Validation of a gene expression-based subclassification strategy for pediatric septic shock

Definition and Epidemiology of Sepsis

Here we review the epidemiology of sepsis, focusing on its definition, incidence, and mortality, as well as the demographic insights and risk factors that influence its occurrence and outcomes. We address how age, sex, and racial/ethnic disparities impact upon incidence and mortality rates. Sepsis is more frequent and severe among the elderly, males, and certain racial and ethnic groups. Poor socioeconomic status, geographic location, and pre-existing comorbidities also elevate the risk of developing and dying from sepsis. Seasonal variations, with an increased incidence during winter months, is also apparent. We delve into the predictive value of disease severity scores such as the Sequential Organ Failure Assessment score. We also highlight issues relating to coding and administrative data that can generate erroneous and misleading information, and the need for greater consistency. The Sepsis-3 definitions, offering more precise clinical criteria, are a step in the right direction. This overview will, we hope, facilitate understanding of the multi-faceted epidemiological characteristics of sepsis and current challenges.

Biological basis of critical illness subclasses: from the bedside to the bench and back again

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.

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.

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

Circulating N-lactoyl-amino acids and N-formyl-methionine reflect mitochondrial dysfunction and predict mortality in septic shock

INTRODUCTION

Sepsis is a highly morbid condition characterized by multi-organ dysfunction resulting from dysregulated inflammation in response to acute infection. Mitochondrial dysfunction may contribute to sepsis pathogenesis, but quantifying mitochondrial dysfunction remains challenging.

OBJECTIVE

To assess the extent to which circulating markers of mitochondrial dysfunction are increased in septic shock, and their relationship to severity and mortality.

METHODS

We performed both full-scan and targeted (known markers of genetic mitochondrial disease) metabolomics on plasma to determine markers of mitochondrial dysfunction which distinguish subjects with septic shock (n = 42) from cardiogenic shock without infection (n = 19), bacteremia without sepsis (n = 18), and ambulatory controls (n = 19) - the latter three being conditions in which mitochondrial function, proxied by peripheral oxygen consumption, is presumed intact.

RESULTS

Nine metabolites were significantly increased in septic shock compared to all three comparator groups. This list includes N-formyl-L-methionine (f-Met), a marker of dysregulated mitochondrial protein translation, and N-lactoyl-phenylalanine (lac-Phe), representative of the N-lactoyl-amino acids (lac-AAs), which are elevated in plasma of patients with monogenic mitochondrial disease. Compared to lactate, the clinical biomarker used to define septic shock, there was greater separation between survivors and non-survivors of septic shock for both f-Met and the lac-AAs measured within 24 h of ICU admission. Additionally, tryptophan was the one metabolite significantly decreased in septic shock compared to all other groups, while its breakdown product kynurenate was one of the 9 significantly increased.

CONCLUSION

Future studies which validate the measurement of lac-AAs and f-Met in conjunction with lactate could define a sepsis subtype characterized by mitochondrial dysfunction.

Immune and metabolic markers for identifying and investigating severe Coronavirus disease and Sepsis in children and young people (pSeP/COVID ChYP study): protocol for a prospective cohort study

INTRODUCTION

Early recognition and appropriate management of paediatric sepsis are known to improve outcomes. A previous system's biology investigation of the systemic immune response in neonates to sepsis identified immune and metabolic markers that showed high accuracy for detecting bacterial infection. Further gene expression markers have also been reported previously in the paediatric age group for discriminating sepsis from control cases. More recently, specific gene signatures were identified to discriminate between COVID-19 and its associated inflammatory sequelae. Through the current prospective cohort study, we aim to evaluate immune and metabolic blood markers which discriminate between sepses (including COVID-19) from other acute illnesses in critically unwell children and young persons, up to 18 years of age.

METHODS AND ANALYSIS

We describe a prospective cohort study for comparing the immune and metabolic whole-blood markers in patients with sepsis, COVID-19 and other illnesses. Clinical phenotyping and blood culture test results will provide a reference standard to evaluate the performance of blood markers from the research sample analysis. Serial sampling of whole blood (50 μL each) will be collected from children admitted to intensive care and with an acute illness to follow time dependent changes in biomarkers. An integrated lipidomics and RNASeq transcriptomics analyses will be conducted to evaluate immune-metabolic networks that discriminate sepsis and COVID-19 from other acute illnesses. This study received approval for deferred consent.

ETHICS AND DISSEMINATION

The study has received research ethics committee approval from the Yorkshire and Humber Leeds West Research Ethics Committee 2 (reference 20/YH/0214; IRAS reference 250612). Submission of study results for publication will involve making available all anonymised primary and processed data on public repository sites.

