ArticleFrontiers in medicine2022
Potential biomarkers for active renal involvement in systemic lupus erythematosus patients.
Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Unsupervised clustering of clinical and laboratory features of systemic lupus erythematosus: insights from a multicentre cohort.Lupus science & medicine · 2026Article
- Gene Expression Dysregulation in Whole Blood of Patients withInternational journal of molecular sciences · 2024Article
- Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis.American journal of physiology. Renal physiology · 2024Article
- Construction of a NETosis-related gene signature for predicting the prognostic status of sepsis patients.Heliyon · 2024Article
- Identification of hub genes and transcription factors in patients with primary gout complicated with atherosclerosis.Scientific reports · 2024Article
- Transcription Factors in the Pathogenesis of Lupus Nephritis and Their Targeted Therapy.International journal of molecular sciences · 2024Review
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to identify the key genes related to active renal involvement in patients with systemic lupus erythematosus (SLE). Methods: Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients with active renal involvement and those who did not have active renal involvement were identified by R software. Hub genes were identified using protein-protein interaction networks. The relationships between the expression levels of identified hub genes and SLEDAI were subjected to linear correlation analysis. The diagnostic accuracy of the hub genes was evaluated with the area under the curve of the receiver operating characteristic curve (ROC-AUC). Transcription factors (TFs) were predicted. The expression levels of different hub genes and histopathological patterns were also examined. Results: A total of 182 DEGs were identified. Enrichment analysis indicated that DEGs were primarily enriched in neutrophil degranulation, neutrophil activation involved in immune response and neutrophil activation. The expression levels of 12 identified hub genes were verified. Ten of the 12 hub genes were positively associated with SLEDAI. The combination model of DEFA4, CTSG, RETN, CEACAM8, TOP2A, LTF, MPO, ELANE, BIRC5, and LCN2 had a certain diagnostic accuracy in detecting renal involvement with high disease activity in SLE patients. The expressions of five predicted TFs were validated by GSE65391 dataset. Conclusion: This work explored the pathogenesis of renal involvement in SLE. These results may guide future experimental research and clinical transformation.
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