Metabolic Biomarkers and Endotypes as Predictors of Sepsis Outcomes: A Prospective Population-Based Cohort Analysis from the UK Biobank

Abstract Background Understanding the impact of population metabolic landscapes on susceptibility and outcomes of sepsis is crucial for guiding clinical consultations. This study explores the relationship between plasma metabolites and the incidence and mortality of sepsis among affected populations. Methods The analysis utilized data from the UK Biobank community study, which involved Nuclear Magnetic Resonance (NMR) spectroscopy of 118,461 baseline plasma samples generated by Nightingale Health, up to December 31, 2013. Risk factors were identified through multivariate logistic regression analysis. Finally, principal component analysis was used to determine the major influencing factors. The data analysis period was from October 1, 2023, to December 1, 2023. Cox regression analysis was conducted to produce adjusted hazard ratios (HR) for the relationships between individual metabolic biomarkers and 11 principal components of metabolic biomarkers (which together explained 90% of the total variance in individual biomarkers) and their association with the incidence and mortality of sepsis. Results A total of 106,533 participants were included in the primary analysis (average age 60.67 years and 96% Caucasian). Total 3,486 cases of sepsis as defined by the study were identified, and among these, 635 instances of sepsis-related mortality occurred. The results showed that lipid and related lipoprotein (HR from 0.89 to 0.95), albumin (HR, 0.87 ,95% (confidence interval) CI, 0.84–0.90) are protective factors for the incident sepsis after adjusted for age, sex, ethnicity, qualifications, socio-economic status, chronic diseases. Metabolites of glycolysis, lipolysis and inflammation are risk factors for the sepsis incident and death. Subgroup analyses conducted on age, gender, and C-reactive protein levels, along with the reanalysis excluding the first two years of follow-up results, demonstrated robust findings. Overall, 13 metabolic biomarker PCs were independently associated with incidence sepsis. addition of PCs to an established risk prediction model, improved incidence sepsis (from 0.737 95% CI: 0.729, 0.744] to 0.792 (95% CI: 0.774, 0.807). Findings from this cohort study suggest that certain metabolic endotype: lower lipid and albumin levels, higher glycolysis, lipolysis, inflammatory plasma metabolites may be associated with an increased risk of sepsis and higher mortality.