Two gene set variation indexes as potential diagnostic tool for sepsis

Area of Science:

• Genomics
• Biomarker Discovery
• Infectious Disease Research

Background:

• Accurate sepsis diagnosis is challenging, highlighting the need for novel diagnostic markers.
• Gene expression profiling offers a potential avenue for identifying sepsis-related molecular signatures.

Purpose of the Study:

• To identify crucial gene sets associated with sepsis by analyzing differentially expressed genes (DEGs) across multiple datasets.
• To develop and validate gene set variation analysis (GSVA) indexes derived from these gene sets as potential diagnostic markers for sepsis.

Main Methods:

• Screening of DEGs in sepsis versus non-sepsis blood samples from three public gene expression datasets.
• Identification of upregulated and downregulated crucial gene sets based on average functional similarity.
• Application of GSVA to generate indexes for each sample against the identified gene sets.

Main Results:

• Two crucial gene sets (upregulated and downregulated) were identified, comprising ten genes each.
• The derived GSVA indexes demonstrated robust diagnostic potential for sepsis, indicated by high area under the ROC curve.
• The diagnostic utility of the upregulated GSVA index was successfully validated in an independent dataset.

Conclusions:

• Two novel sepsis-related gene sets were proposed based on cross-dataset analysis.
• Two GSVA indexes were created, exhibiting promising diagnostic value for sepsis detection.
• The findings suggest that these GSVA indexes can serve as valuable tools for sepsis diagnosis.