# Intestinal microenvironment dynamics and Sepsis-associated encephalopathy pathophysiology: insights from multi-omics profiling

**Authors:** Zhou Xing Zhang, Wen Bo Xu, Fu Li Gu, Yue Chen Zhang, Wei Hu, Shao Song Xi

PMC · DOI: 10.3389/fneur.2025.1724644 · Frontiers in Neurology · 2026-01-26

## TL;DR

This study explores how gut microbiota and miRNAs interact in sepsis-associated encephalopathy, identifying potential biomarkers for diagnosis and treatment.

## Contribution

The study is the first to reveal a fecal miRNA-gut microbiota interaction network in SAE pathogenesis.

## Key findings

- SAE patients show distinct gut microbiota shifts with increased Neisseria and decreased Fusobacterium.
- Twelve fecal miRNAs are differentially expressed in SAE, with miR-30e-3p and miR-223-5p identified as key diagnostic biomarkers.
- miR-30e-3p and miR-223-5p target inflammation and immune-regulatory genes, with elevated IL-1β levels in SAE patients.

## Abstract

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.

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).

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.

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.

## Linked entities

- **Genes:** IL1B (interleukin 1 beta) [NCBI Gene 3553], RPS6KB1 (ribosomal protein S6 kinase B1) [NCBI Gene 6198], AKT1 (AKT serine/threonine kinase 1) [NCBI Gene 207], IGF1 (insulin like growth factor 1) [NCBI Gene 3479], AR (androgen receptor) [NCBI Gene 367]

## Full-text entities

- **Genes:** RPS6KB1 (ribosomal protein S6 kinase B1) [NCBI Gene 6198] {aka PS6K, S6K, S6K-beta-1, S6K1, STK14A, p70 S6KA}, IGF1 (insulin like growth factor 1) [NCBI Gene 3479] {aka IGF, IGF-I, IGFI, MGF}, AKT1 (AKT serine/threonine kinase 1) [NCBI Gene 207] {aka AKT, PKB, PKB-ALPHA, PRKBA, RAC, RAC-ALPHA}, IL1B (interleukin 1 beta) [NCBI Gene 3553] {aka IL-1, IL1-BETA, IL1F2, IL1beta}
- **Diseases:** inflammation (MESH:D007249), encephalopathy (MESH:D001927), SAE (MESH:D065166), gut dysbiosis (MESH:D064806), Sepsis (MESH:D018805)
- **Species:** Homo sapiens (human, species) [taxon 9606], Bacteroides (genus) [taxon 816], Fusobacterium (genus) [taxon 848], Parabacteroides (genus) [taxon 375288], Enterococcus (genus) [taxon 1350], Haemophilus (genus) [taxon 724], Neisseria (genus) [taxon 482]

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12884059/full.md

## References

52 references — full list in the complete paper: https://tomesphere.com/paper/PMC12884059/full.md

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Source: https://tomesphere.com/paper/PMC12884059