The Search for Efficacious New Therapies in Sepsis Needs to Embrace Heterogeneity

Hospital-Onset Sepsis Warrants Expanded Investigation and Consideration as a Unique Clinical Entity

Sepsis causes more than a quarter million deaths among hospitalized adults in the United States each year. Although most cases of sepsis are present on admission, up to one-quarter of patients with sepsis develop this highly morbid and mortal condition while hospitalized. Compared with patients with community-onset sepsis (COS), patients with hospital-onset sepsis (HOS) are twice as likely to require mechanical ventilation and ICU admission, have more than two times longer ICU and hospital length of stay, accrue five times higher hospital costs, and are twice as likely to die. Patients with HOS differ from those with COS with respect to underlying comorbidities, admitting diagnosis, clinical manifestations of infection, and severity of illness. Despite the differences between these patient populations, patients with HOS sepsis are understudied and warrant expanded investigation. Here, we outline important knowledge gaps in the recognition and management of HOS in adults and propose associated research priorities for investigators. Of particular importance are questions regarding standardization of research and clinical case identification, understanding of clinical heterogeneity among patients with HOS, development of tailored management recommendations, identification of impactful prevention strategies, optimization of care delivery and quality metrics, identification and correction of disparities in care and outcomes, and how to ensure goal-concordant care for patients with HOS.

Distinct functional neutrophil phenotypes in sepsis patients correlate with disease severity

Purpose

Sepsis is a clinical syndrome defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis is a highly heterogeneous syndrome with distinct phenotypes that impact immune function and response to infection. To develop targeted therapeutics, immunophenotyping is needed to identify distinct functional phenotypes of immune cells. In this study, we utilized our Organ-on-Chip assay to categorize sepsis patients into distinct phenotypes using patient data, neutrophil functional analysis, and proteomics.

Methods

Following informed consent, neutrophils and plasma were isolated from sepsis patients in the Temple University Hospital ICU (n=45) and healthy control donors (n=7). Human lung microvascular endothelial cells (HLMVEC) were cultured in the Organ-on-Chip and treated with buffer or cytomix ((TNF/IL-1β/IFNγ). Neutrophil adhesion and migration across HLMVEC in the Organ-on-Chip were used to categorize functional neutrophil phenotypes. Quantitative label-free global proteomics was performed on neutrophils to identify differentially expressed proteins. Plasma levels of sepsis biomarkers and neutrophil extracellular traps (NETs) were determined by ELISA.

Results

We identified three functional phenotypes in critically ill ICU sepsis patients based on ex vivo neutrophil adhesion and migration patterns. The phenotypes were classified as: Hyperimmune characterized by enhanced neutrophil adhesion and migration, Hypoimmune that was unresponsive to stimulation, and Hybrid with increased adhesion but blunted migration. These functional phenotypes were associated with distinct proteomic signatures and differentiated sepsis patients by important clinical parameters related to disease severity. The Hyperimmune group demonstrated higher oxygen requirements, increased mechanical ventilation, and longer ICU length of stay compared to the Hypoimmune and Hybrid groups. Patients with the Hyperimmune neutrophil phenotype had significantly increased circulating neutrophils and elevated plasma levels NETs.

Conclusion

Neutrophils and NETs play a critical role in vascular barrier dysfunction in sepsis and elevated NETs may be a key biomarker identifying the Hyperimmune group. Our results establish significant associations between specific neutrophil functional phenotypes and disease severity and identify important functional parameters in sepsis pathophysiology that may provide a new approach to classify sepsis patients for specific therapeutic interventions.

Comparison of time series clustering methods for identifying novel subphenotypes of patients with infection

OBJECTIVE

Severe infection can lead to organ dysfunction and sepsis. Identifying subphenotypes of infected patients is essential for personalized management. It is unknown how different time series clustering algorithms compare in identifying these subphenotypes.

MATERIALS AND METHODS

Patients with suspected infection admitted between 2014 and 2019 to 4 hospitals in Emory healthcare were included, split into separate training and validation cohorts. Dynamic time warping (DTW) was applied to vital signs from the first 8 h of hospitalization, and hierarchical clustering (DTW-HC) and partition around medoids (DTW-PAM) were used to cluster patients into subphenotypes. DTW-HC, DTW-PAM, and a previously published group-based trajectory model (GBTM) were evaluated for agreement in subphenotype clusters, trajectory patterns, and subphenotype associations with clinical outcomes and treatment responses.

