Targeting the host response in sepsis: current approaches and future evidence

Abstract

Sepsis, a dysregulated host response to infection characterized by organ failure, is one of the leading causes of death worldwide. Disbalances of the immune response play an important role in its pathophysiology. Patients may develop simultaneously or concomitantly states of systemic or local hyperinflammation and immunosuppression. Although a variety of effective immunomodulatory treatments are generally available, attempts to inhibit or stimulate the immune system in sepsis have failed so far to improve patients' outcome. The underlying reason is likely multifaceted including failure to identify responders to a specific immune intervention and the complex pathophysiology of organ dysfunction that is not exclusively caused by immunopathology but also includes dysfunction of the coagulation system, parenchymal organs, and the endothelium. Increasing evidence suggests that stratification of the heterogeneous population of septic patients with consideration of their host response might led to treatments that are more effective. The purpose of this review is to provide an overview of current studies aimed at optimizing the many facets of host response and to discuss future perspectives for precision medicine approaches in sepsis.

Keywords: Biomarkers; Clinical studies; Disease tolerance; Immunomodulation; Immunosuppression; Immunotherapy; Personalized medicine; Precision medicine; Septic shock.

Fig. 1

Model of sepsis-induced immune responses. This extended model of sepsis-induced immune responses describes the host inflammatory response before, during, and after sepsis. Infection modifies the innate and adaptive immune response for sustained periods of time, even long after clinical recovery. The immune response in sepsis is highly personalized and contingent upon the patient's immune status when infection occurs. This status is influenced by various factors including age, comorbidities, environmental elements, and the microbiome. Moreover, each patient exhibits a highly intricate combination of genetic variations and epigenetic alterations, rendering their immune system a virtually unique selection of genes responsible for cytokines and mediators that regulate immune responses. Excessive inflammation is triggered by the release of pro-inflammatory mediators by various cell types upon detecting pathogen-associated molecular patterns (PAMPs). Simultaneously, the activation of the complement system, the vascular endothelium, and the coagulation system results in microcirculatory disturbances. These processes are exacerbated by the release of damage-associated molecular patterns (DAMPs) as a consequence of tissue damage, the discharge of neutrophil extracellular traps (NETosis), and inflammatory cell death (pyroptosis). Immune suppression can develop at various time points and is characterized by the secretion of anti-inflammatory cytokines, the apoptosis of T cells, B cells, and dendritic cells, T cell exhaustion, and the proliferation of anti-inflammatory immune cells like regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). Immune suppression is further intensified by decreased expression of human leukocyte antigen–antigen D related (HLA-DR) and heightened expression of programmed cell death 1 (PD-1) and its corresponding ligand (PD-L1). Post sepsis, the immune response can return to pre-sepsis status; however, many sepsis survivors later succumb to secondary infections, chronic critical illness, post-sepsis syndrome, and post-intensive care syndrome (PICS), severely impacting quality of life. A persistent sepsis-induced immune dysfunction can eventually lead to long-term death

Fig. 2

Vascular endothelial dysfunction in the pathogenesis of septic organ injury. The vascular endothelium plays a crucial role in inflammation, immunothrombosis, and vascular barrier integrity. During sepsis, the activation of a highly complex inflammatory cascade by pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) triggers the production of pro-inflammatory, proapoptotic, and procoagulant mediators by both immune cells and vascular endothelial cells (ECs). Toll-like receptor (TLR) signaling causes nuclear translocation of transcription factor NF-kb, leading to a deleterious cytokine release syndrome. The luminal surface of the vascular endothelium is lined by the endothelial glycocalyx (eGC), a gel-like carbohydrate-rich structure. In sepsis, heparanase-1 (HPA-1) activity is upregulated inducing degradation of the eGC. Glycocalyx shedding exposes embedded adhesion molecules such as intracellular adhesion molecule-1 (ICAM-1) and vascular adhesion molecule-1 (VCAM-1) which both enable leukocyte rolling, adhesion, and transmigration. Loss of the eGC, junctional disassembly, and EC apoptosis result in capillary barrier dysfunction, increased permeability, and interstitial tissue edema. Besides amplifying the inflammatory host response, ECs also promote a prothrombotic state leading to microvascular clotting and frequently disseminated intravascular coagulation (DIC). A lack of cleavage of von Willebrand factor (VWF) due to reduced levels of a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13) contributes to the accumulation of ultra-large VWF (ULVWF) multimers facilitating platelet adhesion to injured endothelium. The upregulation of tissue factor which initiates extrinsic coagulation and plasminogen activator inhibitor 1 (PAI-1), the main inhibitor of fibrinolysis, further augments the process of sepsis-induced immunothrombosis

Fig. 3

Overview of the potential research pathway leading from data to the identification of functional endotypes. First, clinical and biological data have to be collected in the framework of observational cohorts or randomized controlled trials. Critical relevance lies in the collection of samples that allow the implementation of high-throughput biological analyses in a second step. Optimally data from multiple databases are bundled in order to allow a robust subphenotype discovery. In a third step, data are fed into an unsupervised machine learning pipeline, which hopefully identifies clusters of patients in the given multi-dimensional variable constellation. These clusters or subphenotypes have then to be validated in an external prospective cohort, and optimally, a parsimonious model is then elaborated that allows identification of subphenotypes at the bedside with a minimal number of variables. Finally, and as the ultimate goal of phenotyping, a biological correlate or ideally, a treatable trait, is identified for each subphenotype, which can be targeted by means of a specific medication, leading to the transition from a subphenotype to a functional endotype