Journal Article

Exploring ENPP5 as a diagnostic biomarker for sepsis: a comprehensive bioinformatics analysis

Wei, Cailing, Yang, Shixiong, Huang, Aichun, Liu, Ningmei, Huang, Jinping, Chen, Jieling, Li, Yanjun, Gao, Jiamin, Lu, Yibo

2025

Overview

Background The rising mortality rates in sepsis highlight the current lack of reliable therapeutic biomarkers. This study aims to identify markers associated with biological functions to offer new strategies for sepsis diagnosis. Methods We conducted differential expression analysis to identify differentially expressed messenger RNAs (DEmRs), long non-coding RNA (DElncRs), and microRNAs (DEmiRs) in sepsis compared to healthy controls. Enrichment analysis was performed using DEmRs, and a lncRNA-miRNA-mRNA competing endogenous RNA network was constructed. Least absolute shrinkage and selection operator (LASSO) and random forest models were applied to identify diagnostic mRNAs. The optimal diagnostic model was determined through decision curve analysis, resulting in the identification of seven hub genes. The key gene, determined by its highest importance and the largest area under the receiver operating characteristics curve (AUC) value, was further validated. Additionally, we analyzed the correlation of the key gene with microenvironment cell infiltration and immune genes. Results A total of 4,450 intersected DEmRs (GSE66099, GSE13904, GSE154918, GSE8121) that were significantly involved in the cell cycle. We obtained 13 mRNAs, and further screened seven hub genes, including PPARD, ZSCAN2, ABI2, ENPP5, FMNL3, CD3E, and CAMK4. Subsequently, ENPP5 was as the key gene based on importance and AUC value. Moreover, Neutrophil cells and macrophages had a high abundance in sepsis patients. ENPP5 was positively associated with T cells but negatively associated with mast cells. Conclusion ENPP5, identified as a key gene, exhibits significant associations with immune cell infiltration and immune-related genes. This suggests its potential role as a biomarker for novel therapeutic strategies in sepsis.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Anopheles / Antibiotics / Bioinformatics / Biological markers / Biomarker / Biomarkers / Biomarkers - blood / Cell cycle / China / Clinical outcomes / Comparative analysis / Competing endogenous RNA / Computational Biology - methods / Correlation analysis / Datasets / Decision trees / Diagnosis / ENPP5 / Gene expression / Gene Expression Profiling / Gene Regulatory Networks / Genes / Genetic aspects / Health aspects / Humans / Identification and classification / Immune cell infiltration / Immune response / Immune system / Infection / Infectious Diseases / Infiltration / Internal Medicine / Leukocytes / Leukocytes (neutrophilic) / Lymphocytes / Lymphocytes T / Macrophages / Mast cells / Medical diagnosis / Medical Microbiology / Medical research / Medicine / Medicine & Public Health / Medicine, Experimental / Messenger RNA / Microenvironments / MicroRNA / MicroRNAs / MicroRNAs - genetics / miRNA / Mortality / mRNA / Neutrophils / Operators (mathematics) / Parasitology / Patients / Performance evaluation / Ribonucleic acid / RNA / RNA, Long Noncoding - genetics / RNA, Messenger - genetics / ROC Curve / Sepsis / Sepsis - diagnosis / Sepsis - genetics / T cells / Taiwan / Tropical Medicine