Transcriptomic Signatures in Sepsis and a Differential Response to Steroids. From the VANISH Randomized Trial

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.

Highlights from the Respiratory Failure and Mechanical Ventilation 2022 Conference

The Respiratory Intensive Care Assembly of the European Respiratory Society gathered in Berlin to organise the second Respiratory Failure and Mechanical Ventilation Conference in June 2022. The conference covered several key points of acute and chronic respiratory failure in adults. During the 3-day conference, ventilatory strategies, patient selection, diagnostic approaches, treatment and health-related quality of life topics were addressed by a panel of international experts. Lectures delivered during the event have been summarised by Early Career Members of the Assembly and take-home messages highlighted.

Development of a Reinforcement Learning Algorithm to Optimize Corticosteroid Therapy in Critically Ill Patients with Sepsis

BACKGROUND

The optimal indication, dose, and timing of corticosteroids in sepsis is controversial. Here, we used reinforcement learning to derive the optimal steroid policy in septic patients based on data on 3051 ICU admissions from the AmsterdamUMCdb intensive care database.

METHODS

We identified septic patients according to the 2016 consensus definition. An actor-critic RL algorithm using ICU mortality as a reward signal was developed to determine the optimal treatment policy from time-series data on 277 clinical parameters. We performed off-policy evaluation and testing in independent subsets to assess the algorithm's performance.

RESULTS

Agreement between the RL agent's policy and the actual documented treatment reached 59%. Our RL agent's treatment policy was more restrictive compared to the actual clinician behavior: our algorithm suggested withholding corticosteroids in 62% of the patient states, versus 52% according to the physicians' policy. The 95% lower bound of the expected reward was higher for the RL agent than clinicians' historical decisions. ICU mortality after concordant action in the testing dataset was lower both when corticosteroids had been withheld and when corticosteroids had been prescribed by the virtual agent. The most relevant variables were vital parameters and laboratory values, such as blood pressure, heart rate, leucocyte count, and glycemia.

CONCLUSIONS

Individualized use of corticosteroids in sepsis may result in a mortality benefit, but optimal treatment policy may be more restrictive than the routine clinical practice. Whilst external validation is needed, our study motivates a 'precision-medicine' approach to future prospective controlled trials and practice.

The ultimate tradeoff: how red cell adaptations to malaria alter the host response during critical illness

The human immune system evolved in response to pathogens. Among these pathogens, malaria has proven to be one of the deadliest and has exerted the most potent selective pressures on its target cell, the red blood cell. Red blood cells have recently gained recognition for their immunomodulatory properties, yet how red cell adaptations contribute to the host response during critical illness remains understudied. This review will discuss how adaptations that may have been advantageous for host survival might influence immune responses in modern critical illness. We will highlight the current evidence for divergent host resilience arising from the adaptations to malaria and summarize how understanding evolutionary red cell adaptations to malaria may provide insight into the heterogeneity of the host response to critical illness, perhaps driving future precision medicine approaches to syndromes affecting the critically ill such as sepsis and acute respiratory distress syndrome (ARDS).

Biological Phenotyping in Sepsis and Acute Respiratory Distress Syndrome

Heterogeneity in sepsis and acute respiratory distress syndrome (ARDS) is increasingly being recognized as one of the principal barriers to finding efficacious targeted therapies. The advent of multiple high-throughput biological data ("omics"), coupled with the widespread access to increased computational power, has led to the emergence of phenotyping in critical care. Phenotyping aims to use a multitude of data to identify homogenous subgroups within an otherwise heterogenous population. Increasingly, phenotyping schemas are being applied to sepsis and ARDS to increase understanding of these clinical conditions and identify potential therapies. Here we present a selective review of the biological phenotyping schemas applied to sepsis and ARDS. Further, we outline some of the challenges involved in translating these conceptual findings to bedside clinical decision-making tools.

I./K. COVID-19 Study Group, Michaëlsson J, Flodström-Tullberg M, Brighenti S, Buggert M, Mjösberg J, Malmberg KJ, Sandberg JK, Gredmark-Russ S, Rooyackers O, Svensson M, Chambers BJ, Eriksson LI, Pernemalm M, Björkström NK, Aleman S, Ljunggren HG, Klingström J, Strålin K, Norrby-Teglund A. Targeted plasma proteomics reveals signatures discriminating COVID-19 from sepsis with pneumonia

BACKGROUND

COVID-19 remains a major public health challenge, requiring the development of tools to improve diagnosis and inform therapeutic decisions. As dysregulated inflammation and coagulation responses have been implicated in the pathophysiology of COVID-19 and sepsis, we studied their plasma proteome profiles to delineate similarities from specific features.

METHODS

We measured 276 plasma proteins involved in Inflammation, organ damage, immune response and coagulation in healthy controls, COVID-19 patients during acute and convalescence phase, and sepsis patients; the latter included (i) community-acquired pneumonia (CAP) caused by Influenza, (ii) bacterial CAP, (iii) non-pneumonia sepsis, and (iv) septic shock patients.

RESULTS

We identified a core response to infection consisting of 42 proteins altered in both COVID-19 and sepsis, although higher levels of cytokine storm-associated proteins were evident in sepsis. Furthermore, microbiologic etiology and clinical endotypes were linked to unique signatures. Finally, through machine learning, we identified biomarkers, such as TRIM21, PTN and CASP8, that accurately differentiated COVID-19 from CAP-sepsis with higher accuracy than standard clinical markers.

CONCLUSIONS

This study extends the understanding of host responses underlying sepsis and COVID-19, indicating varying disease mechanisms with unique signatures. These diagnostic and severity signatures are candidates for the development of personalized management of COVID-19 and sepsis.

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.

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.

