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pmid:36117534

Screening of potential key ferroptosis-related genes in sepsis.

Shunan Cui · Kun Niu · Yining Xie · Shuo Li · Wenzhi Zhu · Ling Yu · Hongyu Tan

PeerJ · 2022 doi:10.7717/peerj.13983

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pmid:36117534
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title
Screening of potential key ferroptosis-related genes in sepsis.
doi
10.7717/peerj.13983
pmid
36117534
authors array · 7 items
[0]
Shunan Cui
[1]
Kun Niu
[2]
Yining Xie
[3]
Shuo Li
[4]
Wenzhi Zhu
[5]
Ling Yu
[6]
Hongyu Tan
journal
PeerJ
year
2022
abstract
Background: Sepsis leads to multiple organ dysfunction caused by a dysregulated host response to infection with a high incidence and mortality. The effect of ferroptosis on the development of sepsis remains unclear. In this study, we aimed to identify the key ferroptosis-related genes involved in sepsis and further explore the potential biological functions of these ferroptosis-related genes in sepsis using bioinformatics analysis. Methods: The GSE13904 (from children) and GSE28750 (from adults) datasets were downloaded from the Gene Expression Omnibus (GEO). The ferroptosis-related genes were obtained from the FerrDb database. The ferroptosis-related differentially expressed genes (DEGs) were screened by the limma R package. The DAVID online database or clusterProfiler R package was used for the functional enrichment analysis. Then, the STRING database was used to predict the interactions of proteins, and the CytoHubba plugin of Cytoscape was used to confirm key clustering modules. Then, the miRNAs and lncRNAs associated with the key clustering modules were predicted by miRWalk 2.0 and LncBase v.2 respectively. Finally, we generated a cecal ligation and puncture (CLP) polymicrobial sepsis model in C57 male mice and examined the expression of the mRNAs and noncoding RNAs of interest in peripheral blood leukocytes by PCR during the acute inflammation phase. Results: In total, 34 ferroptosis-related DEGs were identified in both adult and pediatric septic patients. These ferroptosis-related DEGs were mainly enriched in inflammatory pathways. Then, a significant clustering module containing eight genes was identified. Among them, the following five genes were closely associated with the MAPK signaling pathway: MAPK14, MAPK8, DUSP1, MAP3K5 and MAPK1. Then, crucial miRNAs and lncRNAs associated with biomarker MAPK-related genes were also identified. In particular, let-7b-5p and NEAT1 were selected as noncoding RNAs of interest because of their correlation with ferroptosis in previous studies. Finally, we examined the mRNAs, miRNAs and lncRNAs of interest using CLP-induced sepsis in peripheral blood leukocytes of mice. The results showed that MAPK14, MAPK8, MAP3K5, MAPK1 and NEAT1 were upregulated, while DUSP1 and let-7b-5p were downregulated in the CLP group compared with the sham group. Conclusions: The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis. This study provides a valuable resource for future studies investigating the mechanism of MAPK-related ferroptosis in sepsis.
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The ferroptosis-related DEGs were identified using the limma R package (version 3.42.2) based on |log2 (fold-change)| > 0.5 and adjusted p value < 0.05
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sections[4] "Differential ferroptosis-related gene expression" paragraph 2
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The ferroptosis-related DEGs were identified using the limma R package (version 3.42.2) based on |log2 (fold-change)| > 0.5 and adjusted p value < 0.05
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The following information was supplied regarding data availability:The raw measurements are available in the Supplemental Files.
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The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis.
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The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis.
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The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis.
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Expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum
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PMID 36117534 full text
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The ferroptosis-related DEGs were identified using the limma R package (version 3.42.2) based on |log2 (fold-change)| > 0.5 and adjusted p value < 0.05
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36117534", "kind": "science-record", "revision": 5, "content_hash": "sha256:707dfa85d0639d63f09eba74bffaee9a51bce4be6b95cc2b1f0f099bba19027e", "created_at": "2026-11-01T18:15:22Z", "updated_at": "2026-11-01T22:50:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening of potential key ferroptosis-related genes in sepsis.", "doi": "10.7717/peerj.13983", "pmid": "36117534", "authors": ["Shunan Cui", "Kun Niu", "Yining Xie", "Shuo Li", "Wenzhi Zhu", "Ling Yu", "Hongyu Tan"], "journal": "PeerJ", "year": 2022, "abstract": "Background: Sepsis leads to multiple organ dysfunction caused by a dysregulated host response to infection with a high incidence and mortality. The effect of ferroptosis on the development of sepsis remains unclear. In this study, we aimed to identify the key ferroptosis-related genes involved in sepsis and further explore the potential biological functions of these ferroptosis-related genes in sepsis using bioinformatics analysis.\nMethods: The GSE13904 (from children) and GSE28750 (from adults) datasets were downloaded from the Gene Expression Omnibus (GEO). The ferroptosis-related genes were obtained from the FerrDb database. The ferroptosis-related differentially expressed genes (DEGs) were screened by the limma R package. The DAVID online database or clusterProfiler R package was used for the functional enrichment analysis. Then, the STRING database was used to predict the interactions of proteins, and the CytoHubba plugin of Cytoscape was used to confirm key clustering modules. Then, the miRNAs and lncRNAs associated with the key clustering modules were predicted by miRWalk 2.0 and LncBase v.2 respectively. Finally, we generated a cecal ligation and puncture (CLP) polymicrobial sepsis model in C57 male mice and examined the expression of the mRNAs and noncoding RNAs of interest in peripheral blood leukocytes by PCR during the acute inflammation phase.\nResults: In total, 34 ferroptosis-related DEGs were identified in both adult and pediatric septic patients. These ferroptosis-related DEGs were mainly enriched in inflammatory pathways. Then, a significant clustering module containing eight genes was identified. Among them, the following five genes were closely associated with the MAPK signaling pathway: MAPK14, MAPK8, DUSP1, MAP3K5 and MAPK1. Then, crucial miRNAs and lncRNAs associated with biomarker MAPK-related genes were also identified. In particular, let-7b-5p and NEAT1 were selected as noncoding RNAs of interest because of their correlation with ferroptosis in previous studies. Finally, we examined the mRNAs, miRNAs and lncRNAs of interest using CLP-induced sepsis in peripheral blood leukocytes of mice. The results showed that MAPK14, MAPK8, MAP3K5, MAPK1 and NEAT1 were upregulated, while DUSP1 and let-7b-5p were downregulated in the CLP group compared with the sham group.\nConclusions: The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis. This study provides a valuable resource for future studies investigating the mechanism of MAPK-related ferroptosis in sepsis.", "claims": [{"id": "claim-method", "statement": "The ferroptosis-related DEGs were identified using the limma R package (version 3.42.2) based on |log2 (fold-change)| > 0.5 and adjusted p value < 0.05", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36117534", "locator": "sections[4] \"Differential ferroptosis-related gene expression\" paragraph 2", "quote": "The ferroptosis-related DEGs were identified using the limma R package (version 3.42.2) based on |log2 (fold-change)| > 0.5 and adjusted p value < 0.05"}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The raw measurements are available in the Supplemental Files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36117534", "locator": "sections[26] \"Data Availability\" paragraph 2", "quote": "The following information was supplied regarding data availability:The raw measurements are available in the Supplemental Files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36117534", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36117534"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13904"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13904"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36117534", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.13983", "sha256": 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