Research Progress on Sepsis Diagnosis and Monitoring Based on Omics Technologies: A Review

Abstract

Sepsis poses a significant global health burden, with millions of cases and high mortality rates annually, largely due to challenges in early diagnosis and monitoring. Traditional methods, reliant on nonspecific clinical manifestations and limited biomarkers like C-reactive protein and procalcitonin, often fail to distinguish infection from non-infectious inflammation or capture disease heterogeneity. This review synthesizes recent progress in omics technologies—genomics, transcriptomics, proteomics, and metabolomics—for advancing sepsis management. Genomics, via metagenomic next-generation sequencing, enables rapid pathogen identification and genetic variant analysis for susceptibility and prognosis. Transcriptomics reveals molecular subtypes and immune dynamics through RNA sequencing and single-cell approaches. Proteomics and metabolomics uncover protein and metabolite profiles linked to immune imbalance, organ damage, and metabolic disorders. Multi-omics integration, enhanced by artificial intelligence and machine learning, facilitates biomarker discovery, patient stratification, and predictive modeling, bridging laboratory findings to bedside applications like rapid diagnostic tools and clinical decision support systems. Despite advancements, challenges including data heterogeneity, high costs, and ethical concerns persist. Future directions emphasize single-cell and spatial omics, AI-driven personalization, and ethical frameworks to transform sepsis care from reactive to proactive, ultimately improving outcomes.