A plea for personalization of the hemodynamic management of septic shock

Although guidelines provide excellent expert guidance for managing patients with septic shock, they leave room for personalization according to patients' condition. Hemodynamic monitoring depends on the evolution phase: salvage, optimization, stabilization, and de-escalation. Initially during the salvage phase, monitoring to identify shock etiology and severity should include arterial pressure and lactate measurements together with clinical examination, particularly skin mottling and capillary refill time. Low diastolic blood pressure may trigger vasopressor initiation. At this stage, echocardiography may be useful to identify significant cardiac dysfunction. During the optimization phase, echocardiographic monitoring should be pursued and completed by the assessment of tissue perfusion through central or mixed-venous oxygen saturation, lactate, and carbon dioxide veno-arterial gradient. Transpulmonary thermodilution and the pulmonary artery catheter should be considered in the most severe patients. Fluid therapy also depends on shock phases. While administered liberally during the resuscitation phase, fluid responsiveness should be assessed during the optimization phase. During stabilization, fluid infusion should be minimized. In the de-escalation phase, safe fluid withdrawal could be achieved by ensuring tissue perfusion is preserved. Norepinephrine is recommended as first-line vasopressor therapy, while vasopressin may be preferred in some patients. Essential questions remain regarding optimal vasopressor selection, combination therapy, and the most effective and safest escalation. Serum renin and the angiotensin I/II ratio may identify patients who benefit most from angiotensin II. The optimal therapeutic strategy for shock requiring high-dose vasopressors is scant. In all cases, vasopressor therapy should be individualized, based on clinical evaluation and blood flow measurements to avoid excessive vasoconstriction. Inotropes should be considered in patients with decreased cardiac contractility associated with impaired tissue perfusion. Based on pharmacologic properties, we suggest as the first test a limited dose of dobutamine, to add enoximone or milrinone in the second line and substitute or add levosimendan if inefficient. Regarding adjunctive therapies, while hydrocortisone is nowadays advised in patients receiving high doses of vasopressors, patients responding to corticosteroids may be identified in the future by the analysis of selected cytokines or specific transcriptomic endotypes. To conclude, although some general rules apply for shock management, a personalized approach should be considered for hemodynamic monitoring and support.

Validating a Proteomic Signature of Severe COVID-19

COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19.

DESIGN

Prospective observational cohort study.

SETTING

Two hospitals in the United States.

PATIENTS

One hundred sixty-seven hospitalized adults with COVID-19.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88-0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006).

CONCLUSIONS

Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.

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.

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis

Background

Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be developed.

Methods and results

A total of 1,936 patients (sepsis samples, n=1,692; normal samples, n=244) in 7 discovery datasets were included to conduct weighted gene co-expression network analysis (WGCNA) to filter out candidate genes related to sepsis. Then, two subtypes of sepsis were classified in the training sepsis set (n=1,692), the Adaptive and Inflammatory, using K-means clustering analysis on 90 sepsis-related features. We validated these subtypes using 617 samples in 5 independent datasets and the merged 5 sets. Cibersort method revealed the Adaptive subtype was related to high infiltration levels of T cells and natural killer (NK) cells and a better clinical outcome. Immune features were validated by single-cell RNA sequencing (scRNA-seq) analysis. The Inflammatory subtype was associated with high infiltration of macrophages and a disadvantageous prognosis. Based on functional analysis, upregulation of the Toll-like receptor signaling pathway was obtained in Inflammatory subtype and NK cell-mediated cytotoxicity and T cell receptor signaling pathway were upregulated in Adaptive group. To quantify the cluster findings, a scoring system, called, risk score, was established using four datasets (n=980) in the discovery cohorts based on least absolute shrinkage and selection operator (LASSO) and logistic regression and validated in external sets (n=760). Multivariate logistic regression analysis revealed the risk score was an independent predictor of outcomes of sepsis patients (OR [odds ratio], 2.752, 95% confidence interval [CI], 2.234-3.389, P<0.001), when adjusted by age and gender. In addition, the validation sets confirmed the performance (OR, 1.638, 95% CI, 1.309-2.048, P<0.001). Finally, nomograms demonstrated great discriminatory potential than that of risk score, age and gender (training set: AUC=0.682, 95% CI, 0.643-0.719; validation set: AUC=0.624, 95% CI, 0.576-0.664). Decision curve analysis (DCA) demonstrated that the nomograms were clinically useful and had better discriminative performance to recognize patients at high risk than the age, gender and risk score, respectively.

Conclusions

In-depth analysis of a comprehensive landscape of the transcriptome characteristics of sepsis might contribute to personalized treatments and prediction of clinical outcomes.

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.

Immunomodulatory roles of red blood cells

PURPOSE OF THE REVIEW

To discuss recent advances supporting the role of red blood cells (RBCs) in the host immune response.

RECENT FINDINGS

Over the last century, research has demonstrated that red blood cells exhibit functions beyond oxygen transport, including immune function. Recent work indicates that the nucleic acid sensing receptor, toll-like receptor 9 (TLR9), is expressed on the RBC surface and implicated in innate immune activation and red cell clearance during inflammatory states. In addition to this DNA-sensing role of RBCs, there is growing evidence that RBCs may influence immune function by inducing vascular dysfunction. RBC proteomics and metabolomics have provided additional insight into RBC immune function, with several studies indicating changes to RBC membrane structure and metabolism in response to severe acute respiratory syndrome coronavirus 2 infection. These structural RBC changes may even provide insight into the pathophysiology of the 'long-coronavirus disease 2019' phenomenon. Finally, evidence suggests that RBCs may influence host immune responses via complement regulation. Taken together, these recent findings indicate RBCs possess immune function. Further studies will be required to elucidate better how RBC immune function contributes to the heterogeneous host response during inflammatory states.

