Sepsis: deriving biological meaning and clinical applications from high-dimensional data

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

The Plasma Lipidomic Landscape in Patients with Sepsis due to Community-acquired Pneumonia

Rationale: The plasma lipidome has the potential to reflect many facets of the host status during severe infection. Previous work is limited to specific lipid groups or was focused on lipids as prognosticators.Objectives: To map the plasma lipidome during sepsis due to community-acquired pneumonia (CAP) and determine the disease specificity and associations with clinical features.Methods: We analyzed 1,833 lipid species across 33 classes in 169 patients admitted to the ICU with sepsis due to CAP, 51 noninfected ICU patients, and 48 outpatient controls. In a paired analysis, we reanalyzed patients still in the ICU 4 days after admission (n = 82).Measurements and Main Results: A total of 58% of plasma lipids were significantly lower in patients with CAP-attributable sepsis compared with outpatient controls (6% higher, 36% not different). We found strong lipid class-specific associations with disease severity, validated across two external cohorts, and inflammatory biomarkers, in which triacylglycerols, cholesterol esters, and lysophospholipids exhibited the strongest associations. A total of 36% of lipids increased over time, and stratification by survival revealed diverging lipid recovery, which was confirmed in an external cohort; specifically, a 10% increase in cholesterol ester levels was related to a lower odds ratio (0.84; P = 0.006) for 30-day mortality (absolute mortality, 18 of 82). Comparison with noninfected ICU patients delineated a substantial common illness response (57.5%) and a distinct lipidomic signal for patients with CAP-attributable sepsis (37%).Conclusions: Patients with sepsis due to CAP exhibit a time-dependent and partially disease-specific shift in their plasma lipidome that correlates with disease severity and systemic inflammation and is associated with higher mortality.

A New Strategy for Targeting UCP2 to Modulate Glycolytic Reprogramming as a Treatment for Sepsis A New Strategy for Targeting UCP2

Sepsis is a severe and life-threatening disease caused by infection, characterized by a dysregulated immune response. Unfortunately, effective treatment strategies for sepsis are still lacking. The intricate interplay between metabolism and the immune system limits the treatment options for sepsis. During sepsis, there is a profound shift in cellular energy metabolism, which triggers a metabolic reprogramming of immune cells. This metabolic alteration impairs immune responses, giving rise to excessive inflammation and immune suppression. Recent research has demonstrated that UCP2 not only serves as a critical target in sepsis but also functions as a key metabolic switch involved in immune cell-mediated inflammatory responses. However, the regulatory mechanisms underlying this modulation are complex. This article focuses on UCP2 as a target and discusses metabolic reprogramming during sepsis and the complex regulatory mechanisms between different stages of inflammation. Our research indicates that overexpression of UCP2 reduces the Warburg effect, restores mitochondrial function, and improves the prognosis of sepsis. This discovery aims to provide a promising approach to address the significant challenges associated with metabolic dysfunction and immune paralysis.

Clinical practice of sepsis-induced immunosuppression: Current immunotherapy and future options

Sepsis is a potentially fatal condition characterized by the failure of one or more organs due to a disordered host response to infection. The development of sepsis is closely linked to immune dysfunction. As a result, immunotherapy has gained traction as a promising approach to sepsis treatment, as it holds the potential to reverse immunosuppression and restore immune balance, thereby improving the prognosis of septic patients. However, due to the highly heterogeneous nature of sepsis, it is crucial to carefully select the appropriate patient population for immunotherapy. This review summarizes the current and evolved treatments for sepsis-induced immunosuppression to enhance clinicians' understanding and practical application of immunotherapy in the management of sepsis.

Analysis of comprehensive biomolecules in critically ill patients via bioinformatics technologies

Each patient with a critical illness such as sepsis and severe trauma has a different genetic background, comorbidities, age, and sex. Moreover, pathophysiology changes dynamically over time even in the same patient. Therefore, individualized treatment is necessary to account for heterogeneity in patient backgrounds. Recently, the analysis of comprehensive biomolecular information using clinical specimens has revealed novel molecular pathological classifications called subtypes. In addition, comprehensive biomolecular information using clinical specimens has enabled reverse translational research, which is a data-driven approach to the identification of drug target molecules. The development of these methods is expected to visualize the heterogeneity of patient backgrounds and lead to personalized therapy.