RESULTS

There were 12 473 patients in training and 8256 patients in validation cohorts. DTW-HC, DTW-PAM, and GBTM models resulted in 4 consistent vitals trajectory patterns with significant agreement in clustering (71-80% agreement, P < .001): group A was hyperthermic, tachycardic, tachypneic, and hypotensive. Group B was hyperthermic, tachycardic, tachypneic, and hypertensive. Groups C and D had lower temperatures, heart rates, and respiratory rates, with group C normotensive and group D hypotensive. Group A had higher odds ratio of 30-day inpatient mortality (P < .01) and group D had significant mortality benefit from balanced crystalloids compared to saline (P < .01) in all 3 models.

DISCUSSION

DTW- and GBTM-based clustering algorithms applied to vital signs in infected patients identified consistent subphenotypes with distinct clinical outcomes and treatment responses.

CONCLUSION

Time series clustering with distinct computational approaches demonstrate similar performance and significant agreement in the resulting subphenotypes.

Biomarkers for the Prediction and Judgement of Sepsis and Sepsis Complications: A Step towards precision medicine?

Sepsis and septic shock are a major public health concern and are still associated with high rates of morbidity and mortality. Whilst there is growing understanding of different phenotypes and endotypes of sepsis, all too often treatment strategies still only employ a “one-size-fits-all” approach. Biomarkers offer a unique opportunity to close this gap to more precise treatment approaches by providing insight into clinically hidden, yet complex, pathophysiology, or by individualizing treatment pathways. Predicting and evaluating systemic inflammation, sepsis or septic shock are essential to improve outcomes for these patients. Besides opportunities to improve patient care, employing biomarkers offers a unique opportunity to improve clinical research in patients with sepsis. The high rate of negative clinical trials in this field may partly be explained by a high degree of heterogeneity in patient cohorts and a lack of understanding of specific endotypes or phenotypes. Moving forward, biomarkers can support the selection of more homogeneous cohorts, thereby potentially improving study conditions of clinical trials. This may finally pave the way to a precision medicine approach to sepsis, septic shock and complication of sepsis in the future.

Clinical Subtypes of Sepsis Survivors Predict Readmission and Mortality After Hospital Discharge

RATIONALE

Sepsis survivors experience adverse outcomes including high rates of post-discharge mortality and rehospitalization. Given the heterogeneity of the condition, identifying subtypes within this population with different risks of post-discharge outcomes may optimize post-sepsis care.

OBJECTIVES

To classify individuals into subtypes and assess the association of subtypes with 30-day rehospitalization and mortality.

METHODS

We conducted a retrospective observational study between January 2014 and October 2017 among 20,745 patients admitted to one of 12 Southeastern US hospitals with a clinical definition of sepsis. We used latent class analysis to classify sepsis survivors into subtypes, which were evaluated against 30-day readmission and mortality rates using a specialized regression approach. A secondary analysis evaluated subtypes against ambulatory-care-sensitive-condition readmission rate.

RESULTS

Among 20,745 patients, latent class analysis identified 5 distinct subtypes as the optimal solution. Clinical subtype was associated with 30-day readmission, with the Chronically Ill, Severe Illness subtype demonstrating highest risk (35%) and the Low Functional Needs, Uncomplicated Illness subtype demonstrating the lowest risk (9%). 47% of readmissions in the High Functional Needs, Uncomplicated Illness subtype were for ambulatory-care-sensitive conditions, whereas 17% of readmissions in the Previously Healthy, Severe Illness subtype were for ambulatory-care-sensitive conditions. Subtype was significantly associated with 30-day mortality; highest in the Chronically Ill, Severe Illness subtype (8%) and lowest in the Low Functional Needs, Uncomplicated Illness subtype (0.1%).

CONCLUSIONS

Sepsis survivors can be classified into subtypes with differential 30-day mortality and readmission risk profiles. Pre-discharge classification may allow an individualized approach to post-sepsis care.

A Research Agenda for Precision Medicine in Sepsis and Acute Respiratory Distress Syndrome: An Official American Thoracic Society Research Statement

Background: Precision medicine focuses on the identification of therapeutic strategies that are effective for a group of patients based on similar unifying characteristics. The recent success of precision medicine in non-critical care settings has resulted from the confluence of large clinical and biospecimen repositories, innovative bioinformatics, and novel trial designs. Similar advances for precision medicine in sepsis and in the acute respiratory distress syndrome (ARDS) are possible but will require further investigation and significant investment in infrastructure. Methods: This project was funded by the American Thoracic Society Board of Directors. A multidisciplinary and diverse working group reviewed the available literature, established a conceptual framework, and iteratively developed recommendations for the Precision Medicine Research Agenda for Sepsis and ARDS. Results: The following six priority recommendations were developed by the working group: 1) the creation of large richly phenotyped and harmonized knowledge networks of clinical, imaging, and multianalyte molecular data for sepsis and ARDS; 2) the implementation of novel trial designs, including adaptive designs, and embedding trial procedures in the electronic health record; 3) continued innovation in the data science and engineering methods required to identify heterogeneity of treatment effect; 4) further development of the tools necessary for the real-time application of precision medicine approaches; 5) work to ensure that precision medicine strategies are applicable and available to a broad range of patients varying across differing racial, ethnic, socioeconomic, and demographic groups; and 6) the securement and maintenance of adequate and sustainable funding for precision medicine efforts. Conclusions: Precision medicine approaches that incorporate variability in genomic, biologic, and environmental factors may provide a path forward for better individualizing the delivery of therapies and improving care for patients with sepsis and ARDS.

