Development of a prognostic model for sepsis based on gut microbiota-associated genes and identification of potential targets

TL;DR

This study develops a prognostic model for sepsis based on gut microbiota-related genes and identifies RORA as a potential therapeutic target influenced by gut microbiota metabolites.

Contribution

The novel GMGscore model and identification of RORA as a key target in gut microbiota-sepsis interactions.

Findings

The GMGscore model, based on six genes, showed strong prognostic performance with high AUC values in both training and validation datasets.

RORA was identified as a key gut microbiota-related gene, downregulated in sepsis and associated with immune cell infiltration.

Molecular docking revealed stable interactions between RORA and metabolites from Collinsella, suggesting a potential mechanism for gut microbiota influence on sepsis.

Abstract

Gut microbiota dysbiosis drives sepsis progression by impairing intestinal barrier function and exacerbating systemic inflammation, but the microbiota-host-immune interaction mechanisms remain unclear.

We integrated transcriptomic and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between sepsis patients and healthy controls were identified in GSE154918, then intersected with 248 gut microbiota-related genes from the GutMGene database to obtain candidate genes. A prognostic model named GMGscore was constructed via LASSO-Cox regression in GSE65682 and validated in GSE95233. Area under the curve (AUC) was used to evaluate the model performance. The expression of gut microbiota-related genes was validated in peripheral blood samples obtained from patients with sepsis through RT-qPCR. Furthermore, scRNA-seq data (GSE167363) was used to determine the cellular localization of key genes. Molecular docking predicted interactions between gut microbiota metabolites and the key target.

We identified 34 gut microbiota-related DEGs, which were enriched in pathways like inflammatory bowel disease and IL-17 signaling. The GMGscore, based on 6 genes (CYP1A2, FFAR2, IL4R, MUC1, RORA, ASPM), showed excellent prognostic performance (AUC = 0.903 in training set; AUC = 0.901 in validation set). High GMGscore correlated with poor survival, upregulated neutrophil degranulation and reduced neutrophils. RORA was identified as a key gut microbiota-related target, which was consistently downregulated in sepsis with the highest diagnostic AUC across datasets, mainly expressed in effector T cells and NK cells, and positively correlated with CD8 + T cell/NK cell infiltration (R = 0.419 and 0.352, respectively). Virtual knockout of RORA downregulated cytotoxic genes. Molecular docking showed stable binding of RORA with Collinsella-derived metabolites (Citric acid, Sedoheptulose, and Tricarballylic acid).

The GMGscore is a robust prognostic tool for sepsis. RORA, targeted by gut microbiota metabolites, may regulate immune balance via effector T cells and NK cells. These findings advance understanding of gut microbiota-sepsis crosstalk and provide new avenues for precise prognosis and targeted therapy.

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