TRIAL REGISTRATION NUMBER

NCT04904523.

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.

Refining empiric subgroups of pediatric sepsis using machine-learning techniques on observational data

Sepsis contributes to 1 of every 5 deaths globally with 3 million per year occurring in children. To improve clinical outcomes in pediatric sepsis, it is critical to avoid "one-size-fits-all" approaches and to employ a precision medicine approach. To advance a precision medicine approach to pediatric sepsis treatments, this review provides a summary of two phenotyping strategies, empiric and machine-learning-based phenotyping based on multifaceted data underlying the complex pediatric sepsis pathobiology. Although empiric and machine-learning-based phenotypes help clinicians accelerate the diagnosis and treatments, neither empiric nor machine-learning-based phenotypes fully encapsulate all aspects of pediatric sepsis heterogeneity. To facilitate accurate delineations of pediatric sepsis phenotypes for precision medicine approach, methodological steps and challenges are further highlighted.

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.

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.

Integrated PERSEVERE and endothelial biomarker risk model predicts death and persistent MODS in pediatric septic shock: a secondary analysis of a prospective observational study

Background

Multiple organ dysfunction syndrome (MODS) is a critical driver of sepsis morbidity and mortality in children. Early identification of those at risk of death and persistent organ dysfunctions is necessary to enrich patients for future trials of sepsis therapeutics. Here, we sought to integrate endothelial and PERSEVERE biomarkers to estimate the composite risk of death or organ dysfunctions on day 7 of septic shock.

Methods

We measured endothelial dysfunction markers from day 1 serum among those with existing PERSEVERE data. TreeNet® classification model was derived incorporating 22 clinical and biological variables to estimate risk. Based on relative variable importance, a simplified 6-biomarker model was developed thereafter.

Results

Among 502 patients, 49 patients died before day 7 and 124 patients had persistence of MODS on day 7 of septic shock. Area under the receiver operator characteristic curve (AUROC) for the newly derived PERSEVEREnce model to predict death or day 7 MODS was 0.93 (0.91–0.95) with a summary AUROC of 0.80 (0.76–0.84) upon tenfold cross-validation. The simplified model, based on IL-8, HSP70, ICAM-1, Angpt2/Tie2, Angpt2/Angpt1, and Thrombomodulin, performed similarly. Interaction between variables—ICAM-1 with IL-8 and Thrombomodulin with Angpt2/Angpt1—contributed to the models’ predictive capabilities. Model performance varied when estimating risk of individual organ dysfunctions with AUROCS ranging from 0.91 to 0.97 and 0.68 to 0.89 in training and test sets, respectively.

Conclusions

The newly derived PERSEVEREnce biomarker model reliably estimates risk of death or persistent organ dysfunctions on day 7 of septic shock. If validated, this tool can be used for prognostic enrichment in future pediatric trials of sepsis therapeutics.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04070-5.

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.

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.

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.

Differences in the Genomic Profiles of Immunoparalyzed and Nonimmunoparalyzed Children With Sepsis: A Pilot Study

OBJECTIVES

Sepsis-induced immunoparalysis represents a pathologic downregulation of leukocyte function shown to be associated with adverse outcomes, although its mechanisms remain poorly understood. Our goal was to compare genome-wide gene expression profiles of immunoparalyzed and nonimmunoparalyzed children with sepsis to identify genes and pathways associated with immunoparalysis.

DESIGN

Prospective observational study.

PATIENTS

Twenty-six children with lower respiratory tract infection meeting criteria for sepsis, severe sepsis, or septic shock admitted to the PICU.

SETTING

Two tertiary care PICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Innate immune function was assayed ex vivo by measuring release of tumor necrosis factor-α from whole blood after incubation with lipopolysaccharide for 4 hours. Immunoparalysis was defined as a tumor necrosis factor-α production capacity less than 200 pg/mL. Ten of the 26 children were immunoparalyzed. There were 17 significant differentially expressed genes when comparing genome-wide gene expression profiles of immunoparalyzed and nonimmunoparalyzed children (false discovery rate < 0.05). Nine genes showed increased expression in immunoparalyzed children (+1.5- to +8.8-fold change). Several of these dampen the immune system. Eight showed decreased expression in immunoparalyzed children (-1.7- to -3.9-fold change), several of which are involved in early regulation and activation of immune function. Functional annotation clustering using differentially expressed genes with p value of less than 0.05 showed three clusters related to immunity with significant enrichment scores (2.2-4.5); the most significant gene ontology terms in these clusters were antigen processing and presentation and negative regulation of interleukin-6 production. Network analysis identified potential protein interactions that may be involved in the development of immunoparalysis in children.