Dynamic monitoring of kidney injury status over 3 days in the intensive care unit as a sepsis phenotype associated with hospital mortality and hyperinflammation

Background

Sepsis-associated acute kidney injury (AKI) often worsens with the deterioration of a patient's condition. Therefore, we hypothesized that monitoring AKI dynamically from day 1 to day 3 was potential to predict hospital mortality. Specifically, we explored whether monitoring AKI dynamically in the intensive care unit (ICU) could be a sepsis phenotype predictive of mortality. A new classification was established based on the change in the AKI stage from admission day 1 and day 3. We compared the hospital mortality, cytokines, and immune response pattern between each group.

Methods

We retrospectively enrolled 523 patients with sepsis, and we calculated the AKI stages on day 1 and day 3 admission to ICUs.

Among these 523 people, 388 of them were assigned to normal, improved, and deteriorated groups according to the changes in the AKI stages. 263 of which did not develop AKI on day 1 and day 3 (normal group). The AKI stage improved in 68 patients (improved group) and worsened in 57 (deteriorated group). We compared the mortality rates between the groups, and identified the relationship between the dynamic AKI status, immune response patterns, and cytokine levels.

Results

The hospital mortality rate in the deteriorated group was higher than that in the non-deteriorated group (combination of normal and improved group) (p = 0.004). Additionally, according to the Kaplan–Meier analysis, the non-deteriorated group had a distinct hospital survival curve (p = 0.004). Furthermore, both the overexpression of tumor necrosis factor-α and decreased monocyte expression of human leukocyte antigen-DR were present in the deteriorated group.

Conclusions

The deteriorated group was associated with a higher hospital mortality rate, potentially resulting from an abnormal inflammatory response. Worsening AKI in the first 3 days of ICU admission may be a sepsis phenotype predictive of hospital mortality.

Plasma from patients with bacterial sepsis or severe COVID-19 induces suppressive myeloid cell production from hematopoietic progenitors in vitro

Bacterial sepsis and severe COVID-19 share similar clinical manifestations and are both associated with dysregulation of the myeloid cell compartment. We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis and validated expansion of this cell subpopulation in publicly available transcriptomics data. Here, using published datasets, we show that the gene expression program associated with MS1 correlated with sepsis severity and was up-regulated in monocytes from patients with severe COVID-19. To examine the ontogeny and function of MS1 cells, we developed a cellular model for inducing CD14+ MS1 monocytes from healthy bone marrow hematopoietic stem and progenitor cells (HSPCs). We found that plasma from patients with bacterial sepsis or COVID-19 induced myelopoiesis in HSPCs in vitro and expression of the MS1 gene program in monocytes and neutrophils that differentiated from these HSPCs. Furthermore, we found that plasma concentrations of IL-6, and to a lesser extent IL-10, correlated with increased myeloid cell output from HSPCs in vitro and enhanced expression of the MS1 gene program. We validated the requirement for these two cytokines to induce the MS1 gene program through CRISPR-Cas9 editing of their receptors in HSPCs. Using this cellular model system, we demonstrated that induced MS1 cells were broadly immunosuppressive and showed decreased responsiveness to stimulation with a synthetic RNA analog. Our in vitro study suggests a potential role for systemic cytokines in inducing myelopoiesis during severe bacterial or SARS-CoV-2 infection.