SUMMARY

The appreciation for nongas exchanging, red blood cell immune functions is rapidly growing. A better understanding of these RBC functions may provide insight into the heterogeneity observed in the host immune response to infection and inflammation.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Renaissance of glucocorticoids in critical care in the era of COVID-19: ten urging questions

The 40-year-old experience with glucocorticosteroids (GCs) in the context of severe infections is complex and troublesome. Recently, however, a clear indication for GCs in severe COVID-19 has been established. This may constitute a harbinger of a wider use of GCs in critical illnesses. A fundamental prerequisite of such an action is a better understanding of the heterogeneity of critical illness and GCs operationalization within the precision medicine approach. In this perspective, we formulate ten major questions regarding the use of GCs in critical illness. Answering them will likely facilitate a new era of effective and personalized GCs use in modern critical care.

CIITA promoter polymorphism impairs monocytes HLA-DR expression in patients with septic shock

Low monocyte (m)HLA-DR expression is associated with mortality in sepsis. G-286A∗rs3087456 polymorphism in promoter III of HLA class II transactivator (CIITA), the master regulator of HLA, has been associated with autoimmune diseases but its role in sepsis has never been demonstrated. In 203 patients in septic shock, GG genotype was associated with 28-day mortality and mHLA-DR remained low whereas it increased in patients with AA or AG genotype. In ex vivo cells, mHLA-DR failed to augment in GG in comparison with AG or AA genotype on exposure to IFN-γ. Promoter III transcript levels were similar in control monocytes regardless of genotype and exposure to IFN-γ. Promoter III activity was decreased in GG genotype in monocyte cell line but restored after stimulation with IFN-γ. Hereby, we demonstrated that G-286A∗rs3087456 significantly impact mHLA-DR expression in patients with septic shock in part through CIITA promoter III activity, that can be rescued using IFN-γ.

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.

The End of “One Size Fits All” Sepsis Therapies: Toward an Individualized Approach

Sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to an infection, remains a major challenge for clinicians and trialists. Despite decades of research and multiple randomized clinical trials, a specific therapeutic for sepsis is not available. The evaluation of therapeutics targeting components of host response anomalies in patients with sepsis has been complicated by the inability to identify those in this very heterogeneous population who are more likely to benefit from a specific intervention. Additionally, multiple and diverse host response aberrations often co-exist in sepsis, and knowledge of which dysregulated biological organ system or pathway drives sepsis-induced pathology in an individual patient is limited, further complicating the development of effective therapies. Here, we discuss the drawbacks of previous attempts to develop sepsis therapeutics and delineate a future wherein interventions will be based on the host response profile of a patient.

Unmet needs in pneumonia research: a comprehensive approach by the CAPNETZ study group

Introduction

Despite improvements in medical science and public health, mortality of community-acquired pneumonia (CAP) has barely changed throughout the last 15 years. The current SARS-CoV-2 pandemic has once again highlighted the central importance of acute respiratory infections to human health. The “network of excellence on Community Acquired Pneumonia” (CAPNETZ) hosts the most comprehensive CAP database worldwide including more than 12,000 patients. CAPNETZ connects physicians, microbiologists, virologists, epidemiologists, and computer scientists throughout Europe. Our aim was to summarize the current situation in CAP research and identify the most pressing unmet needs in CAP research.

Methods

To identify areas of future CAP research, CAPNETZ followed a multiple-step procedure. First, research members of CAPNETZ were individually asked to identify unmet needs. Second, the top 100 experts in the field of CAP research were asked for their insights about the unmet needs in CAP (Delphi approach). Third, internal and external experts discussed unmet needs in CAP at a scientific retreat.

Results

Eleven topics for future CAP research were identified: detection of causative pathogens, next generation sequencing for antimicrobial treatment guidance, imaging diagnostics, biomarkers, risk stratification, antiviral and antibiotic treatment, adjunctive therapy, vaccines and prevention, systemic and local immune response, comorbidities, and long-term cardio-vascular complications.

Conclusion

Pneumonia is a complex disease where the interplay between pathogens, immune system and comorbidities not only impose an immediate risk of mortality but also affect the patients’ risk of developing comorbidities as well as mortality for up to a decade after pneumonia has resolved. Our review of unmet needs in CAP research has shown that there are still major shortcomings in our knowledge of CAP.

Early Biomarker Signatures in Surgical Sepsis

INTRODUCTION

Sepsis has complex, time-sensitive pathophysiology and important phenotypic subgroups. The objective of this study was to use machine learning analyses of blood and urine biomarker profiles to elucidate the pathophysiologic signatures of subgroups of surgical sepsis patients.

METHODS

This prospective cohort study included 243 surgical sepsis patients admitted to a quaternary care center between January 2015 and June 2017. We applied hierarchical clustering to clinical variables and 42 blood and urine biomarkers to identify phenotypic subgroups in a development cohort. Clinical characteristics and short-term and long-term outcomes were compared between clusters. A naïve Bayes classifier predicted cluster labels in a validation cohort.

RESULTS

The development cohort contained one cluster characterized by early organ dysfunction (cluster I, n = 18) and one cluster characterized by recovery (cluster II, n = 139). Cluster I was associated with higher Acute Physiologic Assessment and Chronic Health Evaluation II (30 versus 16, P < 0.001) and SOFA scores (13 versus 5, P < 0.001), greater prevalence of chronic cardiovascular and renal disease (P < 0.001) and septic shock (78% versus 17%, P < 0.001). Cluster I had higher mortality within 14 d of sepsis onset (11% versus 1.5%, P = 0.001) and within 1 y (44% versus 20%, P = 0.032), and higher incidence of chronic critical illness (61% versus 30%, P = 0.001). The Bayes classifier achieved 95% accuracy and identified two clusters that were similar to development cohort clusters.

