AUTHOR=Vaquerizo-Villar Fernando , Hernandez-Beeftink Tamara , Heredia-Rodríguez María , Gómez-Sánchez Esther , Lorenzo-López Mario , López-Herrero Rocío , Bardaji-Carrillo Miguel , Tamayo-Velasco Álvaro , Martín-Fernández Marta , Sánchez-de-Prada Laura , Álvarez-Escudero Julián , Veiras Sonia , Baluja Aurora , Gonzalo-Benito Hugo , Martínez-Paz Pedro , García-Concejo Adrián , Fernández-Rodríguez Amanda , Jiménez-Sousa María A. , Resino Salvador , Martínez-Campelo Laura , Suárez-Pajés Eva , Quintela Inés , Cruz Raquel , Carracedo Ángel , Villar Jesús , Flores Carlos , Hornero Roberto , Tamayo Eduardo 

TITLE=Identifying sepsis susceptibility genes in post-surgical patients using an artificial intelligence approach

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1644800

DOI=10.3389/fmed.2025.1644800

ISSN=2296-858X

ABSTRACT=BackgroundEarly detection of sepsis is essential for its successful management. Although genome-wide association studies (GWAS) have shown potential in identifying sepsis-related genetic variants, they often involve heterogeneous patient groups and use single-locus analysis methods. Here, we aim to identify new sepsis susceptibility loci in post-surgical patients using an explainable artificial intelligence (XAI) approach applied to GWAS data.MethodsGWAS was performed in 750 post-operative patients with sepsis and 3,500 population controls. We applied a novel XAI-based methodology to GWAS-derived single nucleotide polymorphisms (SNPs) to predict sepsis and prioritize new genetic variants associated with post-operative sepsis susceptibility. We also assessed functional and enrichment effects using empirical data from integrated software tools and datasets, with the top-ranked variants and associated genes.ResultsOur XAI-GWAS approach showed a notable performance in predicting post-surgical sepsis and prioritized SNPs (such as rs17653532, rs1575081785, and rs74707084) with higher contribution to post-operative sepsis prediction. It also facilitated the discovery of post-operative sepsis risk loci with important functional implications related to gene expression regulation, DNA replication, cyclic nucleotide signaling, cell proliferation, and cardiac dysfunction.ConclusionThe combination of GWAS and XAI prioritized loci associated with post-operative sepsis susceptibility. The determination of key genes, such as PRIM2, SYNPR, and RBSN, through pre-operative blood tests could enhance risk stratification, enable early detection of post-operative sepsis, and guide targeted interventions to improve patient outcomes. Further research with additional and ethnically diverse cohorts comprising sepsis and non-sepsis patients undergoing major surgery is needed to validate these exploratory findings.