Role of Inflammatory Cytokines in COVID-19 Patients: A Review on Molecular Mechanisms, Immune Functions, Immunopathology and Immunomodulatory Drugs to Counter Cytokine Storm

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a severe pandemic of the current century. The vicious tentacles of the disease have been disseminated worldwide with unknown complications and repercussions. Advanced COVID-19 syndrome is characterized by the uncontrolled and elevated release of pro-inflammatory cytokines and suppressed immunity, leading to the cytokine storm. The uncontrolled and dysregulated secretion of inflammatory and pro-inflammatory cytokines is positively associated with the severity of the viral infection and mortality rate. The secretion of various pro-inflammatory cytokines such as TNF-α, IL-1, and IL-6 leads to a hyperinflammatory response by recruiting macrophages, T and B cells in the lung alveolar cells. Moreover, it has been hypothesized that immune cells such as macrophages recruit inflammatory monocytes in the alveolar cells and allow the production of large amounts of cytokines in the alveoli, leading to a hyperinflammatory response in severely ill patients with COVID-19. This cascade of events may lead to multiple organ failure, acute respiratory distress, or pneumonia. Although the disease has a higher survival rate than other chronic diseases, the incidence of complications in the geriatric population are considerably high, with more systemic complications. This review sheds light on the pivotal roles played by various inflammatory markers in COVID-19-related complications. Different molecular pathways, such as the activation of JAK and JAK/STAT signaling are crucial in the progression of cytokine storm; hence, various mechanisms, immunological pathways, and functions of cytokines and other inflammatory markers have been discussed. A thorough understanding of cytokines' molecular pathways and their activation procedures will add more insight into understanding immunopathology and designing appropriate drugs, therapies, and control measures to counter COVID-19. Recently, anti-inflammatory drugs and several antiviral drugs have been reported as effective therapeutic drug candidates to control hypercytokinemia or cytokine storm. Hence, the present review also discussed prospective anti-inflammatory and relevant immunomodulatory drugs currently in various trial phases and their possible implications.

Disseminated Intravascular Coagulation Is an Independent Predictor of Adverse Outcomes in Children in the Emergency Department with Suspected Sepsis

OBJECTIVE

To evaluate the impact of early disseminated intravascular coagulation (DIC) on illness severity in children using a database of emergency department ED encounters for children with suspected sepsis, in view of similar associations in adults.

STUDY DESIGN

Laboratory and clinical data were extracted from a registry of emergency department encounters of children with suspected sepsis between April 1, 2012, and June 26, 2017. International Society of Thrombosis and Hemostasis DIC scores were calculated from laboratory values obtained within 24 hours of emergency department admission. Univariate logistic regression, multivariable logistic regression, and Cox regression were used to assess the influence of DIC scores on vasopressor use (primary outcome), mortality, ventilator requirement, pediatric intensive care unit admission, and hospital duration (secondary outcomes). The optimal DIC score cutoff for outcome prediction was determined.

RESULTS

Of 1653 eligible patients, 284 had DIC scores within 24 hours, including 92 who required vasopressors and 23 who died within 1 year. An initial DIC score of ≥3 was the most sensitive and specific DIC score for predicting adverse outcomes. Those with a DIC score of ≥3 vs <3 had increased odds of vasopressor use in both univariate (OR, 4.48; 95% CI, 2.63-7.62; P < .001) and multivariable (OR, 3.78; 95% CI, 1.82-7.85; P < .001) analyses. Additionally, those with a DIC score of ≥3 vs <3 had increased 1-year mortality with a hazard ratio of 3.55 (95% CI, 1.46-8.64; P = .005).

CONCLUSIONS

A DIC score of ≥3 was an independent predictor for both vasopressor use and mortality in this pediatric cohort, distinct from the adult overt DIC score cutoff of ≥5.

Induction of a regulatory myeloid program in bacterial sepsis and severe COVID-19

A recent estimate suggests that one in five deaths globally are associated with sepsis ¹ . To date, no targeted treatment is available for this syndrome, likely due to substantial patient heterogeneity ^2,3 and our lack of insight into sepsis immunopathology ⁴ . These issues are highlighted by the current COVID-19 pandemic, wherein many clinical manifestations of severe SARS-CoV-2 infection parallel bacterial sepsis ^5-8 . We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis or non-infectious critical illness, and validated its expansion in sepsis across thousands of patients using public transcriptomic data ⁹ . Despite its marked expansion in the circulation of bacterial sepsis patients, its relevance to viral sepsis and association with disease outcomes have not been examined. In addition, the ontogeny and function of this monocyte state remain poorly characterized. Using public transcriptomic data, we show that the expression of the MS1 program is associated with sepsis mortality and is up-regulated in monocytes from patients with severe COVID-19. We found that blood plasma from bacterial sepsis or COVID-19 patients with severe disease induces emergency myelopoiesis and expression of the MS1 program, which are dependent on the cytokines IL-6 and IL-10. Finally, we demonstrate that MS1 cells are broadly immunosuppressive, similar to monocytic myeloid-derived suppressor cells (MDSCs), and have decreased responsiveness to stimulation. Our findings highlight the utility of regulatory myeloid cells in sepsis prognosis, and the role of systemic cytokines in inducing emergency myelopoiesis during severe bacterial and SARS-CoV-2 infections.