related copper-death genes, their immune context, and risk prediction potential. FDX1's connection to immune pathways offers insights into COVID-19 mechanisms and therapy.
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Affiliation(s)
- Qi Wang
- Department of Respiratory and Critical Care Medicine, The Second Hospital of Jilin University, Changchun, Jilin, China
| | - Zhenzhong Su
- Department of Respiratory and Critical Care Medicine, The Second Hospital of Jilin University, Changchun, Jilin, China
| | - Jing Zhang
- Department of General Gynecology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - He Yan
- Department of Respiratory and Critical Care Medicine, The Second Hospital of Jilin University, Changchun, Jilin, China
| | - Jie Zhang
- Department of Respiratory and Critical Care Medicine, The Second Hospital of Jilin University, Changchun, Jilin, China
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Yi C, Zhang H, Yang J, Chen D, Jiang S. Elucidating common pathogenic transcriptional networks in infective endocarditis and sepsis: integrated insights from biomarker discovery and single-cell RNA sequencing. Front Immunol 2024; 14:1298041. [PMID: 38332910 PMCID: PMC10851146 DOI: 10.3389/fimmu.2023.1298041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 12/27/2023] [Indexed: 02/10/2024] Open
Abstract
Background Infective Endocarditis (IE) and Sepsis are two closely related infectious diseases, yet their shared pathogenic mechanisms at the transcriptional level remain unclear. This research gap poses a barrier to the development of refined therapeutic strategies and drug innovation. Methods This study employed a collaborative approach using both microarray data and single-cell RNA sequencing (scRNA-seq) data to identify biomarkers for IE and Sepsis. It also offered an in-depth analysis of the roles and regulatory patterns of immune cells in these diseases. Results We successfully identified four key biomarkers correlated with IE and Sepsis, namely CD177, IRAK3, RNASE2, and S100A12. Further investigation revealed the central role of Th1 cells, B cells, T cells, and IL-10, among other immune cells and cytokines, in the pathogenesis of these conditions. Notably, the small molecule drug Matrine exhibited potential therapeutic effects by targeting IL-10. Additionally, we discovered two Sepsis subgroups with distinct inflammatory responses and therapeutic strategies, where CD177 demonstrated significant classification value. The reliability of CD177 as a biomarker was further validated through qRT-PCR experiments. Conclusion This research not only paves the way for early diagnosis and treatment of IE and Sepsis but also underscores the importance of identifying shared pathogenic mechanisms and novel therapeutic targets at the transcriptional level. Despite limitations in data volume and experimental validation, these preliminary findings add new perspectives to our understanding of these complex diseases.
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Affiliation(s)
- Chen Yi
- Department of Biomedical Engineering, Nanchang Hang Kong University, Nanchang, Jiangxi, China
| | - Haoxiang Zhang
- Department of Biomedical Engineering, Nanchang Hang Kong University, Nanchang, Jiangxi, China
| | - Jun Yang
- Department of Biomedical Engineering, Nanchang Hang Kong University, Nanchang, Jiangxi, China
| | - Dongjuan Chen
- Department of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaofeng Jiang
- Department of Biomedical Engineering, Nanchang Hang Kong University, Nanchang, Jiangxi, China
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Xiao YP, Cheng YC, Chen C, Xue HM, Yang M, Lin C. Identification of the Shared Gene Signatures of HCK, NOG, RNF125 and Biological Mechanism in Pediatric Acute Lymphoblastic Leukaemia and Pediatric Sepsis. Mol Biotechnol 2023:10.1007/s12033-023-00979-6. [PMID: 38123749 DOI: 10.1007/s12033-023-00979-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 11/02/2023] [Indexed: 12/23/2023]
Abstract
The shared mechanisms between pediatric acute lymphoblastic leukaemia (ALL) and pediatric sepsis are currently unclear. This study was aimed to explore the shared key genes of pediatric ALL and pediatric sepsis. The datasets involved were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control samples in GSE13904 and GSE79533 were intersected. The least absolute shrinkage and selection operator (LASSO) and the boruta analyses were performed in GSE13904 and GSE79533 separately based on shared DEGs, and shared key genes were obtained by taking the intersection of sepsis-related key genes and ALL-related key genes. Three shared key genes (HCK, NOG, RNF125) were obtained, that have a good diagnostic value for both sepsis and ALL. The correlation between shared key genes and differentially expressed immune cells was higher in GSE13904 and conversely, the correlation of which was lower in GSE79533. Suggesting that the sharing key genes had a different impact on the immune environment in pediatric ALL and pediatric sepsis. We make the case that this study provides a new perspective to study the relationship between pediatric ALL and pediatric sepsis.
