Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis

Abstract

Background Neonatal sepsis (NS), a life-threatening condition, is characterized by organ dysfunction and is the most common cause of neonatal death. However, the pathogenesis of NS is unclear and the clinical inflammatory markers currently used are not ideal for diagnosis of NS. Thus, exploring the link between immune responses in NS pathogenesis, elucidating the molecular mechanisms involved, and identifying potential therapeutic targets is of great significance in clinical practice. Herein, our study aimed to explore immune-related genes in NS and identify potential diagnostic biomarkers. Datasets for patients with NS and healthy controls were downloaded from the GEO database; GSE69686 and GSE25504 were used as the analysis and validation datasets, respectively. Differentially expressed genes (DEGs) were identified and Gene Set Enrichment Analysis (GSEA) was performed to determine their biological functions. Composition of immune cells was determined and immune-related genes (IRGs) between the two clusters were identified and their metabolic pathways were determined. Key genes with correlation coefficient > 0.5 and p < 0.05 were selected as screening biomarkers. Logistic regression models were constructed based on the selected biomarkers, and the diagnostic models were validated. Results Fifty-two DEGs were identified, and GSEA indicated involvement in acute inflammatory response, bacterial detection, and regulation of macrophage activation. Most infiltrating immune cells, including activated CD8 + T cells, were significantly different in patients with NS compared to the healthy controls. Fifty-four IRGs were identified, and GSEA indicated involvement in immune response and macrophage activation and regulation of T cell activation. Diagnostic models of DEGs containing five genes (PROS1, TDRD9, RETN, LOC728401, and METTL7B) and IRG with one gene (NSUN7) constructed using LASSO algorithm were validated using the GPL6947 and GPL13667 subset datasets, respectively. The IRG model outperformed the DEG model. Additionally, statistical analysis suggested that risk scores may be related to gestational age and birth weight, regardless of sex. Conclusions We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS. Our findings provide a new perspective for future research on NS pathogenesis.

PROS1 is a crucial gene in the macrophage efferocytosis of diabetic foot ulcers: a concerted analytical approach through the prisms of computer analysis

“…The expression of PROS1 shows a positive correlation with neutrophil count, activity, and oxidative burst, suggesting its potential as a therapeutic target for conditions like decompensated liver cirrhosis and sepsis [38]. PROS1 emerges as a promising targeted drug candidate for the treatment of inflammatory disorders, including spinal cord injury and ankylosing spondylitis [38]. In this study, PROS1 was found to be downregulated in the group with DFU, suggesting its potential as a protective factor against DFU.…”

“…When PROS1 is deficient, there is an increase in the expression of pro-inflammatory cytokines such as TNF-α and CCL3 [37]. The expression of PROS1 shows a positive correlation with neutrophil count, activity, and oxidative burst, suggesting its potential as a therapeutic target for conditions like decompensated liver cirrhosis and sepsis [38]. PROS1 emerges as a promising targeted drug candidate for the treatment of inflammatory disorders, including spinal cord injury and ankylosing spondylitis [38].…”

Comprehensive analysis of immunogenic cell death-related gene and construction of prediction model based on WGCNA and multiple machine learning in severe COVID-19

“…Another study reported that NSUN7 may be associated with an excessive inflammatory response in sepsis 40 . In addition, NSUN7 has been reported to be closely associated with immune and inflammatory responses and may be a biomarker for the pathogenesis of neonatal sepsis 41 . After SARS-CoV-2 infection, some severe patients will develop sepsis.…”

Identification and validation of key biomarkers based on RNA methylation genes in sepsis

“…NSUN7 , a member of the NSUN methyltransferase family, reduces protein activity and motility of sperms and is associated with male infertility ( 45 ). A recent study has reported that NSUN7 is up-regulated in neonatal sepsis, combined with bioinformatic analyses, NSUN7 is closely related to immune and inflammatory responses, implying its potential as a biomarker for the pathogenesis of neonatal sepsis ( 46 ). Consistently, we verified NSNU7 was highly expressed in adult septic patients compared to healthy controls.…”