ArticleOpen life sciences2023
Identification of iron metabolism-related genes as diagnostic signatures in sepsis by blood transcriptomic analysis.
Article in Open life sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- The Diagnostic Utility of Host RNA Biosignatures in Adult Patients With Sepsis: A Systematic Review and Meta-Analysis.Critical care explorations · 2025Pooled it
- Large-scale analysis of temporal gene expression variation in peripheral blood.Nature communications · 2026Article
- Emerging roles of lipocalin-2-mediated neuroimmune interactions in chronic pain and itch.Frontiers in pharmacology · 2026Review
- Cytochrome P450 (CYP) 1 enzymes in acute lung injury: from molecular insights to therapeutic implications.Redox report : communications in free radical research · 2025Review
- UropathogenicInternational journal of molecular sciences · 2025Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Iron metabolism is considered to play the principal role in sepsis, but the key iron metabolism-related genetic signatures are unclear. In this study, we analyzed and identified the genetic signatures related to the iron-metabolism in sepsis by using a bioinformatics analysis of four transcriptomic datasets from the GEO database. A total of 21 differentially expressed iron metabolism-related signatures were identified including 9 transporters, 8 enzymes, and 4 regulatory factors. Among them, lipocalin 2 was found to have the highest diagnostic value as its expression showed significant differences in all the comparisons including sepsis vs healthy controls, sepsis vs non-sepsis diseases, and mild forms vs severe forms of sepsis. Besides, the cytochrome P450 gene CYP1B1 also showed diagnostic values for sepsis from the non-sepsis diseases. The CYP4V2, LTF, and GCLM showed diagnostic values for distinguishing the severe forms from mild forms of sepsis. Our analysis identified 21 sepsis-associated iron metabolism-related genetic signatures, which may represent diagnostic and therapeutic biomarkers of sepsis, and will improve our understanding of the molecular mechanism underlying the occurrence of sepsis.
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Registered trials
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