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Affiliation(s)
- Ying-Ping Xiao
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
| | - Yu-Cai Cheng
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
| | - Chun Chen
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
| | - Hong-Man Xue
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
| | - Mo Yang
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China.
- Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China.
| | - Chao Lin
- Pediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China.
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Liu Z, Qiu E, Yang B, Zeng Y. Uncovering hub genes in sepsis through bioinformatics analysis. Medicine (Baltimore) 2023; 102:e36237. [PMID: 38050254 PMCID: PMC10695588 DOI: 10.1097/md.0000000000036237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/31/2023] [Indexed: 12/06/2023] Open
Abstract
In-depth studies on the mechanisms of pathogenesis of sepsis and diagnostic biomarkers in the early stages may be the key to developing individualized and effective treatment strategies. This study aimed to identify sepsis-related hub genes and evaluate their diagnostic reliability. The gene expression profiles of GSE4607 and GSE131761 were obtained from the Gene Expression Omnibus. Differentially co-expressed genes between the sepsis and control groups were screened. Single-sample gene set enrichment analysis and gene set variation analysis were performed to investigate the biological functions of the hub genes. A receiver operating characteristic curve was used to evaluate diagnostic value. Datasets GSE154918 and GSE185263 were used as external validation datasets to verify the reliability of the hub genes. Four differentially co-expressed genes, FAM89A, FFAR3, G0S2, and FGF13, were extracted using a weighted gene co-expression network analysis and differential gene expression analysis methods. These 4 genes were upregulated in the sepsis group and were distinct from those in the controls. Moreover, the receiver operating characteristic curves of the 4 genes exhibited considerable diagnostic value in discriminating septic blood samples from those of the non-septic control group. The reliability and consistency of these 4 genes were externally validated. Single-sample gene set enrichment analysis and gene set variation analysis analyses indicated that the 4 hub genes were significantly correlated with the regulation of immunity and metabolism in sepsis. The identified FAM89A, FFAR3, G0S2, and FGF13 genes may help elucidate the molecular mechanisms underlying sepsis and drive the introduction of new biomarkers to advance diagnosis and treatment.
