Expression and diagnostic values of ferroptosis-related genes in coronavirus-associated viral sepsis

Abstract

Aim: The aim of this study is to investigate the differential expression and diagnostic value of ferroptosis-related genes in coronavirus-associated viral sepsis.

Methods: This study was conducted in two sequential phases: (1) identification of differentially expressed genes through comprehensive analysis of the experimental dataset (GSE164805); and (2) clinical validation of the candidate molecular markers using both test set samples and clinical samples, followed by rigorous evaluation of their diagnostic performance. Firstly, the microchips associated with coronavirus-associated viral sepsis were retrieved from the GEO database, a public data platform of NCBI (National Center for Biotechnology Information), and differentially expressed genes (DEGs) were obtained through differential analysis. The identified DEGs were then intersected with the ferroptosis gene dataset to obtain ferroptosis-related DEGs. Subsequently, molecular signaling pathways of ferroptosis-related genes in coronavirus-associated viral sepsis were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. CIBERSORT was employed to analyze immune cell infiltration in both the coronavirus-associated viral sepsis group and control group. Furthermore, a protein-protein interaction (PPI) network was constructed to identify hub genes involved in ferroptosis. Finally, the expression of ferroptosis hub genes in coronavirus-associated viral sepsis and its diagnostic value were analyzed in validation set GSE199816 and clinical case samples.

Results: In test set GSE164805, a total of 15,059 differentially expressed genes (DEGs) were identified, comprising 7,458 up-regulated and 7,601 down-regulated genes. Subsequently, an intersection analysis with the ferroptosis gene dataset yielded 189 DEGs associated with ferroptosis. Functional enrichment analyses using GO and KEGG revealed significant enrichment in signaling pathways related to ferroptosis, oxidative stress, and HIF-1. Additionally, CIBERSORT immune-infiltration analysis revealed enhanced infiltration of innate immune cells but reduced infiltration of CD8⁺ T cells and natural killer (NK) cells in the coronavirus-associated viral sepsis group compared with healthy controls. Furthermore, analysis identified that the distribution of these immune cells correlated with the expression levels of IL1-β and HMOX1, suggesting that viral infection in the septic pathological state disrupts the balance between immune activation and suppression. Notably, PPI network analysis also identified IL1-β and HMOX1 as hub genes involved in ferroptosis. Finally, the results were verified in the validation set and clinical case samples, and the results showed that the expressions of IL1-β and HMOX1 in the coronavirus-associated viral sepsis group were decreased compared with the case control group and the healthy control group. In clinical samples, the expression levels were as follows: IL1-β (0.390 ± 0.068 vs. 1.101 ± 0.107), HMOX1 (0.629 ± 0.117 vs. 1.101 ± 0.107), and the differences were statistically significant (all p < 0.05). Further diagnostic performance analysis demonstrated that IL1-β and HMOX1 exhibited AUROCs of 0.892 and 0.765, respectively, indicating their robust diagnostic potential for coronavirus-associated viral sepsis.

Conclusion: The present study has successfully identified two hub genes, IL1-β and HMOX1, associated with ferroptosis in coronavirus-associated viral sepsis, and their expression and diagnostic value for the disease. These findings provide effective diagnostic biomarkers and potential therapeutic targets for coronavirus-associated viral sepsis. Notably, this study specifically focused on coronavirus-induced viral sepsis, distinct from previously characterized bacterial sepsis and other viral etiologies, thus warranting future studies with expanded sample sizes for stratified analyses.

Keywords: HMOX1; IL1-β; coronavirus; ferroptosis; viral sepsis.

Figure 1

Overview of differentially expressed genes in coronavirus-associated viral sepsis. (A) Volcano plot of DEGs in coronavirus-associated viral sepsis from the GSE164805 dataset. Blue dots represent downregulated DEGs, red dots indicate upregulated DEGs, and gray dots denote genes without significant differential expression. (B) Heatmap of DEGs in coronavirus-associated viral sepsis from the GSE164805 dataset, displaying expression patterns of filtered DEGs (|log2FC| > 1, p < 0.05) across sample groups. Rows correspond to genes and columns represent samples, with red indicating high expression and blue low expression. Hierarchical clustering demonstrates distinct expression profiles between the viral sepsis group (left, n = 5) and healthy controls (right, n = 5), further validating intergroup transcriptional divergence.

Figure 2

Intersection of differentially expressed genes (DEGs) in the GSE164805 and ferroptosis genes. The count on the left (14,870 genes) refers to DEGs unique to GSE164805; the count in the middle (189 genes) refers to ferroptosis-related DEGs; and the count on the right (375 genes) refers to unique to ferroptosis genes.

Figure 3

Enrichment analysis of ferroptosis-related DEGs. (A) Top 10 GO (gene ontology) biological processes pathway. (B) Top 10 GO cellular component pathway. (C) Top 10 GO molecular function pathway. (D) Top 10 KEGG pathway.

Figure 4

Differential expression of different types of immune cell marker expression between viral sepsis and controls.

Figure 5

Correlation analysis between immune cell infiltration and gene expression profiles.

Figure 6

Protein–protein interaction (PPI) network of ferroptosis DEGs. Subnetwork of hub genes from the PPI network. Node colors reflect differential connectivity degrees, with red indicating higher interaction connectivity and yellow representing lower connectivity.

Figure 7

Validation analysis of key genes in the validation cohort. (A) Volcano plot of differentially expressed genes (DEGs) between the viral sepsis group and pathological control group in the GSE199816 dataset. Key ferroptosis-related genes (IL1B and HMOX1) are labeled, both showing decreased expression in the viral sepsis group. (B) Receiver operating characteristic (ROC) curve of IL1B for diagnosing viral sepsis. (C) ROC curve of HMOX1 for diagnosing viral sepsis.

Figure 8

Differential expression of IL1-β and HMOX1 in viral sepsis versus healthy controls. Box plots depict mRNA levels of IL1-β (A) and HMOX1 (B) in the viral sepsis group (n = 20) and healthy controls (n = 20).

Figure 9

Diagnostic performance analysis of key genes in viral sepsis patients. (A) Receiver Operating Characteristic (ROC) curve of IL1-β for diagnosing viral sepsis. (B) ROC curve of HMOX1 for diagnosing viral sepsis.