CONCLUSIONS

Machine learning analyses of clinical and biomarker variables identified an early organ dysfunction sepsis phenotype characterized by inflammation, renal dysfunction, endotheliopathy, and immunosuppression, as well as poor short-term and long-term clinical outcomes.

Subphenotypes in acute kidney injury: a narrative review

Acute kidney injury (AKI) is a frequently encountered syndrome especially among the critically ill. Current diagnosis of AKI is based on acute deterioration of kidney function, indicated by an increase in creatinine and/or reduced urine output. However, this syndromic definition encompasses a wide variety of distinct clinical features, varying pathophysiology, etiology and risk factors, and finally very different short- and long-term outcomes. Lumping all AKI together may conceal unique pathophysiologic processes specific to certain AKI populations, and discovering these AKI subphenotypes might help to develop targeted therapies tackling unique pathophysiological processes. In this review, we discuss the concept of AKI subphenotypes, current knowledge regarding both clinical and biomarker-driven subphenotypes, interplay with AKI subphenotypes and other ICU syndromes, and potential future and clinical implications.

The pharmacotherapeutic options in patients with catecholamine-resistant vasodilatory shock

INTRODUCTION

Septic and vasoplegic shock are common types of vasodilatory shock (VS) with high mortality. After fluid resuscitation and the use of catecholamine-mediated vasopressors (CMV), vasopressin, angiotensin II, methylene blue (MB) and hydroxocobalamin can be added to maintain blood pressure.

AREAS COVERED

VS treatment utilizes a phased approach with secondary vasopressors added to vasopressor agents to maintain an acceptable mean arterial pressure (MAP). This review covers additional vasopressors and adjunctive therapies used when fluid and catecholamine-mediated vasopressors fail to maintain target MAP.

EXPERT OPINION

Evidence supporting additional vasopressor agents in catecholamine resistant VS is limited to case reports, series, and a few randomized control trials (RCTs) to guide recommendations. Vasopressin is the most common agent added next when MAPs are not adequately supported with CMV. VS patients failing fluids and vasopressors with cardiomyopathy may have cardiotonic agents such as dobutamine or milrinone added before or after vasopressin. Angiotensin II, another class of vasopressor is used in VS to maintain adequate MAP. MB and/or hydoxocobalamin, vitamin C, thiamine and corticosteroids are adjunctive therapies used in refractory VS. More RCTs are needed to confirm the utility of these drugs, at what doses, which combinations and in what order they should be given.

Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study

BACKGROUND

While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as 'mild', 'moderate' or 'severe' based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights.

METHODS

We developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation.

RESULTS

Six stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with 'moderate' TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with 'severe' GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (both p < 0.001).

CONCLUSIONS

Six stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care. Trial registration The core study was registered with ClinicalTrials.gov, number NCT02210221 , registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582).

The landscape of isoform switches in sepsis: a multicenter cohort study

Sepsis is caused by an uncontrolled inflammatory response, whose underlying mechanisms are not fully understood. It is well known that the majority of human genes can be expressed as alternative isoforms. While isoform switching is implicated in many diseases and is particularly prominent in cancer, it has never been reported in the context of sepsis. Patients presented to the emergency department of three tertiary care hospitals from January 2020 to December 2020 were enrolled. Clinical variables and genome-wide transcriptome of peripheral blood mononuclear cells (PBMC) were obtained. Isoform switching analysis were performed to identify significant isoform switches and relevant biological consequences. A total of 48 subjects with sepsis, involving 42 survivors and 6 non-survivors, admitted to the emergency department of three tertiary care hospitals were enrolled in this study. PBMCs were extracted for RNA sequencing (RNA-seq). Patients (n = 4) with mild stroke or acute coronary syndrome without infection were enrolled in this study as controls. The most frequent functional changes resulting from isoform switching were changes affecting the open reading frame, protein domains and intron retention. Many genes without differences in gene expression showed significant isoform switching. Many genes with significant isoform switches ([Formula: see text]> 0.1) were associated with higher mortality risk, including PIGS, CASP3, LITAF, HBB and RUVBL2. The study for the first time described the landscape of isoform switching in sepsis, including differentially expressed isoform fractions between patients with and without sepsis and survivors and nonsurvivors. The biological consequences of isoform switching, including protein domain loss, signal peptide gain, and intron retention, were identified.

Redefining critical illness

Research and practice in critical care medicine have long been defined by syndromes, which, despite being clinically recognizable entities, are, in fact, loose amalgams of heterogeneous states that may respond differently to therapy. Mounting translational evidence-supported by research on respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-suggests that the current syndrome-based framework of critical illness should be reconsidered. Here we discuss recent findings from basic science and clinical research in critical care and explore how these might inform a new conceptual model of critical illness. De-emphasizing syndromes, we focus on the underlying biological changes that underpin critical illness states and that may be amenable to treatment. We hypothesize that such an approach will accelerate critical care research, leading to a richer understanding of the pathobiology of critical illness and of the key determinants of patient outcomes. This, in turn, will support the design of more effective clinical trials and inform a more precise and more effective practice at the bedside.

Warm autoimmune haemolytic anaemia seen in association with primary sclerosing cholangitis in the setting of Klebsiella pneumoniae bacteraemia

Warm autoimmune haemolytic anaemia mediated by warm agglutinins is a rare and heterogeneous disease which can be idiopathic or secondary to an underlying disease. Primary sclerosing cholangitis is a chronic autoimmune cholangiopathy that is very rarely associated with haemolytic anaemia. Infections can also act as triggers for immune haemolytic anaemia. Here, we report a case of a woman in her 50s with a history of primary sclerosing cholangitis and a positive direct antiglobulin test with no evidence of haemolysis who developed overt warm autoimmune haemolytic anaemia in the setting of cholangitis and Klebsiella pneumoniae bacteraemia. She was treated conservatively with appropriate antibiotics and cautious red blood cell transfusion with complete resolution of haemolysis; immunosuppression was avoided given sepsis on presentation. This case highlights a rare association of warm immune haemolytic anaemia in the setting of K. pneumoniae bacteraemia and the role of a tailored treatment approach to treat this heterogeneous disease.

Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response

Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies.

Methods for Phenotyping Adult Patients in Sepsis and Septic Shock: A Scoping Review

Despite its heterogeneous phenotypes, sepsis or life-threatening dysfunction in response to infection is often treated empirically. Identifying patient subgroups with unique pathophysiology and treatment response is critical to the advancement of sepsis care. However, phenotyping methods and results are as heterogeneous as the disease itself. This scoping review evaluates the prognostic capabilities and treatment implications of adult sepsis and septic shock phenotyping methods.

DATA SOURCES

Medline and Embase.

STUDY SELECTION

We included clinical studies that described sepsis or septic shock and used any clustering method to identify sepsis phenotypes. We excluded conference abstracts, literature reviews, comments, letters to the editor, and in vitro studies. We assessed study quality using a validated risk of bias tool for observational cohort and cross-sectional studies.

DATA EXTRACTION

We extracted population, methodology, validation, and phenotyping characteristics from 17 studies.

DATA SYNTHESIS

Sepsis phenotyping methods most frequently grouped patients based on the degree of inflammatory response and coagulopathy using clinical, nongenomic variables. Five articles clustered patients based on genomic or transcriptomic data. Seven articles generated patient subgroups with differential response to sepsis treatments. Cluster clinical characteristics and their associations with mortality and treatment response were heterogeneous across studies, and validity was evaluated in nine of 17 articles, hindering pooled analysis of results and derivation of universal truths regarding sepsis phenotypes, their prognostic capabilities, and their associations with treatment response.

CONCLUSIONS

Sepsis phenotyping methods can identify high-risk patients and those with high probability of responding well to targeted treatments. Research quality was fair, but achieving generalizability and clinical impact of sepsis phenotyping will require external validation and direct comparison with alternative approaches.

Endotypes and the Path to Precision in Moderate and Severe Traumatic Brain Injury

Heterogeneity is recognized as a major barrier in efforts to improve the care and outcomes of patients with traumatic brain injury (TBI). Even within the narrower stratum of moderate and severe TBI, current management approaches do not capture the complexity of this condition characterized by manifold clinical, anatomical, and pathophysiologic features. One approach to heterogeneity may be to resolve undifferentiated TBI populations into endotypes, subclasses that are distinguished by shared biological characteristics. The endotype paradigm has been explored in a range of medical domains, including psychiatry, oncology, immunology, and pulmonology. In intensive care, endotypes are being investigated for syndromes such as sepsis and acute respiratory distress syndrome. This review provides an overview of the endotype paradigm as well as some of its methods and use cases. A conceptual framework is proposed for endotype research in moderate and severe TBI, together with a scientific road map for endotype discovery and validation in this population.

A Standardized Step-by-Step Approach for the Diagnosis and Treatment of Sepsis

Sepsis is the major culprit of death among critically ill patients who are hospitalized in intensive care units (ICUs). Although sepsis-related mortality is steadily declining year-by-year due to the continuous understanding of the pathophysiological mechanism on sepsis and improvement of the bundle treatment, sepsis-associated hospitalization is rising worldwide. Surviving Sepsis Campaign (SSC) guidelines are continuously updating, while their content is extremely complex and comprehensive for a precisely implementation in clinical practice. As a consequence, a standardized step-by-step approach for the diagnosis and treatment of sepsis is particularly important. In the present study, we proposed a standardized step-by-step approach for the diagnosis and treatment of sepsis using our daily clinical experience and the latest researches, which is close to clinical practice and is easy to implement. The proposed approach may assist clinicians to more effectively diagnose and treat septic patients and avoid the emergence of adverse clinical outcomes.

Gene Expression Scoring of Immune Activity Levels for Precision Use of Hydrocortisone in Vasodilatory Shock

PURPOSE

Among patients with vasodilatory shock, gene expression scores may identify different immune states. We aimed to test whether such scores are robust in identifying patients' immune state and predicting response to hydrocortisone treatment in vasodilatory shock.

MATERIALS AND METHODS

We selected genes to generate continuous scores to define previously established subclasses of sepsis. We used these scores to identify a patient's immune state. We evaluated the potential for these states to assess the differential effect of hydrocortisone in two randomized clinical trials of hydrocortisone versus placebo in vasodilatory shock.

RESULTS

We initially identified genes associated with immune-adaptive, immune-innate, immune-coagulant functions. From these genes, 15 were most relevant to generate expression scores related to each of the functions. These scores were used to identify patients as immune-adaptive prevalent (IA-P) and immune-innate prevalent (IN-P). In IA-P patients, hydrocortisone therapy increased 28-day mortality in both trials (43.3% vs 14.7%, P = 0.028) and (57.1% vs 0.0%, P = 0.99). In IN-P patients, this effect was numerically reversed.

CONCLUSIONS

Gene expression scores identified the immune state of vasodilatory shock patients, one of which (IA-P) identified those who may be harmed by hydrocortisone. Gene expression scores may help advance the field of personalized medicine.

LPIN1 Is a Regulatory Factor Associated With Immune Response and Inflammation in Sepsis

Objectives

Sepsis is a clinical disease that is typically treated in the intensive care unit, and the complex pathophysiology under this disease has not been thoroughly understood. While ferroptosis is involved in inflammation and infection, its effect in sepsis is still unknown. The study aimed to identify ferroptosis-related genes in sepsis, providing translational potential therapeutic targets.

