Population scale proteomics enables adaptive digital twin modelling in sepsis

Sepsis is one of the leading causes of mortality in the world. Currently, the heterogeneity of sepsis makes it challenging to determine the molecular mechanisms that define the syndrome. Here, we leverage population scale proteomics to analyze a well-defined cohort of 1364 blood samples taken at time-of-admission to the emergency department from patients suspected of sepsis. We identified panels of proteins using explainable artificial intelligence that predict clinical outcomes and applied these panels to reduce high-dimensional proteomics data to a low-dimensional interpretable latent space (ILS). Using the ILS, we constructed an adaptive digital twin model that accurately predicted organ dysfunction, mortality, and early-mortality-risk patients using only data available at time-of-admission. In addition to being highly effective for investigating sepsis, this approach supports the flexible incorporation of new data and can generalize to other diseases to aid in translational research and the development of precision medicine. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement L.M. is funded by the Swedish Research Council (grant number VR-2020-02419), the Wallenberg foundation (grant number 2016.0023) and Alfred Österlunds Foundation. J.M. is a Wallenberg academy fellow (KAW 2017.0271) and is also funded by the Swedish Research Council (Vetenskapsrådet, VR) (2019-01646 and 2018-05795), the Wallenberg foundation (KAW2016.0023, KAW2019.0353 and KAW2020.0299), and Alfred Österlunds Foundation. E.M. is funded by Wenner-Gren Foundation (FT2020-0003), the Crafoord Foundation, and the Swedish Society of Medicine (SLS-985287). F.K. is funded by Region Skåne ALF project and the Crafoord Foundation. A.L. is funded by the Swedish Research Council VR 2023-02707 and Region Skåne ALF project 2022-0146. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval for the study was obtained from the Swedish National Ethics Committee (file numbers 2022-01454-01, 2014/741 and 2016/271). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data produced in the present study are available upon reasonable request to the authors