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综合转录组学和免疫分析揭示了老年患者术后谵妄相关的关键分子途径和核心基因。

Integrated transcriptomic and immune profiling reveals crucial molecular pathways and hub genes associated with postoperative delirium in elderly patients.

作者信息

Gou Zi-Han, Su Nan, Li Xiao-Chuan, Ren Da-Peng, Ren Shan-Shan, Wang Lin, Wang Yao

机构信息

Department of Anesthesiology, The People's Hospital of kaizhou District Chongqing, Chongqing, China.

Inner Mongolia People's Hospital Department of Surgical Anesthesia, Inner Mongolia, China.

出版信息

Front Med (Lausanne). 2025 May 9;12:1580355. doi: 10.3389/fmed.2025.1580355. eCollection 2025.

DOI:10.3389/fmed.2025.1580355
PMID:40417694
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12098571/
Abstract

BACKGROUND

Postoperative delirium (POD) manifests as severe mental disorientation, often experienced by elderly patients undergoing surgery, significantly hindering recovery and deteriorating the quality of life. Despite numerous clinical studies, the molecular mechanisms behind POD in elderly patients are still not well understood, requiring further investigation to identify potential biomarkers and therapeutic targets.

METHODS

This study amalgamates Gene Set Variation Analysis (GSVA), Weighted Gene Co-expression Network Analysis (WGCNA), differential expression analysis, and immune infiltration assessments to identify molecular pathways and hub genes linked to the initiation of POD in the elderly. Gene expression data were sourced from the GSE163943 dataset in the Gene Expression Omnibus (GEO) database. A total of 18,894 protein-coding genes were extracted for analysis.

RESULTS

We constructed a gene co-expression network using WGCNA and performed GSVA to investigate the link between POD and different types of cell death. The results indicated that POD is positively associated with pyroptosis and parthanatos, while negatively correlated with oxidative stress and disulfidptosis. Differential expression analysis revealed 145 differentially expressed genes (DEGs), including 83 downregulated and 62 upregulated genes. Analysis of functional enrichment revealed that DEGs were enriched in activities like neuron projection development, axonogenesis, and synapse organization, with KEGG pathway analysis identifying neuroactive ligand-receptor interaction and neurodegeneration pathways. Gene Set Enrichment Analysis (GSEA) further revealed the upregulation of the apoptosis pathway and the downregulation of neuroactive ligand-receptor interaction. Protein-protein interaction (PPI) network analysis identified 10 hub genes, including COL18A1, CD63, and LTF. Immune infiltration analysis indicated that the occurrence of POD is strongly associated with immune cell activation, particularly in T cells and macrophages.

CONCLUSION

Overall, this research primarily examines the intricate interplay between cell death processes and alterations in the immune microenvironment throughout the development of geriatric POD, pinpointing essential genes that provide vital theoretical support for further studies on geriatric POD. However, this discovery is only an initial one derived from analyzing the datasets. Upcoming research ought to evaluate and scrutinize additional datasets and conduct essential experiments to guarantee the precision and widespread relevance of the analytical findings.

摘要

背景

术后谵妄(POD)表现为严重的精神定向障碍,常发生于接受手术的老年患者中,严重阻碍康复并降低生活质量。尽管有众多临床研究,但老年患者POD背后的分子机制仍未完全明确,需要进一步研究以确定潜在的生物标志物和治疗靶点。

方法

本研究结合基因集变异分析(GSVA)、加权基因共表达网络分析(WGCNA)、差异表达分析和免疫浸润评估,以识别与老年患者POD发病相关的分子途径和核心基因。基因表达数据来自基因表达综合数据库(GEO)中的GSE163943数据集。共提取18894个蛋白质编码基因进行分析。

结果

我们使用WGCNA构建了基因共表达网络,并进行GSVA以研究POD与不同类型细胞死亡之间的联系。结果表明,POD与焦亡和PARP-1依赖性坏死呈正相关,而与氧化应激和双硫死亡呈负相关。差异表达分析揭示了145个差异表达基因(DEG),包括83个下调基因和62个上调基因。功能富集分析表明,DEG富集于神经元投射发育、轴突形成和突触组织等活动,KEGG通路分析确定了神经活性配体-受体相互作用和神经退行性变途径。基因集富集分析(GSEA)进一步揭示了凋亡途径的上调和神经活性配体-受体相互作用的下调。蛋白质-蛋白质相互作用(PPI)网络分析确定了10个核心基因,包括COL18A1、CD63和LTF。免疫浸润分析表明,POD的发生与免疫细胞激活密切相关,尤其是T细胞和巨噬细胞。

结论

总体而言,本研究主要探讨了老年POD发生过程中细胞死亡过程与免疫微环境变化之间的复杂相互作用,确定了关键基因,为进一步研究老年POD提供了重要的理论支持。然而,这一发现仅是基于对数据集的分析得出的初步结果。后续研究应评估和审查更多数据集,并进行必要的实验,以确保分析结果的准确性和广泛相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/33507ee44736/fmed-12-1580355-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/1bc9720b778b/fmed-12-1580355-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/a70e0940cc9f/fmed-12-1580355-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/33507ee44736/fmed-12-1580355-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/1bc9720b778b/fmed-12-1580355-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/a70e0940cc9f/fmed-12-1580355-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/746c/12098571/33507ee44736/fmed-12-1580355-g003.jpg

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