Methods

The dataset GSE65682 was used to download the sample source from the Gene Expression Omnibus (GEO) database. Consensus weighted gene co-expression network analysis (WGCNA) was performed to find suspected modules of sepsis. The differentially expressed genes (DEGs) most significantly associated with mortality were intersected with those altered by lipopolysaccharide (LPS) treatment and were further analyzed for the identification of main pathways of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The related pathway markers were further verified by qPCR.

Results

A total of 802 blood samples with sepsis were included for WGCNA, which identified 21 modules. Intersected with ferroptosis databases and LPS treatment groups, we identified two ferroptosis-related genes: PEBP1 and LPIN1. Only LPIN1 contributes to a poor outcome. Then, 205 DEGs were further identified according to the high or low LPIN1 expression. Among them, we constructed a gene regulatory network with several transcriptional factors using the NetworkAnalyst online tool and identified that these genes mostly correlate with inflammation and immune response. The immune infiltration analysis showed that lower expression of LPIN1 was related to macrophage infiltration and could be an independent predictor factor of the survival status in sepsis patients. Meanwhile, the multivariate Cox analysis showed that LPIN1 had a significant correlation with survival that was further verified by in vitro and in vivo experiments.

Conclusion

In conclusion, LPIN1 could become a reliable biomarker for patient survival in sepsis, which is associated with immune and inflammation status.

Multidimensional analysis of the host response reveals prognostic and pathogen-driven immune subtypes among adults with sepsis in Uganda

Background

The global burden of sepsis is concentrated in sub-Saharan Africa, where severe infections disproportionately affect young, HIV-infected adults and high-burden pathogens are unique. In this context, poor understanding of sepsis immunopathology represents a crucial barrier to development of locally-effective treatment strategies. We sought to determine inter-individual immunologic heterogeneity among adults hospitalized with sepsis in a sub-Saharan African setting, and characterize associations between immune subtypes, infecting pathogens, and clinical outcomes.

Methods

Among a prospective observational cohort of 288 adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to 14 soluble host immune mediators, reflective of key domains of sepsis immunopathology (innate and adaptive immune activation, endothelial dysfunction, fibrinolysis), to identify immune subtypes in randomly-split discovery (N = 201) and internal validation (N = 87) sub-cohorts. In parallel, we applied similar methods to whole-blood RNA-sequencing data from a consecutive subset of patients (N = 128) to identify transcriptional subtypes, which we characterized using biological pathway and immune cell-type deconvolution analyses.

Results

Unsupervised clustering consistently identified two immune subtypes defined by differential activation of pro-inflammatory innate and adaptive immune pathways, with transcriptional evidence of concomitant CD56(-)/CD16( +) NK-cell expansion, T-cell exhaustion, and oxidative-stress and hypoxia-induced metabolic and cell-cycle reprogramming in the hyperinflammatory subtype. Immune subtypes defined by greater pro-inflammatory immune activation, T-cell exhaustion, and metabolic reprogramming were consistently associated with a high-prevalence of severe and often disseminated HIV-associated tuberculosis, as well as more extensive organ dysfunction, worse functional outcomes, and higher 30-day mortality.

Conclusions

Our results highlight unique host- and pathogen-driven features of sepsis immunopathology in sub-Saharan Africa, including the importance of severe HIV-associated tuberculosis, and reinforce the need to develop more biologically-informed treatment strategies in the region, particularly those incorporating immunomodulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-03907-3.

Managing sepsis in the era of precision medicine: challenges and opportunities

INTRODUCTION

Precision medicine is a medical model in which decisions, practices, interventions and therapies are tailored to the individual patient based on their predicted response or risk of disease. Sepsis is a life-threatening condition characterized by immune system dysregulation whose pathophysiology remains incompletely understood. There is much hope that precision medicine can lead to better outcomes in patients with sepsis.

AREAS COVERED

In this review from a comprehensive literature search in PubMed for English-language studies conducted in adults, we highlight recent advances in the diagnosis and treatment of sepsis of bacterial origin in adults using precision medicine approaches including rapid diagnostic tests, predictive biomarkers, genomic methods, rapid antimicrobial susceptibility testing, and monitoring cell mediated immunity. Challenges and directions for future research are also discussed.

EXPERT OPINION

Current diagnostic testing in sepsis relies primarily on conventional cultures (e.g. blood cultures), which are time-consuming and may delay critical therapeutic decisions. Nonculture-based techniques including nucleic acid amplification technologies (NAAT), other molecular methods (biomarkers), and genomic sequencing offer promise to overcome some of the inherent limitations seen with culture-based techniques.

Using RNA-Seq to Investigate Immune-Metabolism Features in Immunocompromised Patients With Sepsis

Objective: Sepsis is life threatening and leads to complex inflammation in patients with immunocompromised conditions, such as cancer, and receiving immunosuppressants for autoimmune diseases and organ transplant recipients. Increasing evidence has shown that RNA-Sequencing (RNA-Seq) can be used to define subendotype in patients with sepsis; therefore, we aim to use RNA-Seq to identify transcriptomic features among immunocompromised patients with sepsis.

Methods: We enrolled patients who were admitted to medical intensive care units (ICUs) for sepsis at a tertiary referral centre in central Taiwan. Whole blood on day-1 and day-8 was obtained for RNA-Seq. We used Gene Set Enrichment Analysis (GSEA) to identify the enriched pathway of day-8/day-1 differentially expressed genes and MiXCR to determine the diversity of T cell repertoire.

