Identification of apoptosis-immune-related gene signature and construction of diagnostic model for sepsis based on single-cell sequencing and bulk transcriptome analysis

Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sep...

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Published inFrontiers in genetics Vol. 15; p. 1389630
Main Authors Sun, Zhongyi, Hu, Yanan, Qu, Jiachen, Zhao, Qiuyue, Gao, Han, Peng, Zhiyong
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 04.06.2024
Subjects
apoptosis
bioinformatics
function analysis
gene signature
Genetics
immune landscape
sepsis
apoptosis
immune landscape
function analysis
gene signature
sepsis
bioinformatics
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Abstract Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis. Three sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis. We identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: , , , , , , , , , , and . Subsequently, a prognostic model was constructed using LASSO regression with , , and identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from , other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury. The current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. , , and might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.
AbstractList IntroductionSepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis.MethodsThree sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis.ResultsWe identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: CASP8, VDAC2, CHMP1A, CHMP5, FASLG, IFNAR1, JAK1, JAK3, STAT4, IRF9, and BCL2. Subsequently, a prognostic model was constructed using LASSO regression with BCL2, FASLG, IRF9 and JAK3 identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from IRF9, other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury.ConclusionThe current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. BCL2, FASLG, IRF9 and JAK3 might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.
Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis. Three sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis. We identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: , , , , , , , , , , and . Subsequently, a prognostic model was constructed using LASSO regression with , , and identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from , other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury. The current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. , , and might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.
Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis.IntroductionSepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis.Three sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis.MethodsThree sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis.We identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: CASP8, VDAC2, CHMP1A, CHMP5, FASLG, IFNAR1, JAK1, JAK3, STAT4, IRF9, and BCL2. Subsequently, a prognostic model was constructed using LASSO regression with BCL2, FASLG, IRF9 and JAK3 identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from IRF9, other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury.ResultsWe identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: CASP8, VDAC2, CHMP1A, CHMP5, FASLG, IFNAR1, JAK1, JAK3, STAT4, IRF9, and BCL2. Subsequently, a prognostic model was constructed using LASSO regression with BCL2, FASLG, IRF9 and JAK3 identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from IRF9, other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury.The current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. BCL2, FASLG, IRF9 and JAK3 might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.ConclusionThe current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. BCL2, FASLG, IRF9 and JAK3 might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.
Introduction Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a classic programmed cell death, contributes to the pathogenesis of various diseases. However, there is much uncertainty about its mechanism in sepsis. Methods Three sepsis gene expression profiles (GSE65682, GSE13904, and GSE26378) were downloaded from the Gene Expression Omnibus database. Apoptosis-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes Pathway database. We utilized LASSO regression and SVM-RFE algorithms to identify characteristic genes associated with sepsis. CIBERSORT and single cell sequencing analysis were employed to explore the potential relationship between hub genes and immune cell infiltration. The diagnostic capability of hub genes was validated across multiple external datasets. Subsequently, the animal sepsis model was established to assess the expression levels of hub genes in distinct target organs through RT-qPCR and Immunohistochemistry analysis. Results We identified 11 apoptosis-related genes as characteristic diagnostic markers for sepsis: CASP8 , VDAC2 , CHMP1A , CHMP5 , FASLG , IFNAR1 , JAK1 , JAK3 , STAT4 , IRF9 , and BCL2 . Subsequently, a prognostic model was constructed using LASSO regression with BCL2 , FASLG , IRF9 and JAK3 identified as hub genes. Apoptosis-related genes were closely associated with the immune response during the sepsis process. Furthermore, in the validation datasets, aside from IRF9 , other hub genes demonstrated similar expression patterns and diagnostic abilities as observed in GSE65682 dataset. In the mouse model, the expression differences of hub genes between sepsis and control group revealed the potential impacts on sepsis-induced organ injury. Conclusion The current findings indicated the participant of apoptosis in sepsis, and apoptosis-related differentially expressed genes could be used for diagnosis biomarkers. BCL2 , FASLG , IRF9 and JAK3 might be key regulatory genes affecting apoptosis in sepsis. Our findings provided a novel aspect for further exploration of the pathological mechanisms in sepsis.
Author Gao, Han
Zhao, Qiuyue
Peng, Zhiyong
Hu, Yanan
Sun, Zhongyi
Qu, Jiachen
AuthorAffiliation 3 Department of Pulmonary Medicine , Zhongnan Hospital of Wuhan University , Wuhan , China
2 Clinical Research Center of Hubei Critical Care Medicine , Wuhan , China
1 Department of Critical Care Medicine , Zhongnan Hospital of Wuhan University , Wuhan , China
AuthorAffiliation_xml – name: 2 Clinical Research Center of Hubei Critical Care Medicine , Wuhan , China
– name: 3 Department of Pulmonary Medicine , Zhongnan Hospital of Wuhan University , Wuhan , China
– name: 1 Department of Critical Care Medicine , Zhongnan Hospital of Wuhan University , Wuhan , China
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Keywords apoptosis
immune landscape
function analysis
gene signature
sepsis
bioinformatics
Language English
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Xin Ouyang, Guangdong Provincial People’s Hospital, China
Edited by: Elisa Frullanti, University of Siena, Italy
Reviewed by: Georgia Damoraki, National and Kapodistrian University of Athens, Greece
These authors have contributed equally to this work and share first authorship
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Snippet Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging. Apoptosis, a...
Introduction Sepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging....
IntroductionSepsis leads to multi-organ dysfunction due to disorders of the host response to infections, which makes diagnosis and prognosis challenging....
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SubjectTerms apoptosis
bioinformatics
function analysis
gene signature
Genetics
immune landscape
sepsis
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Title Identification of apoptosis-immune-related gene signature and construction of diagnostic model for sepsis based on single-cell sequencing and bulk transcriptome analysis
URI https://www.ncbi.nlm.nih.gov/pubmed/38894720
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