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Affiliation(s)
- Zhao Liu
- Department of Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, China
| | - Eryue Qiu
- Department of Trauma Center, Zhuzhou Central Hospital, Zhuzhou, China
| | - Bihui Yang
- Department of Hematology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Yiqian Zeng
- Department of Trauma Center, Zhuzhou Central Hospital, Zhuzhou, China
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Liu J, Wang H, Xiao H, Ji L, Yao Y, Cao C, Liu Y, Huang L. Predicting the prognosis in patients with sepsis by an endoplasmic reticulum stress gene signature. Aging (Albany NY) 2023; 15:13434-13451. [PMID: 38011291 DOI: 10.18632/aging.205252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/11/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Prognostic stratification of patients with sepsis is important for the development of individualized treatment strategies. Endoplasmic reticulum stress (ERS) plays a key role in sepsis. This study aimed to identify a set of genes related to ER stress to construct a predictive model for the prognosis of sepsis. METHODS The transcriptomic and clinical data of 479 sepsis patients were obtained from GSE65682 and divided into a training set (n=288) and a validation set (n=191) at a ratio of 3:2. The external test set was GSE95233 (n=51). LASSO and Cox regression analyses were performed to establish a signature to predict the prognosis of patients with sepsis. Moreover, we developed a nomogram that included the risk signature and clinical features to predict survival probability. RESULTS A prognostic signature was constructed with ten endoplasmic reticulum related genes (ADRB2, DHCR7, GABARAPL2, MAOA, MPO, PDZD8, QDPR, SCAP, TFRC, and TLR4) in the training set, which significantly divided patients with sepsis into high- and low-risk groups in terms of survival. This signature was validated using validation and external test sets. A nomogram based on the risk signature was constructed to quantitatively predict the prognosis of patients with sepsis. CONCLUSIONS We constructed an ERS signature as a novel prognostic marker for predicting survival in sepsis patients, which could be used to develop novel biomarkers for the diagnosis, treatment, and prognosis of sepsis and to provide new ideas and prospects for future clinical research.
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Affiliation(s)
- Jian Liu
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Hao Wang
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Huimin Xiao
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Li Ji
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yonghui Yao
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Chunshui Cao
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yong Liu
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Liang Huang
- Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
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Wufuer D, Li Y, Aierken H, Zheng J. Bioinformatics-led discovery of ferroptosis-associated diagnostic biomarkers and molecule subtypes for tuberculosis patients. Eur J Med Res 2023; 28:445. [PMID: 37853432 PMCID: PMC10585777 DOI: 10.1186/s40001-023-01371-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 09/13/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Ferroptosis is closely associated with the pathophysiological processes of many diseases, such as infection, and is characterized by the accumulation of excess lipid peroxides on the cell membranes. However, studies on the ferroptosis-related diagnostic markers in tuberculosis (TB) is still lacking. Our study aimed to explore the role of ferroptosis-related biomarkers and molecular subtypes in TB. METHODS GSE83456 dataset was applied to identify ferroptosis-related genes (FRGs) associated with TB, and GSE42826, GSE28623, and GSE34608 datasets for external validation of core biomarkers. Core FRGs were identified using weighted gene co-expression network analysis (WGCNA). Subsequently, two ferroptosis-related subtypes were constructed based on ferroptosis score, and differently expressed analysis, GSEA, GSEA, immune cell infiltration analysis between the two subtypes were performed.Affiliations: Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.correctly RESULTS: A total of 22 FRGs were identified, of which three genes (CHMP5, SAT1, ZFP36) were identified as diagnostic biomarkers that were enriched in pathways related to immune-inflammatory response. In addition, TB patients were divided into high- and low-ferroptosis subtypes (HF and LF) based on ferroptosis score. HF patients had activated immune- and inflammation-related pathways and higher immune cell infiltration levels than LF patients. CONCLUSION Three potential diagnostic biomarkers and two ferroptosis-related subtypes were identified in TB patients, which would help to understand the pathogenesis of TB.Author names: Kindly check and confirm the process of the author names [2,4]correctly.
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Affiliation(s)
- Dilinuer Wufuer
- The First Affiliated Hospital of Guangzhou Medical University/National Clinical Research Center for Respiratory Disease/National Respiratory Medical Center/State Key Laboratory of Respiratory Disease/Guangzhou Institute of Respiratory Health, NO. 151 Yanjang Road, Guangzhou, 510120, China
| | - YuanYuan Li
- Department of Respiratory Medicine, Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, 830049, Xinjiang, China
| | - Haidiya Aierken
- Department of Respiratory Medicine, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, Xinjiang, China
| | - JinPing Zheng
- The First Affiliated Hospital of Guangzhou Medical University/National Clinical Research Center for Respiratory Disease/National Respiratory Medical Center/State Key Laboratory of Respiratory Disease/Guangzhou Institute of Respiratory Health, NO. 151 Yanjang Road, Guangzhou, 510120, China.