Results: A total of 18 immunocompromised subjects with sepsis and 18 sequential organ failure assessment (SOFA) score-matched immunocompetent control subjects were enrolled. The ventilator-day, ICU-stay, and hospital-day were similar between the two groups, whereas the hospital mortality was higher in immunocompromised patients than those in immunocompetent patients (50.0 vs. 5.6%, p < 0.01). We found that the top day-8/day-1 upregulated genes in the immunocompetent group were mainly innate immunity and inflammation relevant genes, namely, PRSS33, HDC, ALOX15, FCER1A, and OLR1, whereas a blunted day-8/day-1 dynamic transcriptome was found among immunocompromised patients with septic. Functional pathway analyses of day-8/day-1 differentially expressed genes identified the upregulated functional biogenesis and T cell-associated pathways in immunocompetent patients recovered from sepsis, whereas merely downregulated metabolism-associated pathways were found in immunocompromised patients with septic. Moreover, we used MiXCR to identify a higher diversity of T cell receptor (TCR) in immunocompetent patients both on day-1 and on day-8 than those in immunocompromised patients.

Conclusions: Using RNA-Seq, we found compromised T cell function, altered metabolic signalling, and decreased T cell diversity among immunocompromised patients with septic, and more mechanistic studies are warranted to elucidate the underlying mechanism.

Low-dose corticosteroid therapy for cardiogenic shock in adults (COCCA): study protocol for a randomized controlled trial

Background

Cardiogenic shock (CS) is a life-threatening condition characterized by circulatory insufficiency caused by an acute dysfunction of the heart pump. The pathophysiological approach to CS has recently been enriched by the tissue consequences of low flow, including inflammation, endothelial dysfunction, and alteration of the hypothalamic-pituitary-adrenal axis. The aim of the present trial is to evaluate the impact of early low-dose corticosteroid therapy on shock reversal in adults with CS.

Method/design

This is a multicentered randomized, double-blind, placebo-controlled trial with two parallel arms in adult patients with CS recruited from medical, cardiac, and polyvalent intensive care units (ICU) in France. Patients will be randomly allocated into the treatment or control group (1:1 ratio), and we will recruit 380 patients (190 per group). For the treatment group, hydrocortisone (50 mg intravenous bolus every 6 h) and fludrocortisone (50 μg once a day enterally) will be administered for 7 days or until discharge from the ICU. The primary endpoint is catecholamine-free days at day 7. Secondary endpoints include morbidity and all-cause mortality at 28 and 90 days post-randomization. Pre-defined subgroups analyses are planned, including: postcardiotomy, myocardial infarction, etomidate use, vasopressor use, and adrenal profiles according the short corticotropin stimulation test. Each patient will be followed for 90 days. All analyses will be conducted on an intention-to-treat basis.

Discussion

This trial will provide valuable evidence about the effectiveness of low dose of corticosteroid therapy for CS. If effective, this therapy might improve outcome and become a therapeutic adjunct for patients with CS.

Trial registration

ClinicalTrials.gov, NCT03773822. Registered on 12 December 2018

Construction and validation of a robust prognostic model based on immune features in sepsis

Purpose

Sepsis, with life-threatening organ failure, is caused by the uncontrolled host response to infection. Immune response plays an important role in the pathophysiology of sepsis. Immune-related genes (IRGs) are promising novel biomarkers that have been used to construct the diagnostic and prognostic model. However, an IRG prognostic model used to predict the 28-day mortality in sepsis was still limited. Therefore, the study aimed to develop a prognostic model based on IRGs to identify patients with high risk and predict the 28-day mortality in sepsis. Then, we further explore the circulating immune cell and immunosuppression state in sepsis.

Materials and methods

The differentially expressed genes (DEGs), differentially expressed immune-related genes (DEIRGs), and differentially expressed transcription factors (DETFs) were obtained from the GEO, ImmPort, and Cistrome databases. Then, the TFs-DEIRGs regulatory network and prognostic prediction model were constructed by Cox regression analysis and Pearson correlation analysis. The external datasets also validated the reliability of the prognostic model. Based on the prognostic DEIRGs, we developed a nomogram and conducted an independent prognosis analysis to explore the relationship between DEIRGs in the prognostic model and clinical features in sepsis. Besides, we further evaluate the circulating immune cells state in sepsis.

Results

A total of seven datasets were included in our study. Among them, GSE65682 was identified as a discovery cohort. The results of GSEA showed that there is a significant correlation between sepsis and immune response. Then, based on a P value <0.01, 69 prognostic DEIRGs were obtained and the potential molecular mechanisms of DEIRGs were also clarified. According to multivariate Cox regression analysis, 22 DEIRGs were further identified to construct the prognostic model and identify patients with high risk. The Kaplan-Meier survival analysis showed that high-risk groups have higher 28-day mortality than low-risk groups (P=1.105e-13). The AUC value was 0.879 which symbolized that the prognostic model had a better accuracy to predict the 28-day mortality. The external datasets also prove that the prognostic model had an excellent prediction value. Furthermore, the results of correlation analysis showed that patients with Mars1 might have higher risk scores than Mars2-4 (P=0.002). According to the previous study, Mars1 endotype was characterized by immunoparalysis. Thus, the sepsis patients in high-risk groups might exist the immunosuppression. Between the high-risk and low-risk groups, circulating immune cells types were significantly different, and risk score was significantly negatively correlated with naive CD4+ T cells (P=0.019), activated NK cells (P=0.0045), monocytes (P=0.0134), and M1 macrophages (P=0.0002).

Conclusions

Our study provides a robust prognostic model based on 22 DEIRGs which can predict 28-day mortality and immunosuppression status in sepsis. The higher risk score was positively associated with 28-day mortality and the development of immunosuppression. IRGs are a promising biomarker that might facilitate personalized treatments for sepsis.

