Identification of potential hub genes linked to immune and metabolic alterations in postoperative systemic inflammatory dysregulation

Silu Cao; Jinxuan Tang; Miaomiao Fei; Qi Jing; Fanbing Meng; Meixian Zhang; Qidong Liu; Hui Zhang; Cheng Li

doi:10.3389/fimmu.2023.1238774

Identification of potential hub genes linked to immune and metabolic alterations in postoperative systemic inflammatory dysregulation

Front Immunol. 2023 Sep 8:14:1238774. doi: 10.3389/fimmu.2023.1238774. eCollection 2023.

Authors

Silu Cao¹, Jinxuan Tang¹, Miaomiao Fei¹, Qi Jing¹, Fanbing Meng¹, Meixian Zhang¹, Qidong Liu^{1

2}, Hui Zhang¹, Cheng Li¹

Affiliations

¹ Department of Anesthesiology and Perioperative medicine, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
² Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Orthopedic Department of Tongji Hospital, Tongji University School of Medicine, Shanghai, China.

Abstract

Background: Postoperative systemic inflammatory dysregulation (PSID) is characterised by strongly interlinked immune and metabolic abnormalities. However, the hub genes responsible for the interconnections between these two systemic alterations remain to be identified.

Methods: We analysed differentially expressed genes (DEGs) of individual peripheral blood nucleated cells in patients with PSID (n = 21, CRP > 250 mg/L) and control patients (n = 25, CRP < 75 mg/L) following major abdominal surgery, along with their biological functions. Correlation analyses were conducted to explore the interconnections of immune-related DEGs (irDEGs) and metabolism-related DEGs (mrDEGs). Two methods were used to screen hub genes for irDEGs and mrDEGs: we screened for hub genes among DEGs via 12 algorithms using CytoHubba in Cytoscape, and also screened for hub immune-related and metabolic-related genes using weighted gene co-expression network analysis. The hub genes selected were involved in the interaction between changes in immunity and metabolism in PSID. Finally, we validated our results in mice with PSID to confirm the findings.

Results: We identified 512 upregulated and 254 downregulated DEGs in patients with PSID compared with controls. Gene enrichment analysis revealed that DEGs were significantly associated with immune- and metabolism-related biological processes and pathways. Correlation analyses revealed a close association between irDEGs and mrDEGs. Fourteen unique hub genes were identified via 12 screening algorithms using CytoHubba in Cytoscape and via weighted gene co-expression network analysis. Among these, CD28, CD40LG, MAPK14, and S100A12 were identified as hub genes among both immune- and metabolism-related genes; these genes play a critical role in the interaction between alterations in immunity and metabolism in PSID. The experimental results also showed that the expression of these genes was significantly altered in PSID mice.

Conclusion: This study identified hub genes associated with immune and metabolic alterations in patients with PSID and hub genes that link these alterations. These findings provide novel insights into the mechanisms underlying immune and metabolic interactions and new targets for clinical treatment can be proposed on this basis.

Keywords: C-reactive protein; hub genes; metabolism; postoperative systemic inflammatory dysregulation; surgery.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Animals
CD28 Antigens*
CD40 Ligand
Gene Expression Profiling
Humans
Mice
Postoperative Period

Substances

CD28 Antigens
CD40 Ligand

Grants and funding

We acknowledge the National Natural Science Foundation [grant number: 82271223], Shanghai Municipal Committee of Science and Technology [grant number: 23XD1422900], and Shanghai Fourth People’s Hospital, School of Medicine, Tongji University [grant numbers: sykyqd01902 and SY-XKZT-2021-2001] for providing funding support for the current work.