Evidence mapPaperPMID 40417694Full record

ArticleFrontiers in medicine2025

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

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

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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5 · Who and what money

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7 authors.

Zi-Han Gou *Department of Anesthesiology, The People's Hospital of kaizhou District Chongqing, Chongqing, China.
Nan Su *Inner Mongolia People's Hospital Department of Surgical Anesthesia, Inner Mongolia, China.
Xiao-Chuan LiDepartment of Orthopaedic, Chongqing Sanbo Changan Hospital, Chongqing, China.
Da-Peng RenDepartment of Anesthesiology, The People's Hospital of kaizhou District Chongqing, Chongqing, China.
Shan-Shan RenDepartment of Anesthesiology, The Thirteenth People's Hospital of Chongqing, Chongqing, China.
Lin WangDepartment of Anesthesiology, The Thirteenth People's Hospital of Chongqing, Chongqing, China.
Yao WangDepartment of Anesthesiology, The Thirteenth People's Hospital of Chongqing, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

cell deathelderlyimmune microenvironmentpostoperative deliriumPPIWGCNA

Identifiers

PMID40417694
PMCPMC12098571

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