Fei Li

Fei Li

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 May 2025 in Biomedicines
Verified
Journal Article
Open access
PDF file
ZGZhanyan Gao
Zhanyan Gao
YFYang Feng
Yang Feng
CZChenghui Zheng
Chenghui Zheng
FLFei Li
Fei Li
ZSZhan Sun
Zhan Sun
JLJun Liang
Jun Liang
Background: Systemic lupus erythematosus (SLE) is an immune-mediated disease with widespread involvement, and its pathogenesis remains incompletely understood. Recent studies suggest that modifications such as acetylation and lactylation play crucial roles in SLE progression, with potential interrelationships between them. This study aimed to identify biomarker genes co-associated with both lactylation and acetylation and to explore their potential mechanisms in SLE pathogenesis. Methods: Microarray data from peripheral blood mononuclear cells (PBMCs) of SLE patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. In the training dataset (GSE81622), differential expression analysis was performed to compare SLE samples with healthy controls. Lactate- and acetylation-related genes were used to identify differentially expressed lactate-related genes (LR-DEGs) and acetylation-related genes (AR-DEGs). Genes co-associated with both lactylation and acetylation were further examined. LASSO regression, support vector machine recursive feature elimination (SVM-RFE), and ROC curve analysis were used to identify hub genes. Immune infiltration analysis and a clinical nomogram model were developed for accurate diagnosis and treatment prediction. qPCR was used to validate the hub genes. Results: A total of 1181 differentially expressed genes (DEGs) were identified between SLE and healthy groups. Of these, 33 LR-DEGs and 28 AR-DEGs were identified. Seven genes were found to be co-associated with both lactylation and acetylation. Using LASSO and SVM-RFE, two hub genes, CDCA5 and MCTS1, were identified and validated in the GSE24706 dataset. ROC curve analysis and clinical nomogram revealed significant associations of these biomarkers with SLE pathogenesis. Conclusions: Our study identifies CDCA5 and MCTS1 as potential biomarkers for SLE, potentially influencing its pathogenesis through histone lactylation and acetylation. Experimental validation confirmed their differential expression between SLE patients and healthy controls. These findings underscore the role of epigenetic modifications in SLE, offering new insights into its regulatory mechanisms and immune interactions.