A pharmacoproteomic landscape of organotypic intervention responses in Gram-negative sepsis

Sepsis is the major cause of mortality across intensive care units globally, yet details of accompanying pathological molecular events remain unclear. This knowledge gap has resulted in ineffective biomarker development and suboptimal treatment regimens to prevent and manage organ dysfunction/damage. Here, we used pharmacoproteomics to score time-dependent treatment impact in a murine Escherichia coli sepsis model after administering beta-lactam antibiotic meropenem (Mem) and/or the immunomodulatory glucocorticoid methylprednisolone (Gcc). Three distinct proteome response patterns were identified, which depended on the underlying proteotype for each organ. Gcc enhanced some positive proteome responses of Mem, including superior reduction of the inflammatory response in kidneys and partial restoration of sepsis-induced metabolic dysfunction. Mem introduced sepsis-independent perturbations in the mitochondrial proteome that Gcc counteracted. We provide a strategy for the quantitative and organotypic assessment of treatment effects of candidate therapies in relationship to dosing, timing, and potential synergistic intervention combinations during sepsis.

Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets

Background

Sepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or 'omics' experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq.

Objective

Most of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis.

Methods

PubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.).

Results

After performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca).

Conclusions

SeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.

Integrative diagnostics: the time is now-a report from the International Society for Strategic Studies in Radiology

Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the "silo" of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the electronic health record, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient's care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice.

Host Response Biomarkers for Sepsis in the Emergency Room

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Embracing complexity in sepsis

Sepsis involves the dynamic interplay between a pathogen, the host response, the failure of organ systems, medical interventions and a myriad of other factors. This together results in a complex, dynamic and dysregulated state that has remained ungovernable thus far. While it is generally accepted that sepsis is very complex indeed, the concepts, approaches and methods that are necessary to understand this complexity remain underappreciated. In this perspective we view sepsis through the lens of complexity theory. We describe the concepts that support viewing sepsis as a state of a highly complex, non-linear and spatio-dynamic system. We argue that methods from the field of complex systems are pivotal for a fuller understanding of sepsis, and we highlight the progress that has been made over the last decades in this respect. Still, despite these considerable advancements, methods like computational modelling and network-based analyses continue to fly under the general scientific radar. We discuss what barriers contribute to this disconnect, and what we can do to embrace complexity with regards to measurements, research approaches and clinical applications. Specifically, we advocate a focus on longitudinal, more continuous biological data collection in sepsis. Understanding the complexity of sepsis will require a huge multidisciplinary effort, in which computational approaches derived from complex systems science must be supported by, and integrated with, biological data. Such integration could finetune computational models, guide validation experiments, and identify key pathways that could be targeted to modulate the system to the benefit of the host. We offer an example for immunological predictive modelling, which may inform agile trials that could be adjusted throughout the trajectory of disease. Overall, we argue that we should expand our current mental frameworks of sepsis, and embrace nonlinear, system-based thinking in order to move the field forward.

Plasma enzymatic activity, proteomics and peptidomics in COVID-19-induced sepsis: A novel approach for the analysis of hemostasis

Introduction: Infection by SARS-CoV-2 and subsequent COVID-19 can cause viral sepsis. We investigated plasma protease activity patterns in COVID-19-induced sepsis with bacterial superinfection, as well as plasma proteomics and peptidomics in order to assess the possible implications of enhanced proteolysis on major protein systems (e.g., coagulation). Methods: Patients (=4) admitted to the intensive care units (ICUs) at the University of California, San Diego (UCSD) Medical Center with confirmed positive test for COVID-19 by real-time reverse transcription polymerase chain reaction (RT-PCR) were enrolled in a study approved by the UCSD Institutional Review Board (IRB# 190699, Protocol #20-0006). Informed consent was obtained for the collection of blood samples and de-identified use of the data. Blood samples were collected at multiple time points and analyzed to quantify a) the circulating proteome and peptidome by mass spectrometry; b) the aminopeptidase activity in plasma; and c) the endopeptidase activity in plasma using fluorogenic substrates that are cleaved by trypsin-like endopeptidases, specific clotting factors and plasmin. The one patient who died was diagnosed with bacterial superinfection on day 7 after beginning of the study. Results: Spikes in protease activity (factor VII, trypsin-like activity), and corresponding increases in the intensity of peptides derived by hydrolysis of plasma proteins, especially of fibrinogen degradation products and downregulation of endogenous protease inhibitors were detected on day 7 for the patient who died. The activity of the analyzed proteases was stable in survivors. Discussion: The combination of multiomics and enzymatic activity quantification enabled to i) hypothesize that elevated proteolysis occurs in COVID-19-induced septic shock with bacterial superinfection, and ii) provide additional insight into malfunctioning protease-mediated systems, such as hemostasis.

