Intestinal Microenvironment Dynamics and Sepsis-Associated Encephalopathy Pathophysiology: Insights from Multi-Omics Profiling

舟兴 张¹Wen Bo Xu²Fuli Gu²Yue Chen Zhang³Wei Hu¹Shao Song Xi^4*

• ¹Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou, China
• ²The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
• ³Zhejiang University School of Medicine Sir Run Run Shaw Hospital, Hangzhou, China
• ⁴Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China

Background. Sepsis-associated encephalopathy (SAE), a devastating complication of sepsis, lacks specific biomarkers and clear pathophysiological understanding, particularly regarding the gut-brain axis. While gut dysbiosis is implicated in SAE, the underlying mechanisms remain elusive. Methods. This study employed an integrated multiomics approach (16S rDNA and fecal miRNA sequencing) to dissect the gut microenvironment in SAE patients (n=10) compared to sepsis patients without encephalopathy (SP, n=20). Results. Although α-and β-diversity indices showed no significant differences, distinct compositional shifts in the gut microbiota were observed in SAE patients, characterized by increased abundance of Neisseria, Haemophilus, Lautropia, Enterococcus, Parabacteroides, and decreased Fusobacterium, Phocaeicola, Bacteroides, among others. Concurrently, 12 fecal miRNAs were differentially expressed (DE) in SAE, with 11 upregulated (e.g., miR-106a-5p, miR-181a-5p, miR-223-5p, miR-30e-3p) and 1 downregulated (miR-222-3p). Crucially, correlation network analysis revealed significant interactions between 10 DE miRNAs and 15 bacterial genera, establishing a complex gut microbiota-miRNA interplay in SAE. Machine learning (LASSO and elastic net regression) identified miR-30e-3p and miR-223-5p as the most promising combined diagnostic biomarkers, achieving an area under the curve (AUC) of 0.893. Functional exploration via ceRNA network analysis indicated miR-30e-3p targets inflammation and apoptosis-related genes (e.g., IL1B, RPS6KB1, AKT1), while miR-223-5p primarily targets immune-regulatory genes (e.g., IGF1, AR). Experimental validation confirmed significantly elevated serum IL-1β levels in SAE patients (p<0.001), supporting the predicted inflammatory pathway. Conclusions. This study provides the first evidence of a fecal miRNA-gut microbiota interaction network in SAE pathogenesis, highlighting miR-30e-3p and miR-223-5p as pivotal mediators and potential diagnostic/therapeutic targets.