Sepsis is globally recognized as a primary contributor to morbidity and mortality. The Sepsis 3.0 definition is captured as ‘a life-threatening organ dysfunction caused by a dysregulated host response to infection’. Timely identification of sepsis and immune dysregulation could optimize both clinical interventions and outcomes. However, quantifying immune cell-related biomarkers and correlating omics features is too specialized and time-consuming to be widely utilized. Assessing the morphological changes in immune cells is a novel diagnostic method that quantifies the state of immune activation by using a small amount of whole blood in less than 10 minutes. Morphological characteristics can be analyzed in multiple dimensions, including extracellular, intracellular, and nuclear features, that occur during sepsis and its evolution. The morphological features of sepsis-related immune cells can profile the immune response, identify homogeneous subgroups with clinical and laboratory features, and assist in exploring immunological therapy to improve treatment responses and outcomes.

Exploration of the biophysical changes in immune cells might be a promising and sensitive tool for the rapid diagnosis and risk stratification of sepsis, which could enhance the prediction, treatment, and patient outcomes of sepsis. First, we need to elucidate the morphological properties of immunecells in multiple dimensions (intracellular, extracellular, and cell nucleus) during sepsis development, evolution, and treatment. This process involves the utilization of diverse methodologies such as flow cytometry for assessing cell quantities and types, molecular techniques like PCR and sequencing to understand gene expression alterations, and microscopy for observing physical transformations in cells. These comprehensive analyses play a crucial role in evaluating patient treatment responses, predicting disease progression, and determining prognosis. Then, it is essential to combine other related promising biomarkers or basic functional information with clinical data to enable early diagnosis and subtyping of sepsis by using statistical, machine learning, or deep learning methods. Lastly, our ultimate objective is to optimize potential new drug targets for sepsis immunotherapy, including personalized medicine approaches for sepsis patients. Overall, this topic aims to identify the surveillance and morphological properties of immune dysfunction for early detection and classification of sepsis, explore promising immuno-therapeutic targets, construct precise models and medicine approaches to predict treatment response, and optimize clinical outcomes.

In this research topic, there are several questions that need to be addressed:

• Elucidating the morphological properties of immune cells for early sepsis detection and tracing its evolution.
• Exploring the relationship between morphological properties and other multidimensional insights (genes, omics, epigenetics, morphology, function) from immune cells and endothelial cells, as well as the interplay between inflammatory reactions, cytokines, and complement products.
• Investigating multidimensional combinations of immune dysregulations and clinical big data to unravel sepsis endotypes and predictive models by using statistical, machine learning, or deep learning methods.
• Discovering promising immuno-therapeutic targets and personalized medicine based on individual immune and clinical characteristics of patients.

This research topic welcomes a variety of article types in various forms, including but not limited to Original Research, Review, Mini Review, Brief Research Report, and Perspective.

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Frontiers in Pharmacology

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