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Despite its importance, the transcriptomic regulation of ferroptosis in human sepsis has not been systematically characterised. Here, we present a comprehensive integrative analysis, combining 17 transcriptomic data sets from previously published studies involving blood samples from septic patients and healthy controls, encompassing microarray, bulk RNA sequencing, and single-cell RNA sequencing platforms. Our findings reveal that ferroptosis-related gene regulation intensifies with disease progression and is markedly more pronounced in adults. Single-cell analysis identified monocytes as the primary regulators of ferroptosis in peripheral blood during sepsis. Eleven core ferroptosis-related genes (\n                    <jats:italic toggle=\"yes\">ACSL1<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">ALOX5<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">CAPG<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">CREB5<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">MAPK14<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">MGST1<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">MICU1<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">QSOX1<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">SAT1<\/jats:italic>\n                    ,\n                    <jats:italic toggle=\"yes\">SIAH2<\/jats:italic>\n                    , and\n                    <jats:italic toggle=\"yes\">SLC2A3<\/jats:italic>\n                    ) were consistently upregulated, serving as robust candidates for sepsis biomarkers, while additional genes correlated with disease severity, suggesting prognostic value. This large-scale integrative approach provides novel molecular insights into sepsis pathophysiology and identifies promising targets for improved diagnosis and therapy.\n                  <\/jats:p>","DOI":"10.1177\/11779322261447645","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T02:36:38Z","timestamp":1789526198000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Unravelling Ferroptosis in Sepsis: A Comprehensive Integrative Transcriptomic Analysis Across Age and Disease Severity"],"prefix":"10.1177","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0499-4254","authenticated-orcid":false,"given":"Miguel Victor Bringel","family":"Sales","sequence":"first","affiliation":[{"name":"N\u00facleo de Biologia Experimental, Universidade de Fortaleza (UNIFOR), Fortaleza, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helder Imoto","family":"Nakaya","sequence":"additional","affiliation":[{"name":"Hospital Israelita Albert Einstein, S\u00e3o Paulo, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fernando de Queiroz","family":"Cunha","sequence":"additional","affiliation":[{"name":"Center for Research in Inflammatory Diseases (CRID), Department of Pharmacology, Ribeir\u00e3o Preto Medical School, University of S\u00e3o Paulo (USP), S\u00e3o Paulo, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8783-9009","authenticated-orcid":false,"given":"Antonio Edson Rocha","family":"Oliveira","sequence":"additional","affiliation":[{"name":"N\u00facleo de Biologia Experimental, Universidade de Fortaleza (UNIFOR), Fortaleza, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(18)30696-2"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000005337"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/5786182"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1111\/cpr.13644"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41568-022-00459-0"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.956361"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1097\/01.shk.0000079425.52617.db"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1097\/SHK.0b013e3181c0f068"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2025.1528986"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00011-023-01849-2"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2022.940261"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12890-023-02361-3"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/30.1.207"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1101\/2023.07.13.548886"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm254"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg405"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv007"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btn647"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","unstructured":"Prada C Lima D Nakaya H. 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