Research question:
Can we identify genomic, transcriptomic, or proteomic signatures among participants of the UK Biobank that are predicitive of episodes of infection/sepsis?
Objective:
We aim to identify these signatures and assess their associations with future infectious episodes in the short (<12 months), middle (1-3 years) and long (4-10 years) term. Also, we intend to correlate them with available clinical outcomes.
Rationale:
Sepsis, a life-threatening immune response to infection, remains a major cause of morbidity and mortality. Survivors often face recurrent infections, prolonging hospital stays and worsening outcomes. Identifying genomic, transcriptomic, and proteomic markers of infection susceptibility could improve patient stratification and treatment.
Sepsis heterogeneity complicates risk assessment. Traditional biomarkers (CRP, PCT) lack specificity for predicting recurrence, whereas multiomic approaches offer promise. Genetic factors, including SNPs in immune-related genes (TLRs, cytokines), influence sepsis susceptibility (Rautanen et al. 2015). WGS and GWAS can identify variants linked to recurrence. Proteomic analysis reveals immune dysfunction, with biomarkers like PD-L1 and interleukins implicated in prognosis. (Chen et al. 2023).
Sepsis-induced immunosuppression increases infection risk post-recovery. Omics-based markers, such as reduced HLA-DR on monocytes, can identify high-risk patients. Long-term immune dysregulation and epigenetic changes may sustain infection susceptibility. Integrating multiomic data can enhance clinical decision-making, reduce morbidity, and improve survival. Future research should focus on validation and clinical implementation.