Distinct subsets of neutrophils crosstalk with cytokines and metabolites in patients with sepsis

Sepsis is a life-threatening condition caused by a dysregulated host response to infection. Despite continued efforts to understand the pathophysiology of sepsis, no effective therapies are currently available. While singular components of the aberrant immune response have been investigated, comprehensive studies linking different data layers are lacking. Using an integrated systems immunology approach, we evaluated neutrophil phenotypes and concomitant changes in cytokines and metabolites in patients with sepsis. Our findings identify differentially expressed mature and immature neutrophil subsets in patients with sepsis. These subsets correlate with various proteins, metabolites, and lipids, including pentraxin-3, angiopoietin-2, and lysophosphatidylcholines, in patients with sepsis. These results enabled the construction of a statistical model based on weighted multi-omics linear regression analysis for sepsis biomarker identification. These findings could help inform early patient stratification and treatment options, and facilitate further mechanistic studies targeting the trifecta of surface marker expression, cytokines, and metabolites.

Integrative Diagnostics: The Time Is Now-A Report From the International Society for Strategic Studies in Radiology

Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the "silo" of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the electronic health record, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient's care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice.

Immunopathophysiology of human sepsis

Sepsis is an ill-defined syndrome yet is a leading cause of morbidity and mortality worldwide. The most recent consensus defines sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection. However, this definition belies the complexity and breadth of immune mechanisms involved in sepsis, which are characterized by simultaneous hyperinflammation and immune suppression. In this review, we describe the immunopathogenesis of sepsis and highlight some recent pathophysiological findings that have expanded our understanding of sepsis. Sepsis endotypes can be used to divide sepsis patients in different groups with distinct immune profiles and outcomes. We also summarize evidence on the role of the gut microbiome in sepsis immunity. The challenge of the coming years will be to translate our increasing knowledge about the molecular mechanisms underlying sepsis into therapies that improve relevant patient outcomes.

Sepsis biomarkers and diagnostic tools with a focus on machine learning

Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers.

Current sepsis therapeutics

Management of the patient with sepsis comprises three key branches: control of the underlying infection, haemodynamic stabilization, and modulation of the host response. Each aspect should be considered in all patients and, when relevant, managed at the same time. Infection control is applicable to all patients with sepsis and will include antibiotic therapy and often surgical intervention to remove an infectious source. Haemodynamic support involves fluid administration in all patients and vasoactive agents in patients with associated circulatory shock. Noradrenaline is the first choice vasopressor agent; inotropic agents, usually dobutamine, may be added in case of myocardial depression. No interventions directed at individual components of the host response to sepsis have yet been shown to improve outcomes, but glucocorticoids and vasopressin have a global impact on the response and can thus be considered in this category. A move toward more personalized treatment is needed across all three arms of sepsis management.

Gaps and opportunities in sepsis translational research

Infection initiates sepsis, but the clinical disease arises through the innate immune response of the host. A rapidly evolving understanding of the biology of that response has not been paralleled by the development of successful new treatment. The COVID-19 pandemic has begun to change this revealing the promise of distinct therapeutic approaches and the feasibility of new approaches to evaluate them. We review the history of mediator-targeted therapy for sepsis and explore the conceptual, biological, technological, and organizational challenges that must be addressed to enable the development of effective treatments for a leading cause of global morbidity and mortality.