Pediatric sepsis biomarkers for prognostic and predictive enrichment

Sepsis is a major public health problem in children throughout the world. Given that the treatment guidelines emphasize early recognition, there is interest in developing biomarkers of sepsis, and most attention is focused on diagnostic biomarkers. While there is a need for ongoing discovery and development of diagnostic biomarkers for sepsis, this review will focus on less well-known applications of sepsis biomarkers. Among patients with sepsis, the biomarkers can give information regarding the risk of poor outcome from sepsis, risk of sepsis-related organ dysfunction, and subgroups of patients with sepsis who share underlying biological features potentially amenable to targeted therapeutics. These types of biomarkers, beyond the traditional concept of diagnosis, address the important concepts of prognostic and predictive enrichment, which are key components of bringing the promise of precision medicine to the bedside of children with sepsis.

Monocyte Trajectories Endotypes Are Associated With Worsening in Septic Patients

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. The immune system plays a key role in sepsis onset and remains dysregulated over time in a heterogeneous manner. Here, we decipher the heterogeneity of the first week evolution of the monocyte HLA-DR (mHLA-DR) surface protein expression in septic patients, a key molecule for adaptive immunity onset. We found and verified four distinctive trajectories endotypes in a discovery (n = 276) and a verification cohort (n = 102). We highlight that 59% of septic patients exhibit low or decreasing mHLA-DR expression while in others mHLA-DR expression increased. This study depicts the first week behavior of mHLA-DR over time after sepsis onset and shows that initial and third day mHLA-DR expression measurements is sufficient for an early risk stratification of sepsis patients. These patients might benefit from immunomodulatory treatment to improve outcomes. Going further, our study introduces a way of deciphering heterogeneity of immune system after sepsis onset which is a first step to reach a more comprehensive landscape of 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.

What Is the Role of Steroids for Septic Shock in 2021?

Corticosteroids have been used for decades in the adjunctive treatment of severe infections in intensive care. The most frequent scenario in intensive care is in septic shock, where low doses of glucocorticoids appear to restore vascular responsiveness to norepinephrine. There is a strong body of evidence suggesting that hydrocortisone reduces time on vasopressor, and may modulate the immune response. In this review, we explore the current evidence supporting the use of corticosteroids in septic shock, its benefits, and potential harms. In addition to landmark clinical trials, we will also describe new frontiers for the use of corticosteroids in septic shock which should be explored in future studies.

Secondary pneumonias in critically ill patients with COVID-19: risk factors and outcomes

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the current evidence of secondary pneumonias in COVID-19 patients, its incidence, risk factors and impact outcomes.

RECENT FINDINGS

Early studies reported low incidence of hospital-acquired infections in COVID-19 patients. More recent large studies clearly showed that the incidence of secondary pneumonias was markedly high in patients under mechanical ventilation. Duration of mechanical ventilation, acute respiratory distress syndrome, prone position and male sex were identified as risk factors. The adjunctive therapy with steroids and immunomodulators were associated with a higher risk of pneumonia and invasive pulmonary Aspergillosis. Although secondary pneumonias seemed to be associated with poor outcomes, namely mortality, in comparison with influenza, no difference was found in heterogeneity of outcomes. Immunosuppressive therapy has been studied in several observational and randomized trials with conflicting results and the true impact on superinfections, namely secondary pneumonias, has not been properly assessed.

SUMMARY

According to the current evidence, COVID-19 patients are at an increased risk of secondary pneumonias. The impact of immunosuppressive therapies on superinfections is yet to be determined. Further studies are needed to assess the true risk of secondary infections associated with immunosuppressive therapies and to identify preventive strategies.

Genetics of Acute Respiratory Distress Syndrome: Pathways to Precision

Clinical risk factors alone fail to fully explain acute respiratory distress syndrome (ARDS) risk or ARDS death, suggesting that individual risk factors contribute. The goals of genomic ARDS studies include better mechanistic understanding, identifying dysregulated pathways that may be amenable to pharmacologic targeting, using genomic causal inference techniques to find measurable traits with meaning, and deconvoluting ARDS heterogeneity by proving reproducible subpopulations that may share a unique biology. This article discusses the latest advances in ARDS genomics, provides historical perspective, and highlights some of the ways that the coronavirus disease 2019 (COVID-19) pandemic is accelerating genomic ARDS research.

Metatranscriptomic Characterization of Coronavirus Disease 2019 Identified a Host Transcriptional Classifier Associated With Immune Signaling

BACKGROUND

The recent identification of a novel coronavirus, also known as SARS-CoV-2, has caused a global outbreak of respiratory illnesses. The rapidly developing pandemic has posed great challenges to diagnosis of this novel infection. However, little is known about the metatranscriptomic characteristics of patients with Coronavirus Disease 2019 (COVID-19).

METHODS

We analyzed metatranscriptomics in 187 patients (62 cases with COVID-19 and 125 with non-COVID-19 pneumonia). Transcriptional aspects of three core elements – pathogens, the microbiome, and host responses – were interrogated. Based on the host transcriptional signature, we built a host gene classifier and examined its potential for diagnosing COVID-19 and indicating disease severity.

RESULTS

The airway microbiome in COVID-19 patients had reduced alpha diversity, with 18 taxa of differential abundance. Potentially pathogenic microbes were also detected in 47% of the COVID-19 cases, 58% of which were respiratory viruses. Host gene analysis revealed a transcriptional signature of 36 differentially expressed genes significantly associated with immune pathways such as cytokine signaling. The host gene classifier built on such a signature exhibited potential for diagnosing COVID-19 (AUC of 0.75-0.89) and indicating disease severity.

CONCLUSIONS

Compared to those with non-COVID-19 pneumonias, COVID-19 patients appeared to have a more disrupted airway microbiome with frequent potential concurrent infections, and a special trigger host immune response in certain pathways such as interferon gamma signaling. The immune-associated host transcriptional signatures of COVID-19 hold promise as a tool for improving COVID-19 diagnosis and indicating disease severity.