Tehran University of Medical Sciences Iranian Journal of Allergy, Asthma and Immunology 1735-1502 0 0 2026 04 16 1 13 Jun Zhang Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China Huijing Tong Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China Xiaojun Wang Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China Yingwei Ding Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China Linghong Xu Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China Gang Chen Department of Emergency, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China 2025 12 10 2026 01 27 Sepsis is a life-threatening systemic inflammatory response syndrome marked by high mortality and immune dysfunction. Histamine, synthesized from histidine, by histidine decarboxylase (HDC), regulates immune cell recruitment and inflammatory mediators, playing a key role in inflammatory diseases. The precise mechanisms and clinical significance of histamine in sepsis require further study. Gene expression data from the Gene Expression Omnibus (GEO) database were analyzed. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify differentially expressed histamine-related genes (DEHRGs). Machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF), were utilized to screen diagnostic genes, and a predictive model was constructed and validated using receiver operating characteristic analysis and decision curve analysis (DCA). Functional enrichment, immune infiltration assessment, using single-sample gene set enrichment analysis (ssGSEA), cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), regulatory network construction, and drug prediction were subsequently conducted. Nine DEHRGs were identified. Three key diagnostic genes-FYN, IL2RB, and MMP8-were selected and validated across multiple cohorts, showing high diagnostic accuracy (area under the curve [AUC]>0.85). The study revealed distinct immune patterns, including increased regulatory T cell (Treg) infiltration in the sepsis group. Two sepsis molecular subtypes with differential immune characteristics were also identified. This study systematically explored the association between histamine and sepsis pathogenesis, defining a three-gene diagnostic model and elucidating complex immune and molecular regulatory mechanisms. These findings offer new insights for developing targeted diagnostic and therapeutic strategies for sepsis. https://ijaai.tums.ac.ir/index.php/ijaai/article/view/4694 https://ijaai.tums.ac.ir/index.php/ijaai/article/download/4694/2323