Identification of an Immune-Related Gene Diagnostic Model and Potential Drugs in Sepsis Using Bioinformatics and Pharmacogenomics Approaches

Abstract

Purpose

Sepsis is an organ dysfunction with high mortality. Early identification, diagnosis, and effective treatment of sepsis are beneficial to the survival of patients. This study aimed to find potential diagnosis and immune-related genes, and drug targets, which could provide novel diagnostic and therapeutic markers for sepsis.

Patients and Methods

The GSE69063, GSE154918 and GSE28750 datasets were integrated to evaluate immune infiltration and identify differentially expressed genes (DEGs) and immune-related genes. Weighted gene co-expression network analysis (WGCNA) was applied to find the hub module related to immune score and sepsis. Immune-related key genes were screened out by taking interaction of DEGs, immune-related genes, and genes in hub module. Protein–protein interaction (PPI) analysis was used to further screen immune-related hub genes, followed by construction of a diagnostic model based on immune-related hub genes. Functional analysis and drug prediction of immune-related hub genes were, respectively, performed by David software and DGIdb database, followed by expression validation by reverse transcriptase polymerase chain reaction (RT-PCR).

Results

Totally, 93 immune-related key genes were identified between 561 DEGs, 1793 immune-related genes and 12,459 genes in the hub module of WGCNA. Through PPI analysis, a total of 5 diagnose and immune-related hub genes were further obtained, including IL7R, IL10, CD40LG, CD28 and LCN2. Relationship pairs between these 5 genes and immune cell were identified, including LCN2/IL7R/CD28-activated dendritic cell and IL10-immature B cell. Based on pharmacogenomics, 17 candidate drugs might interact with IL 10, including CYCLOSPORINE. Six candidate drugs might interact with CD28 and 11 with CD40LG, CD40LG and CD28 were drug targets of ALDESLEUKIN. Four significantly enriched signaling pathways were identified, such as T cell receptor signaling pathway, NF-kappa B signaling pathway and JAK-STAT signaling pathway.

Conclusion

The 5-gene diagnostic model could be used to diagnose and guide clinical immunotherapy for sepsis.

Keywords:

• sepsis
• diagnosis
• immune infiltration
• drug target
• WGCNA

Abbreviation

CD28, CD28 molecule; CD40LG, CD40 ligand; DT, Decision Tree; DEGs, differentially expressed genes; FDR, false discovery rate; FC, Fold change; GEO, Gene Expression Omnibus; GO, gene ontology; IL10, interleukin 10; IL7R, interleukin 7 receptor; KEGG, Kyoto Encyclopedia of Genes and Genomes; LCN2, lipocalin 2; PCA, principle component analysis; PPI, Protein–protein interaction; RF, Random Forest; ROC, receiver operating characteristic; ssGSEA, Single-sample gene set enrichment analysis; SVM, Support Vector Machine; WGCNA, Weighted gene co-expression network analysis.

Data Sharing Statement

All data generated or analyzed during this study are included in this article.

Ethics Approval and Informed Consent

The study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics committee of the General Hospital of Northern Theater Command PLA (Y2022-005). Additionally, all individuals provided the informed consent of the patients and their families.

Consent for Publication

The subjects gave written informed consent for the publication of any associated data and accompanying images.

Disclosure

All authors declare that they have no conflicts of interest for this work.

Additional information

Funding

This study was funded by Natural Fund Guiding Plan of Liaoning Province (2019-ZD-1054).