ArticleFrontiers in immunology2023
Identification of NETs-related biomarkers and molecular clusters in systemic lupus erythematosus.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 44 citations in OpenAlex.
- PTGS2/COX-2 is associated with neurovascular and blood-brain barrier changes in behaviourally classified MRL/lpr mice.Lupus science & medicine · 2026Article
- Neutrophils as critical orchestrators of chronic inflammation.Cellular & molecular immunology · 2026Review
- Neutrophil extracellular traps in the animal model of adenine-induced chronic kidney disease.PloS one · 2026Article
- Neutrophil Extracellular Traps (NETs) in health and disease.Molecular biomedicine · 2025Review
- Neutrophil extracellular traps in tumor metastasis: mechanisms, and therapeutic implications.Discover oncology · 2025Review
- Integrated bioinformatics and validation reveal TMEM45A in systemic lupus erythematosus regulating atrial fibrosis in atrial fibrillation.Molecular medicine (Cambridge, Mass.) · 2025Article
- Identification biomarkers and therapeutic targets of disulfidptosis-related in rheumatoid arthritis via bioinformatics, molecular dynamics simulation, and experimental validation.Scientific reports · 2025Article
- Neutrophil extracellular traps in tumor metabolism and microenvironment.Biomarker research · 2025Review
- Machine learning-driven discovery of NETs-associated diagnostic biomarkers and molecular subtypes in tuberculosis.Frontiers in cellular and infection microbiology · 2025Article
- Article
- Biomarkers for systemic lupus erythematosus: A scoping review.Immunity, inflammation and disease · 2024Article
- Systemic lupus in the era of machine learning medicine.Lupus science & medicine · 2024Review
- Extracellular Traps in Patients Diagnosed With Bacterial Vaginosis, Trichomoniasis, Candidiasis, Noninfectious Vaginitis and Cytolytic Vaginosis.International journal of microbiology · 2024Article
- Identification of m6A-Related Biomarkers in Systemic Lupus Erythematosus: A Bioinformation-Based Analysis.Journal of inflammation research · 2024Article
- Comprehensive analysis of IRF8-related genes and immune characteristics in lupus nephritis.Frontiers in pharmacology · 2024Article
- Decoding the mitochondrial connection: development and validation of biomarkers for classifying and treating systemic lupus erythematosus through bioinformatics and machine learning.BMC rheumatology · 2023Article
- Role of exosome-mediated molecules SNORD91A and SLC40A1 in M2 macrophage polarization and prognosis of ESCC.Discover oncology · 2023Article
- Elucidating the role of T-cell exhaustion-related genes in colorectal cancer: a single-cell bioinformatics perspective.Functional & integrative genomics · 2023Article
- The impact of the Hedgehog signal pathway on the tumor immune microenvironment of gastric adenocarcinoma by integrated analysis of scRNA-seq and RNA-seq datasets.Functional & integrative genomics · 2023Article
- The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma.Discover oncology · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neutrophil extracellular traps (NETs) is an important process involved in the pathogenesis of systemic lupus erythematosus (SLE), but the potential mechanisms of NETs contributing to SLE at the genetic level have not been clearly investigated. This investigation aimed to explore the molecular characteristics of NETs-related genes (NRGs) in SLE based on bioinformatics analysis, and identify associated reliable biomarkers and molecular clusters. Dataset GSE45291 was acquired from the Gene Expression Omnibus repository and used as a training set for subsequent analysis. A total of 1006 differentially expressed genes (DEGs) were obtained, most of which were associated with multiple viral infections. The interaction of DEGs with NRGs revealed 8 differentially expressed NRGs (DE-NRGs). The correlation and protein-protein interaction analyses of these DE-NRGs were performed. Among them, HMGB1, ITGB2, and CREB5 were selected as hub genes by random forest, support vector machine, and least absolute shrinkage and selection operator algorithms. The significant diagnostic value for SLE was confirmed in the training set and three validation sets (GSE81622, GSE61635, and GSE122459). Additionally, three NETs-related sub-clusters were identified based on the hub genes' expression profiles analyzed by unsupervised consensus cluster assessment. Functional enrichment was performed among the three NETs subgroups, and the data revealed that cluster 1 highly expressed DEGs were prevalent in innate immune response pathways while that of cluster 3 were enriched in adaptive immune response pathways. Moreover, immune infiltration analysis also revealed that innate immune cells were markedly infiltrated in cluster 1 while the adaptive immune cells were upregulated in cluster 3. As per our knowledge, this investigation is the first to explore the molecular characteristics of NRGs in SLE, identify three potential biomarkers (HMGB1, ITGB2, and CREB5), and three distinct clusters based on these hub biomarkers.
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