Sepsis-induced immunosuppression: mechanisms, diagnosis and current treatment options

Sepsis is a common complication of combat injuries and trauma, and is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is also one of the significant causes of death and increased health care costs in modern intensive care units. The use of antibiotics, fluid resuscitation, and organ support therapy have limited prognostic impact in patients with sepsis. Although its pathophysiology remains elusive, immunosuppression is now recognized as one of the major causes of septic death. Sepsis-induced immunosuppression is resulted from disruption of immune homeostasis. It is characterized by the release of anti-inflammatory cytokines, abnormal death of immune effector cells, hyperproliferation of immune suppressor cells, and expression of immune checkpoints. By targeting immunosuppression, especially with immune checkpoint inhibitors, preclinical studies have demonstrated the reversal of immunocyte dysfunctions and established host resistance. Here, we comprehensively discuss recent findings on the mechanisms, regulation and biomarkers of sepsis-induced immunosuppression and highlight their implications for developing effective strategies to treat patients with septic shock.

The role of proteomics and metabolomics in severe infections

PURPOSE OF REVIEW

Severe infections are a common cause of ICU admission, with a high morbidity and mortality. Omics, namely proteomics and metabolomics, aim to identify, characterize, and quantify biological molecules to achieve a systems-level understanding of disease. The aim of this review is to provide a clear overview of the current evidence of the role of proteomics and metabolomics in severe infections.

RECENT FINDINGS

Proteomics and metabolomics are technologies that are being used to explore new markers of diagnosis and prognosis, clarify mechanisms of disease, and consequently discover potential targets of therapy and finally of a better disease phenotyping. These technologies are starting to be used but not yet in clinical use.

SUMMARY

Our traditional way of approaching the disease as sepsis is believing that a process can be broken into its parts and that the whole can be explained by the sum of each part. This approach is highly reductionist and does not take the system complexity nor the nonlinear dynamics of the processes. Proteomics and metabolomics allow the analysis of several proteins and metabolites simultaneously, thereby generating diagnostic and prognostic signatures. An exciting future prospect for proteomics and metabolomics is their employment towards precision medicine.

Molecular Methodologies for Improved Polymicrobial Sepsis Diagnosis

Polymicrobial sepsis is associated with worse patient outcomes than monomicrobial sepsis. Routinely used culture-dependent microbiological diagnostic techniques have low sensitivity, often leading to missed identification of all causative organisms. To overcome these limitations, culture-independent methods incorporating advanced molecular technologies have recently been explored. However, contamination, assay inhibition and interference from host DNA are issues that must be addressed before these methods can be relied on for routine clinical use. While the host component of the complex sepsis host–pathogen interplay is well described, less is known about the pathogen’s role, including pathogen–pathogen interactions in polymicrobial sepsis. This review highlights the clinical significance of polymicrobial sepsis and addresses how promising alternative molecular microbiology methods can be improved to detect polymicrobial infections. It also discusses how the application of shotgun metagenomics can be used to uncover pathogen/pathogen interactions in polymicrobial sepsis cases and their potential role in the clinical course of this condition.

Transcriptional Response in a Sepsis Mouse Model Reflects Transcriptional Response in Sepsis Patients

Mortality due to sepsis remains unacceptably high, especially for septic shock patients. Murine models have been used to better understand pathophysiology mechanisms. However, the mouse model is still under debate. Herein we investigated the transcriptional response of mice injected with lipopolysaccharide (LPS) and compared it to either human cells stimulated in vitro with LPS or to the blood cells of septic patients. We identified a molecular signature composed of 2331 genes with an FDR median of 0%. This molecular signature is highly enriched in regulated genes in peritoneal macrophages stimulated with LPS. There is significant enrichment in several inflammatory signaling pathways, and in disease terms, such as pneumonia, sepsis, systemic inflammatory response syndrome, severe sepsis, an inflammatory disorder, immune suppression, and septic shock. A significant overlap between the genes upregulated in mouse and human cells stimulated with LPS has been demonstrated. Finally, genes upregulated in mouse cells stimulated with LPS are enriched in genes upregulated in human cells stimulated in vitro and in septic patients, who are at high risk of death. Our results support the hypothesis of common molecular and cellular mechanisms between mouse and human sepsis.

The immunology of sepsis

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to an infection. This recently implemented definition does not capture the heterogeneity or the underlying pathophysiology of the syndrome, which is characterized by concurrent unbalanced hyperinflammation and immune suppression. Here, we review current knowledge of aberrant immune responses during sepsis and recent initiatives to stratify patients with sepsis into subgroups that are more alike from a clinical and/or pathobiological perspective, which could be key for identification of patients who are more likely to benefit from specific immune interventions.