Work

Risk assessment with gene expression markers in sepsis development

Year: 2024

Type: article

Abstract: Infection is a commonplace, self-limiting condition, which in some cases lead to sepsis. We investigated the individual phenotypic predisposition to developing sepsis in a large cohort of noninfected patients undergoing major elective surgery. Whole blood RNA sequencing analysis was performed on preoperative samples taken from 267 patients. These comprised patients who developed postoperatively infection with (n=69) or without (n=57) organ dysfunction, noninfectious systemic inflammatory response (n=47), or an uncomplicated postoperative course (n=94). Machine learning classification models built on preoperative transcriptomic signatures predicted postoperative outcome including sepsis with area under the curve values of up to 0.889 (mean 0.830) and sensitivity/specificity up to 0.857/0.856 (mean 0.801/0.804). Our models, further confirmed with qPCR analysis, potentially offer a risk prediction tool of sepsis development in the clinic. Funding Information: GP would like to thank the Area of Excellence of the Hong Kong Research Council, “Institute of Metabolic Medicine”, (5/2019-4/2027); Hong Kong, China. Declaration of Interests: MS grants from NewB, Apollo Therapeutics and UCL Technology Fund, others from Abbott, Amormed, Biomerieux, Biotest, Deltex Medical, Fresenius, Mindray, NewB, Pfizer, Radiometer, Roche Diagnostics, Safeguard Biosystems, Shionogi and Spiden outside of this project. MS is an 17 unpaid advisor to PreSymptom Health Ltd, Hemotune, deepUll, and Santersus and RL is a part-time advisor to PreSymptom Health Ltd. All other authors declare no competing interests. Ethics Approval Statement: This was a sub-study of the study ESCAPE which has been approved National Ethics Committee of Greece (approval 30/20) and by the National Organization for Medicines of Greece (approval IS 021-20). Sampling was done before treatment with any biological disease-modifying drug or with corticosteroids (EudraCT number 2020-001039-29; Clinicaltrials.gov NCT04339712).

Source: Cell Reports Medicine

DOI: 10.1016/j.xcrm.2024.101712