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Cheng X, Wang S, Li Z, He D, Wu J, Ding W. IL-1β-pretreated bone mesenchymal stem cell-derived exosomes alleviate septic endoplasmic reticulum stress via regulating SIRT1/ERK pathway. Heliyon 2023; 9:e20124. [PMID: 37771539 PMCID: PMC10522952 DOI: 10.1016/j.heliyon.2023.e20124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/10/2023] [Accepted: 09/12/2023] [Indexed: 09/30/2023] Open
Abstract
Background Endoplasmic reticulum (ER) plays a crucial role in the development of organ injury caused by sepsis. Therefore, it is highly important to devise strategies that specially target ER stress for the treatment of sepsis. Previous research has shown that priming chemokines can enhance the therapeutic effects of mesenchymal stem cells (MSCs). In this study, we aimed to investigate the function and mechanism of exosomes derived from MSCs that were pretreated with IL-1β (IB-exos) in the context of septic ER stress. Methods Mouse bone MSCs were preconditioned with or without IL-1β and the supernatant was used for exosome extraction. In vitro sepsis cell mode was induced by treating HUVECs with LPS, while in vivo sepsis model was established through cecal ligation and puncture (CLP) operation in mice. Cell viability, apoptosis, motility, and tube formation were assessed using the EDU proliferation assay, flow cytometry analysis, migration assay, and tube formation assay, respectively. The molecular mechanism was investigated using ELISA, qRT-PCR, Western blot, and immunofluorescence staining. Results Pretreatment with IL-1β enhanced the positive impact of MSC-exos on the viability, apoptosis, motility, and tube formation ability of HUVECs. The administration of LPS or CLP increased ER stress response, but this effect was blocked by the treatment of IB-exos. Additionally, IB-exos reversed the inhibitory effects of LPS or CLP on the expression levels of SIRT1 and ERK phosphorylation. Knockdown of SIRT1 counteracted the effects of IB-exos on HUVEC cellular function and ER stress. In a mouse model, the injection of IB-exos mitigated sepsis-induced lung injury by inhibiting ER stress response through the activation of SIRT1. Conclusion IB-exos have been found to alleviate sepsis-induced lung injury via inhibiting ER stress through the SIRT1/ERK pathway. These findings indicated that IB-exos could potentially be used as a strategy to mitigate lung injury caused by sepsis.
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Affiliation(s)
- Xinsheng Cheng
- Division of Trauma and Acute Care Surgery, Department of Surgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, China
- Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen, Guangdong, China
| | - Shikai Wang
- Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen, Guangdong, China
| | - Zhipeng Li
- Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen, Guangdong, China
| | - Di He
- Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen, Guangdong, China
| | - Jianguo Wu
- Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen, Guangdong, China
| | - Weiwei Ding
- Division of Trauma and Acute Care Surgery, Department of Surgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, China
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Tong R, Ding X, Liu F, Li H, Liu H, Song H, Wang Y, Zhang X, Liu S, Sun T. Classification of subtypes and identification of dysregulated genes in sepsis. Front Cell Infect Microbiol 2023; 13:1226159. [PMID: 37671148 PMCID: PMC10475835 DOI: 10.3389/fcimb.2023.1226159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 08/07/2023] [Indexed: 09/07/2023] Open
Abstract
Background Sepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis. Methods The datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples. Results A total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients. Conclusion This study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.
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Affiliation(s)
- Ran Tong
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Xianfei Ding
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Fengyu Liu
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Hongyi Li
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Huan Liu
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Heng Song
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuze Wang
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Xiaojuan Zhang
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Shaohua Liu
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
| | - Tongwen Sun
- General Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Henan Key Laboratory of Critical Care Medicine, Henan Engineering Research Center for Critical Care Medicine, Zhengzhou, Henan, China
- Zhengzhou Key Laboratory of Sepsis, Zhengzhou, Henan, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
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