Identification and validation of an endotoxin tolerance–based prognostic model with therapeutic insights in sepsis

TL;DR

A new gene-based model predicts sepsis mortality risk by tracking immune suppression linked to endotoxin tolerance, validated with clinical and molecular data.

Contribution

A novel endotoxin tolerance-related gene signature and age-integrated nomogram for sepsis mortality prediction with experimental and computational validation.

Findings

The 10-gene ETG signature showed AUCs of 0.73–0.78 for 28-day mortality prediction.

Non-survivors had lower FCGR1A, TLR5, and CX3CR1 mRNA and protein levels in PBMCs.

CX3CR1, FCGR1A, and TLR5 were identified as druggable targets with potential ligands.

Abstract

Sepsis outcomes remain difficult to predict because immune trajectories are heterogeneous and dynamically shift from early activation to immunosuppression. Endotoxin tolerance (ET) in circulating monocytes/macrophages is a key mechanism of sepsis-associated immunosuppression but has not been systematically leveraged for prognostication. We sought to develop and clinically validate an ET-related gene (ETG) signature for short-term mortality risk stratification.

Public whole-blood transcriptomic datasets were intersected with curated ET gene sets to derive ETG candidates. An ensemble machine-learning framework (108 model/feature-selection combinations across 12 algorithms) was used to build and rank prognostic models for 28-day mortality; the final parsimonious signature (10 ETGs, including IL4R, ATM, CX3CR1, FCGR1A) informed a risk score. A two-variable nomogram (age + ETG risk score) was constructed. Internal performance was assessed by bootstrapped calibration, time-dependent ROC/AUC at 7, 14, and 28 days, and Harrell’s C-index. Experimental validation used a prospective ICU cohort (n=50; 13 survivors, 37 non-survivors). PBMCs were profiled by RT-qPCR and Western blot; CD14+ monocytes were analyzed by flow cytometry for FCGR1A/CD64, CX3CR1, and PD-1. We further explored regulatory context (ceRNA network) and druggability (DGIdb query and molecular docking to CX3CR1, FCGR1A, and TLR5).

The 10-gene ETG signature stratified mortality risk with acceptable discrimination and calibration. AUCs were 0.76 (95% CI 0.69–0.83), 0.78 (0.72–0.83), and 0.73 (0.67–0.78) at 7, 14, and 28 days, respectively; Harrell’s C-index was 0.782. The age-integrated nomogram showed close agreement between predicted and observed survival across timepoints. Functional enrichment indicated immune-response pathways enriched in the low-risk group. In the clinical cohort, non-survivors exhibited lower mRNA and protein levels of FCGR1A, TLR5, and CX3CR1 in PBMCs; flow cytometry revealed reduced proportions of FCGR1A+, CX3CR1+, and PD-1+ CD14+ monocytes (p<0.01). The ceRNA analysis highlighted a putative NEAT1/miR-1287-5p/CX3CR1 axis. Docking suggested plausible ligandability of CX3CR1, FCGR1A, and TLR5, nominating candidates such as valproic acid and CGP-52608 for follow-up testing.

An ET-anchored, 10-gene signature captures a clinically relevant axis of sepsis-associated immunosuppression and enables short-term mortality risk stratification. Integration with age yields a simple nomogram with stable internal performance. Multilayer validation (transcript, protein, single-cell) supports biological plausibility. Prospective multicenter studies with richer clinical annotation and functional assays are warranted to confirm generalizability and to evaluate ET-guided immunomodulatory strategies.

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