ArticleEuropean journal of medical research2023
Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis.
Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 13 citations in OpenAlex.
- METTL7B Expression in Sepsis: Association With Disease Severity and 28-Day Mortality.Journal of clinical laboratory analysis · 2026Article
- Application of a machine learning model integrating T cell subsets and clinical markers in 28-Day mortality prediction of sepsis patients.Clinical and experimental medicine · 2026Article
- Umbilical cord blood cell transcriptional and methylation signatures at birth are associated with BPD development and chorioamnionitis: a pilot study.Scientific reports · 2026Article
- Umbilical Cord Blood Cell Transcriptional and Methylation Signatures at Birth Are Associated with BPD Development.bioRxiv : the preprint server for biology · 2025Article
- Shared immune biomarkers in necrotizing enterocolitis and neonatal sepsis identified via bioinformatics and machine learning.Scientific reports · 2025Article
- Pyroptosis-Related Genes as Prognostic Biomarkers and Immune Infiltration Features in Sepsis-Induced ARDS: A Single-Cell and Bulk RNA-Sequencing Analysis.Journal of inflammation research · 2025Article
- Comprehensive analysis of immunogenic cell death-related gene and construction of prediction model based on WGCNA and multiple machine learning in severe COVID-19.Scientific reports · 2024Article
- Article
- Application of Advanced Molecular Methods to Study Early-Onset Neonatal Sepsis.International journal of molecular sciences · 2024Review
- A practical predictive model to predict 30-day mortality in neonatal sepsis.Revista da Associacao Medica Brasileira (1992) · 2024Article
- Causal Relationships Between Leukocyte Subsets and Adverse Fetal Outcomes: A Mendelian Randomization Study.Mediators of inflammation · 2024Article
- Identification and validation of key biomarkers based on RNA methylation genes in sepsis.Frontiers in immunology · 2023Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundNeonatal 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.
resultsFifty-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.
conclusionsWe 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.
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