ArticleMedicina oral, patologia oral y cirugia bucal2024
Identification of ferroptosis-related diagnostic markers in primary Sjögren's syndrome based on machine learning.
Article in Medicina oral, patologia oral y cirugia bucal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Ferroptosis in salivary gland disorders: mechanisms, biomarkers, and therapeutic perspectives.Apoptosis : an international journal on programmed cell death · 2026Review
- From subjective assessment to data-driven diagnosis: the AI revolution in multimodal early detection of Sjögren's disease.Frontiers in immunology · 2026Review
- Ferroptosis and organelle roles in dry eye.iScience · 2025Review
- Enhanced co-expression of TIGIT and PD-1 on γδ T cells correlates with clinical features and laboratory parameters in patients with primary Sjögren's syndrome.Clinical rheumatology · 2025Article
- Advances in research on immunocyte iron metabolism, ferroptosis, and their regulatory roles in autoimmune and autoinflammatory diseases.Cell death & disease · 2024Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrimary Sjogren's syndrome (pSS) is a common autoimmune disorder that affects up to 0.3-3% of the global population. Ferroptosis has recently been identified to play a significant role in autoimmune diseases. However, the molecular mechanisms of ferroptosis in the initiation and progression of pSS remains unclear. MATERIAL AND
methodsTo investigate the molecular mechanisms underlying the occurrence and progression of pSS, we utilized a comprehensive approach by integrating data obtained from the Gene Expression Omnibus (GEO) database with data from the FerrDb database to identify the ferroptosis-related differentially expressed genes (DEGs). Furthermore, we implemented an innovative transcriptomic analysis method utilizing a computer-aided algorithm to establish a network between hub genes associated with ferroptosis and the immune microenvironment in pSS patients.
resultsOur results revealed significant differences in the gene expression profiles of pSS samples compared to normal tissues, with 1,830 significantly up-regulated genes and 1,310 significantly down-regulated genes. In addition, our results showed a significant increase in the proportions of B cells and CD4+ T cells in pSS samples compared to normal tissues. AND then, our analysis revealed that a combination of six ferroptosis-related genes, including TBK1, SLC1A4, PIK3CA, ENO3, EGR1, and ATG5, could serve as optimal markers for the diagnosis of pSS. The combined analysis of these six genes accurately diagnosed the occurrence of pSS.
conclusionsThis study offers valuable insights into the pathogenesis of pSS and highlights the importance of targeting ferroptosis-related DEGs, which suggests a novel treatment strategy for pSS.
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