Precision in the storm Host response dysregulation as a guide for prognosis and targeted therapies in pneumonia and sepsis

The overall objective of this thesis is to advance the field of immunomodulation in sepsis, pneumonia, and COVID-19 by aiding in the transition from clinical severity-based approaches to host response-based precision medicine using advanced (machine-learning) statistics and multi-omics. To address this, the thesis is organized into three key parts, each examining critical challenges identified in the introduction. Part I exemplifies the potential benefits of focusing on host response dysregulation and how to facilitate such a paradigm shift. Part II evaluates the impact of an increasingly relevant global factor: ageing populations and its potential implications for the effectiveness of immunomodulatory therapies. Finally, Part III investigates host response alterations underpinning adverse outcomes at multiple stages of disease progression: in pneumonia and COVID-19 before and during established sepsis. By employing multi-omics, including (cellular) transcriptomics and (cellular and plasma) proteomics, this chapter seeks to uncover actionable pathways that drive clinical deterioration and mortality and proposes novel research and therapeutic opportunities for early and potentially life-saving interventions.