Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis
Abstract Background Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear. Results In this study, bioinformatics analysis revealed the novel key biomarkers assoc...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-01-01
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| Series: | BMC Infectious Diseases |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12879-023-08883-9 |
| _version_ | 1827388717354975232 |
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| author | Pingping Liang Yongjian Wu Siying Qu Muhammad Younis Wei Wang Zhilong Wu Xi Huang |
| author_facet | Pingping Liang Yongjian Wu Siying Qu Muhammad Younis Wei Wang Zhilong Wu Xi Huang |
| author_sort | Pingping Liang |
| collection | DOAJ |
| description | Abstract Background Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear. Results In this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein–protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases. Conclusions These results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis. |
| first_indexed | 2024-03-08T16:22:57Z |
| format | Article |
| id | doaj.art-06976617f6ad4f46b28c9a82e4017e59 |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-03-08T16:22:57Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj.art-06976617f6ad4f46b28c9a82e4017e592024-01-07T12:13:18ZengBMCBMC Infectious Diseases1471-23342024-01-0124111410.1186/s12879-023-08883-9Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysisPingping Liang0Yongjian Wu1Siying Qu2Muhammad Younis3Wei Wang4Zhilong Wu5Xi Huang6Foshan Fourth People’s Hospital, Guangdong ProvinceCenter for Infection and Immunity and Guangdong Provincial Engineering Research Center of Molecular Imaging, the Fifth Affiliated Hospital of Sun Yat-Sen UniversityDepartment of Clinical Laboratory, Zhuhai Hospital of Integrated Traditional Chinese and Western Medicine, The Second People’s Hospital of Zhuhai, Guangdong ProvinceFoshan Fourth People’s Hospital, Guangdong ProvinceFoshan Fourth People’s Hospital, Guangdong ProvinceFoshan Fourth People’s Hospital, Guangdong ProvinceFoshan Fourth People’s Hospital, Guangdong ProvinceAbstract Background Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear. Results In this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein–protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases. Conclusions These results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis.https://doi.org/10.1186/s12879-023-08883-9SepsisBiomarkersIntegrated transcriptomeTherapyDrugs |
| spellingShingle | Pingping Liang Yongjian Wu Siying Qu Muhammad Younis Wei Wang Zhilong Wu Xi Huang Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis BMC Infectious Diseases Sepsis Biomarkers Integrated transcriptome Therapy Drugs |
| title | Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| title_full | Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| title_fullStr | Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| title_full_unstemmed | Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| title_short | Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| title_sort | exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis |
| topic | Sepsis Biomarkers Integrated transcriptome Therapy Drugs |
| url | https://doi.org/10.1186/s12879-023-08883-9 |
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