{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["16"],"submitter":["Yang L"],"pubmed_abstract":["Sepsis is a life-threatening condition caused by a dysregulated immune response, often leading to organ failure and death. Diagnosis and therapy remain challenging. This study aimed to identify biomarkers for sepsis through multi-omics analysis and experimental validation. A total of 1,166 samples from the GEO repository underwent differential analysis, WGCNA, and logistic regression to identify sepsis-associated features. After SVM-RFE screening, a 28-gene signature distinguishing sepsis from healthy controls achieved an AUC of 0.970 (sensitivity 0.939, specificity 1.000) in an independent cohort and 0.870 (sensitivity 0.906, specificity 0.700) in qRT-PCR validation. A 13-gene signature distinguishing sepsis from SIRS achieved an AUC of 1.000 (sensitivity 1.000, specificity 1.000) and 0.7"],"journal":["Frontiers in immunology"],"pagination":["1611348"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12852012"],"repository":["biostudies-literature"],"pubmed_title":["Multi-omics machine learning identifies diagnostic gene signatures and functionally supports PRKACB involvement in macrophage inflammatory responses in sepsis."],"pmcid":["PMC12852012"],"pubmed_authors":["Qian W","Yang L","Teng S","Ma Z","Han C"],"additional_accession":[]},"is_claimable":false,"name":"Multi-omics machine learning identifies diagnostic gene signatures and functionally supports PRKACB involvement in macrophage inflammatory responses in sepsis.","description":"Sepsis is a life-threatening condition caused by a dysregulated immune response, often leading to organ failure and death. Diagnosis and therapy remain challenging. This study aimed to identify biomarkers for sepsis through multi-omics analysis and experimental validation. A total of 1,166 samples from the GEO repository underwent differential analysis, WGCNA, and logistic regression to identify sepsis-associated features. After SVM-RFE screening, a 28-gene signature distinguishing sepsis from healthy controls achieved an AUC of 0.970 (sensitivity 0.939, specificity 1.000) in an independent cohort and 0.870 (sensitivity 0.906, specificity 0.700) in qRT-PCR validation. A 13-gene signature distinguishing sepsis from SIRS achieved an AUC of 1.000 (sensitivity 1.000, specificity 1.000) and 0.7","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-18T05:50:12.631Z","creation":"2026-06-18T03:07:47.835Z"},"accession":"S-EPMC12852012","cross_references":{"pubmed":["41624837"],"doi":["10.3389/fimmu.2025.1611348"]}}