ArticleHereditas2022
ARG1 as a promising biomarker for sepsis diagnosis and prognosis: evidence from WGCNA and PPI network.
Article in Hereditas, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Article
- Identification of differentially expressed genes associated with tracheal injury recovery in a rabbit model of septic shock.BMC medical genomics · 2026Article
- Machine learning-based transcriptomic analysis identifies candidate genes in sepsis-induced coagulopathy and explores the immunomodulatory potential of baicalein.Human genomics · 2025Article
- Article
- Exploration of telomere-related biomarkers for lung adenocarcinoma and targeted drug prediction.Discover oncology · 2025Article
- Gene Expression Signatures of Porcine Bone Marrow-Derived Antigen-Presenting Cells Infected with Classical Swine Fever Virus.Viruses · 2025Article
- Parishin Protects Against Sepsis-Induced Intestinal Injury by Modulating the ACSL4/p-Smad3/PGC-1α Pathway: An Integrated Approach of Bioinformatics and Experimental Validation.Journal of inflammation research · 2025Article
- Identifying novel aging-related diagnostic and prognostic models and aging-targeted drugs for sepsis patients.Scientific reports · 2024Article
- Article
- Evidence from Machine Learning, Diagnostic Hub Genes in Sepsis and Diagnostic Models based on Xgboost Models, Novel Molecular Models for the Diagnosis of Sepsis.Current medicinal chemistry · 2024Article
- The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination.Frontiers in immunology · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSepsis is a life-threatening multi-organ dysfunction caused by the dysregulated host response to infection. Sepsis remains a major global concern with high mortality and morbidity, while management of sepsis patients relies heavily on early recognition and rapid stratification. This study aims to identify the crucial genes and biomarkers for sepsis which could guide clinicians to make rapid diagnosis and prognostication.
methodsPreliminary analysis of multiple global datasets, including 170 samples from patients with sepsis and 110 healthy control samples, revealed common differentially expressed genes (DEGs) in peripheral blood of patients with sepsis. After Gene Oncology (GO) and pathway analysis, the Weighted Gene Correlation Network Analysis (WGCNA) was used to screen for genes most related with clinical diagnosis. Also, the Protein-Protein Interaction Network (PPI Network) was constructed based on the DEGs and the hub genes were found. The results of WGCNA and PPI network were compared and one shared gene was discovered. Then more datasets of 728 experimental samples and 355 control samples were used to prove the diagnostic and prognostic value of this gene. Last, we used real-time PCR to confirm the bioinformatic results.
resultsFour hundred forty-four common differentially expressed genes in the blood of sepsis patients from different ethnicities were identified. Fifteen genes most related with clinical diagnosis were found by WGCNA, and 24 hub genes with most node degrees were identified by PPI network. ARG1 turned out to be the unique overlapped gene. Further analysis using more datasets showed that ARG1 was not only sharply up-regulated in sepsis than in healthy controls, but also significantly high-expressed in septic shock than in non-septic shock, significantly high-expressed in severe or lethal sepsis than in uncomplicated sepsis, and significantly high-expressed in non-responders than in responders upon early treatment. These all demonstrate the performance of ARG1 as a key biomarker. Last, the up-regulation of ARG1 in the blood was confirmed experimentally.
conclusionsWe identified crucial genes that may play significant roles in sepsis by WGCNA and PPI network. ARG1 was the only overlapped gene in both results and could be used to make an accurate diagnosis, discriminate the severity and predict the treatment response of sepsis.
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