IL2RB affects Th1/Th2 and Th17 responses of peripheral blood mononuclear cells from septic patients

Identification of diagnostic candidate genes in COVID-19 patients with sepsis

PURPOSE

Coronavirus Disease 2019 (COVID-19) and sepsis are closely related. This study aims to identify pivotal diagnostic candidate genes in COVID-19 patients with sepsis.

PATIENTS AND METHODS

We obtained a COVID-19 data set and a sepsis data set from the Gene Expression Omnibus (GEO) database. Identification of differentially expressed genes (DEGs) and module genes using the Linear Models for Microarray Data (LIMMA) and weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (least absolute shrinkage and selection operator (LASSO) regression and Random Forest (RF)) were used to identify candidate hub genes for the diagnosis of COVID-19 patients with sepsis. Receiver operating characteristic (ROC) curves were developed to assess the diagnostic value. Finally, the data set GSE28750 was used to verify the core genes and analyze the immune infiltration.

RESULTS

The COVID-19 data set contained 3,438 DEGs， and 595 common genes were screened in sepsis. sepsis DEGs were mainly enriched in immune regulation. The intersection of DEGs for COVID-19 and core genes for sepsis was 329, which were also mainly enriched in the immune system. After developing the PPI network, 17 node genes were filtered and thirteen candidate hub genes were selected for diagnostic value evaluation using machine learning. All thirteen candidate hub genes have diagnostic value, and 8 genes with an Area Under the Curve (AUC) greater than 0.9 were selected as diagnostic genes.

CONCLUSION

Five core genes (CD3D, IL2RB, KLRC, CD5, and HLA-DQA1) associated with immune infiltration were identified to evaluate their diagnostic utility COVID-19 patients with sepsis. This finding contributes to the identification of potential peripheral blood diagnostic candidate genes for COVID-19 patients with sepsis.

Th1/Th2 cytokines in early peripheral blood of patients with multiple injuries and its predictive value for SIRS: A bioinformatic analysis

This study aims to evaluate the changes in helper T lymphocyte (Th)1/Th2 factor levels in peripheral blood of patients with severe multiple injuries and their prognostic value for nosocomial infection using bioinformatic analysis. The experimental group consisted of 180 patients with numerous injuries admitted to our hospital between January 2021 and June 2023, with 80 healthy volunteers serving as controls. Th1 cytokines (interleukin-2 and interferon-γ) and Th2 cytokines (IL-4 and IL-10) were evaluated 48 hours after admission using enzyme-linked immunosorbent assays. The experimental group was separated into two groups: those with systemic inflammatory response syndrome (SIRS) and those without SIRS, for cytokine analysis and SIRS incidence. Furthermore, the study examined Th1 and Th2 cytokine levels in trauma patients in various body locations within the experimental group. A receiver operating characteristic (ROC) curve analysis was performed to determine the predictive value of Th1/Th2 cytokines for SIRS incidence. The experimental group had lower IL-2 and IFN-γ levels compared to the control group, but greater levels of IL-4 and IL-10. There were no significant variations in Th1 and Th2 cytokine levels across the experimental groups. Patients with SIRS had lower levels of IL-2 and IFN-γ but greater levels of IL-4 and IL-10 compared to those without SIRS. Combined cytokine levels have a better predictive value for SIRS than individual cytokines alone. In conclusion, individuals with severe multiple injuries had a change from Th1 to Th2 cytokine profiles, which was most evident in those with SIRS. The combined cytokine levels had a substantial predictive value for SIRS incidence in this patient cohort.

CXCL9, IL2RB, and SPP1, potential diagnostic biomarkers in the co-morbidity pattern of atherosclerosis and non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) is a hepatocyte inflammation based on hepatocellular steatosis, yet there is no effective drug treatment. Atherosclerosis (AS) is caused by lipid deposition in the endothelium, which can lead to various cardiovascular diseases. NASH and AS share common risk factors, and NASH can also elevate the risk of AS, causing a higher morbidity and mortality rate for atherosclerotic heart disease. Therefore, timely detection and diagnosis of NASH and AS are particularly important. In this study, differential gene expression analysis and weighted gene co-expression network analysis were performed on the AS (GSE100927) and NASH (GSE89632) datasets to obtain common crosstalk genes, respectively. Then, candidate Hub genes were screened using four topological algorithms and externally validated in the GSE43292 and GSE63067 datasets to obtain Hub genes. Furthermore, immune infiltration analysis and gene set variation analysis were performed on the Hub genes to explore the underlying mechanisms. The DGIbd database was used to screen candidate drugs for AS and NASH. Finally, a NASH model was constructed using free fatty acid-induced human L02 cells, an AS model was constructed using lipopolysaccharide-induced HUVECs, and a co-morbidity model was constructed using L02 cells and HUVECs to verify Hub gene expression. The result showed that a total of 113 genes common to both AS and NASH were identified as crosstalk genes, and enrichment analysis indicated that these genes were mainly involved in the regulation of immune and metabolism-related pathways. 28 candidate Hub genes were screened according to four topological algorithms, and CXCL9, IL2RB, and SPP1 were identified as Hub genes after in vitro experiments and external dataset validation. The ROC curves and SVM modeling demonstrated the good diagnostic efficacy of these three Hub genes. In addition, the Hub genes are strongly associated with immune cell infiltration, especially macrophages and γ-δ T cell infiltration. Finally, five potential therapeutic drugs were identified. has-miR-185 and hsa-miR-335 were closely related to AS and NASH. This study demonstrates that CXCL9, IL2RB, and SPP1 may serve as potential biomarkers for the diagnosis of the co-morbidity patterns of AS and NASH and as potential targets for drug therapy.

Inflammation and Neurodegeneration in Glaucoma: Isolated Eye Disease or a Part of a Systemic Disorder? - Serum Proteomic Analysis

Introduction

Glaucoma is the most common optic neuropathy and the leading cause of irreversible blindness worldwide, which affects 3.54% of the population aged 40-80 years. Despite numerous published studies, some aspects of glaucoma pathogenesis, serum biomarkers, and their potential link with other diseases remain unclear. Recent articles have proposed that autoimmune, oxidative stress and inflammation may be involved in the pathogenesis of glaucoma.

Methods

We investigated the serum expression of 92 inflammatory and neurotrophic factors in glaucoma patients. The study group consisted of 26 glaucoma patients and 192 healthy subjects based on digital fundography.

Results

Patients with glaucoma had significantly lower serum expression of IL-2Rβ, TWEAK, CX3CL1, CD6, CD5, LAP TGF-beta1, LIF-R, TRAIL, NT-3, and CCL23 and significantly higher expression of IL-22Rα1.

Conclusion

Our results indicate that patients with glaucoma tend to have lower levels of neuroprotective proteins and higher levels of neuroinflammatory proteins, similar to those observed in psychiatric, neurodegenerative and autoimmune diseases, indicating a potential link between these conditions and glaucoma pathogenesis.