Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury

BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets...
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Autor*in:	Zhiwen Cao [verfasserIn] Peipei Lu [verfasserIn] Li Li [verfasserIn] Qi Geng [verfasserIn] Lin Lin [verfasserIn] Lan Yan [verfasserIn] Lulu Zhang [verfasserIn] Changqi Shi [verfasserIn] Ning Zhao [verfasserIn] Xiaojuan He [verfasserIn] Yong Tan [verfasserIn] Cheng Lu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide

Übergeordnetes Werk:	In: Frontiers in Immunology - Frontiers Media S.A., 2011, 14(2023)
Übergeordnetes Werk:	volume:14 ; year:2023

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fimmu.2023.1287136

Katalog-ID:	DOAJ100020461

Internformat


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520			\|a BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.
650		4	\|a acute liver injury
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650		4	\|a triptolide
653		0	\|a Immunologic diseases. Allergy
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allfields	10.3389/fimmu.2023.1287136 doi (DE-627)DOAJ100020461 (DE-599)DOAJ5aa6f2a5185c4a11867626bf7a2dc58f DE-627 ger DE-627 rakwb eng RC581-607 Zhiwen Cao verfasserin aut Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI. acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide Immunologic diseases. Allergy Peipei Lu verfasserin aut Li Li verfasserin aut Qi Geng verfasserin aut Lin Lin verfasserin aut Lan Yan verfasserin aut Lulu Zhang verfasserin aut Changqi Shi verfasserin aut Li Li verfasserin aut Ning Zhao verfasserin aut Xiaojuan He verfasserin aut Yong Tan verfasserin aut Cheng Lu verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 14(2023) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:14 year:2023 https://doi.org/10.3389/fimmu.2023.1287136 kostenfrei https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023
spelling	10.3389/fimmu.2023.1287136 doi (DE-627)DOAJ100020461 (DE-599)DOAJ5aa6f2a5185c4a11867626bf7a2dc58f DE-627 ger DE-627 rakwb eng RC581-607 Zhiwen Cao verfasserin aut Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI. acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide Immunologic diseases. Allergy Peipei Lu verfasserin aut Li Li verfasserin aut Qi Geng verfasserin aut Lin Lin verfasserin aut Lan Yan verfasserin aut Lulu Zhang verfasserin aut Changqi Shi verfasserin aut Li Li verfasserin aut Ning Zhao verfasserin aut Xiaojuan He verfasserin aut Yong Tan verfasserin aut Cheng Lu verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 14(2023) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:14 year:2023 https://doi.org/10.3389/fimmu.2023.1287136 kostenfrei https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023
allfields_unstemmed	10.3389/fimmu.2023.1287136 doi (DE-627)DOAJ100020461 (DE-599)DOAJ5aa6f2a5185c4a11867626bf7a2dc58f DE-627 ger DE-627 rakwb eng RC581-607 Zhiwen Cao verfasserin aut Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI. acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide Immunologic diseases. Allergy Peipei Lu verfasserin aut Li Li verfasserin aut Qi Geng verfasserin aut Lin Lin verfasserin aut Lan Yan verfasserin aut Lulu Zhang verfasserin aut Changqi Shi verfasserin aut Li Li verfasserin aut Ning Zhao verfasserin aut Xiaojuan He verfasserin aut Yong Tan verfasserin aut Cheng Lu verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 14(2023) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:14 year:2023 https://doi.org/10.3389/fimmu.2023.1287136 kostenfrei https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023
allfieldsGer	10.3389/fimmu.2023.1287136 doi (DE-627)DOAJ100020461 (DE-599)DOAJ5aa6f2a5185c4a11867626bf7a2dc58f DE-627 ger DE-627 rakwb eng RC581-607 Zhiwen Cao verfasserin aut Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI. acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide Immunologic diseases. Allergy Peipei Lu verfasserin aut Li Li verfasserin aut Qi Geng verfasserin aut Lin Lin verfasserin aut Lan Yan verfasserin aut Lulu Zhang verfasserin aut Changqi Shi verfasserin aut Li Li verfasserin aut Ning Zhao verfasserin aut Xiaojuan He verfasserin aut Yong Tan verfasserin aut Cheng Lu verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 14(2023) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:14 year:2023 https://doi.org/10.3389/fimmu.2023.1287136 kostenfrei https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023
allfieldsSound	10.3389/fimmu.2023.1287136 doi (DE-627)DOAJ100020461 (DE-599)DOAJ5aa6f2a5185c4a11867626bf7a2dc58f DE-627 ger DE-627 rakwb eng RC581-607 Zhiwen Cao verfasserin aut Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI. acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide Immunologic diseases. Allergy Peipei Lu verfasserin aut Li Li verfasserin aut Qi Geng verfasserin aut Lin Lin verfasserin aut Lan Yan verfasserin aut Lulu Zhang verfasserin aut Changqi Shi verfasserin aut Li Li verfasserin aut Ning Zhao verfasserin aut Xiaojuan He verfasserin aut Yong Tan verfasserin aut Cheng Lu verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 14(2023) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:14 year:2023 https://doi.org/10.3389/fimmu.2023.1287136 kostenfrei https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023
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authorswithroles_txt_mv	Zhiwen Cao @@aut@@ Peipei Lu @@aut@@ Li Li @@aut@@ Qi Geng @@aut@@ Lin Lin @@aut@@ Lan Yan @@aut@@ Lulu Zhang @@aut@@ Changqi Shi @@aut@@ Ning Zhao @@aut@@ Xiaojuan He @@aut@@ Yong Tan @@aut@@ Cheng Lu @@aut@@
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The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. 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callnumber-first	R - Medicine
author	Zhiwen Cao
spellingShingle	Zhiwen Cao misc RC581-607 misc acute liver injury misc immunoinfiltration misc bioinformatics misc acetaminophen misc triptolide misc Immunologic diseases. Allergy Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury
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topic_title	RC581-607 Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury acute liver injury immunoinfiltration bioinformatics acetaminophen triptolide
topic	misc RC581-607 misc acute liver injury misc immunoinfiltration misc bioinformatics misc acetaminophen misc triptolide misc Immunologic diseases. Allergy
topic_unstemmed	misc RC581-607 misc acute liver injury misc immunoinfiltration misc bioinformatics misc acetaminophen misc triptolide misc Immunologic diseases. Allergy
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title	Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury
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title_sort	bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury
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title_auth	Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury
abstract	BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.
abstractGer	BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.
abstract_unstemmed	BackgroundAcute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.
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title_short	Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury
url	https://doi.org/10.3389/fimmu.2023.1287136 https://doaj.org/article/5aa6f2a5185c4a11867626bf7a2dc58f https://www.frontiersin.org/articles/10.3389/fimmu.2023.1287136/full https://doaj.org/toc/1664-3224
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This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI.MethodsThe datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models.ResultsFunctional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">acute liver injury</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">immunoinfiltration</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bioinformatics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">acetaminophen</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">triptolide</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Immunologic diseases. 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Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury

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