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已发表论文
通过转录组分析识别和分析瑞马唑仑在小鼠脓毒症相关性脑病中的潜在治疗机制
Authors Zhou J, Hu W , Luo Y, Zhang X , Hu B , Zou X
Received 22 August 2025
Accepted for publication 24 January 2026
Published 3 February 2026 Volume 2026:19 562264
DOI https://doi.org/10.2147/JIR.S562264
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Anh Ngo
Jin Zhou,1,* Wen Hu,1,* Yushan Luo,2 Xujiao Zhang,2 Bailong Hu,1 Xiaohua Zou1
1Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China; 2School of Anesthesiology, Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Bailong Hu, Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China, Tel +86-15185184309, Email 375896605@qq.com Xiaohua Zou, Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China, Tel +86-13809416036, Fax +86-851-86771013, Email zouxiaohuazxh@163.com
Background: Sepsis-associated encephalopathy (SAE) is a common complication of sepsis, marked by neuroinflammation and cognitive impairment. Remimazolam (Rem), a novel ultra-short-acting benzodiazepine, exhibits potential anti-inflammatory and neuroprotective effects; however, its molecular mechanisms in SAE remain poorly understood.
Methods: Male mice were randomly assigned to three groups: SHAM (Con, n=6), Sepsis (CLP, n=6), and remimazolam-treated Sepsis (Rem, n=6). Hippocampal tissues were collected for RNA sequencing. Differential expression analysis was performed to identify genes modulated by Rem treatment. To further screen candidate genes, weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) networks were utilized, and functional enrichment was assessed through gene set enrichment analysis (GSEA). Immune microenvironment alterations were compared across groups, and potential therapeutic compounds targeting hub genes were predicted using public drug–gene interaction databases. Hub gene expression was validated at both mRNA (qRT-PCR) and protein levels.
Results: RNA-seq identified 3397 and 914 differentially expressed genes (DEGs) in the Sepsis (CLP vs Con) and remimazolam-treated (Rem vs CLP) groups, respectively. A total of 647 key DEGs with opposing expression trends were screened. Through WGCNA and PPI analysis, five hub genes—ICAM1, Tlr2, Cd274, FOS, and SOCS3—were identified. Pathways related to inflammatory response, IL6/JAK/STAT3 signaling, and TNFα/NF-κB signaling were significantly enriched with these genes, suggesting their potential role in the pathogenesis of SAE. Among the twenty-one candidate drugs predicted to target these hub genes, AVELUMAB-CD274 and LIFITEGRAST-ICAM1 exhibited high binding affinity. The expressions of ICAM1, Tlr2, Cd274, and SOCS3 were further validated at both mRNA (qRT-PCR) and protein levels, corroborating the transcriptomic findings.
Conclusion: This study reveals that ICAM1, Tlr2, Cd274, and SOCS3 are key molecular correlates of remimazolam treatment in a murine SAE model. Our transcriptomic analysis offers insights into the molecular basis of remimazolam’s protective effects, highlighting these genes and pathways for future research.
Keywords: sepsis-associated encephalopathy, remimazolam, immune microenvironmental, RNA sequencing
1Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China; 2School of Anesthesiology, Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Bailong Hu, Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China, Tel +86-15185184309, Email 375896605@qq.com Xiaohua Zou, Department of Anesthesiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China, Tel +86-13809416036, Fax +86-851-86771013, Email zouxiaohuazxh@163.com
Background: Sepsis-associated encephalopathy (SAE) is a common complication of sepsis, marked by neuroinflammation and cognitive impairment. Remimazolam (Rem), a novel ultra-short-acting benzodiazepine, exhibits potential anti-inflammatory and neuroprotective effects; however, its molecular mechanisms in SAE remain poorly understood.
Methods: Male mice were randomly assigned to three groups: SHAM (Con, n=6), Sepsis (CLP, n=6), and remimazolam-treated Sepsis (Rem, n=6). Hippocampal tissues were collected for RNA sequencing. Differential expression analysis was performed to identify genes modulated by Rem treatment. To further screen candidate genes, weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) networks were utilized, and functional enrichment was assessed through gene set enrichment analysis (GSEA). Immune microenvironment alterations were compared across groups, and potential therapeutic compounds targeting hub genes were predicted using public drug–gene interaction databases. Hub gene expression was validated at both mRNA (qRT-PCR) and protein levels.
Results: RNA-seq identified 3397 and 914 differentially expressed genes (DEGs) in the Sepsis (CLP vs Con) and remimazolam-treated (Rem vs CLP) groups, respectively. A total of 647 key DEGs with opposing expression trends were screened. Through WGCNA and PPI analysis, five hub genes—ICAM1, Tlr2, Cd274, FOS, and SOCS3—were identified. Pathways related to inflammatory response, IL6/JAK/STAT3 signaling, and TNFα/NF-κB signaling were significantly enriched with these genes, suggesting their potential role in the pathogenesis of SAE. Among the twenty-one candidate drugs predicted to target these hub genes, AVELUMAB-CD274 and LIFITEGRAST-ICAM1 exhibited high binding affinity. The expressions of ICAM1, Tlr2, Cd274, and SOCS3 were further validated at both mRNA (qRT-PCR) and protein levels, corroborating the transcriptomic findings.
Conclusion: This study reveals that ICAM1, Tlr2, Cd274, and SOCS3 are key molecular correlates of remimazolam treatment in a murine SAE model. Our transcriptomic analysis offers insights into the molecular basis of remimazolam’s protective effects, highlighting these genes and pathways for future research.
Keywords: sepsis-associated encephalopathy, remimazolam, immune microenvironmental, RNA sequencing