CONCLUSIONS

In this exploratory analysis, immunoparalyzed children with sepsis showed increased expression of genes that dampen the immune system and decreased expression of genes involved in regulation and activation of the immune system. Analysis also implicated other proteins as potentially having as yet unidentified roles in the development of immunoparalysis.

Impact of Inherited Genetic Variants on Critically Ill Septic Children

Sepsis remains an important source of morbidity and mortality in children, despite the development of standardized care. In the last decades, there has been an increased interest in genetic and genomic approaches to early recognition and development of treatments to manipulate the host inflammatory response. This review will present a summary of the normal host response to infection and progression to sepsis, followed by highlighting studies with a focus on gene association studies, epigenetics, and genome-wide expression profiling. The susceptibility (or outcome) of sepsis in children has been associated with several polymorphisms of genes broadly involved in inflammation, immunity, and coagulation. More recently, gene expression profiling has been focused on identifying novel biomarkers, pathways and therapeutic targets, and gene expression-based subclassification. Knowledge of a patient’s individual genotype may, in the not-too-remote future, be used to guide tailored treatment for sepsis. However, at present, the impact of genomics remains far from the bedside of critically ill children.

Precision medicine in sepsis and septic shock: From omics to clinical tools

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Multi-omic characterization of pediatric ARDS via nasal brushings

RATIONALE

While nasal brushing transcriptomics can identify disease subtypes in chronic pulmonary diseases, it is unknown whether this is true in pediatric acute respiratory distress syndrome (PARDS).

OBJECTIVES

Determine whether nasal transcriptomics and methylomics can identify clinically meaningful PARDS subgroups that reflect important pathobiological processes.

METHODS

Nasal brushings and serum were collected on days 1, 3, 7, and 14 from control and PARDS subjects from two centers. PARDS duration was the primary endpoint.

MEASUREMENTS AND MAIN RESULTS

Twenty-four control and 39 PARDS subjects were enrolled. Two nasal methylation patterns were identified. Compared to Methyl Subgroup 1, Subgroup 2 had hypomethylation of inflammatory genes and was enriched for immunocompromised subjects. Four transcriptomic patterns were identified with temporal patterns indicating injury, repair, and regeneration. Over time, both inflammatory (Subgroup B) and cell injury (Subgroup D) patterns transitioned to repair (Subgroup A) and eventually homeostasis (Subgroup C). When control specimens were included, they were largely Subgroup C. In comparison with 17 serum biomarkers, the nasal transcriptome was more predictive of prolonged PARDS. Subjects with initial Transcriptomic Subgroup B or D assignment had median PARDS duration of 8 days compared to 2 in A or C (p = 0.02). For predicting PARDS duration ≥ 3 days, nasal transcriptomics was more sensitive and serum biomarkers more specific.

CONCLUSIONS

PARDS nasal transcriptome may reflect distal lung injury, repair, and regeneration. A combined nasal PCR and serum biomarker assay could be useful for predictive and diagnostic enrichment. Trial registration Clinicaltrials.gov NCT03539783 May 29, 2018.

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.

Transcriptomic Profiles in Children With Septic Shock With or Without Immunoparalysis

Background

Severe innate immune suppression, termed immunoparalysis, is associated with increased risks of nosocomial infection and mortality in children with septic shock. Currently, immunoparalysis cannot be clinically diagnosed in children, and mechanisms remain unclear. Transcriptomic studies identify subsets of septic children with downregulation of genes within adaptive immune pathways, but assays of immune function have not been performed as part of these studies, and little is known about transcriptomic profiles of children with immunoparalysis.

Methods

We performed a nested case-control study to identify differences in RNA expression patterns between children with septic shock with immunoparalysis (defined as lipopolysaccharide (LPS)-induced tumor necrosis factor (TNF)α response < 200 pg/ml) vs those with normal LPS-induced TNFα response. Children were enrolled within 48 hours of the onset of septic shock and divided into two groups based on LPS-induced TNFα response. RNA was extracted from whole blood for RNAseq, differential expression analyses using DESeq2 software, and pathway analyses using Ingenuity Pathway Analysis.

Results

32 children were included in analyses. Comparing those with immunoparalysis (n =19) to those with normal TNFα response (n = 13), 2,303 transcripts were differentially expressed with absolute value fold change ≥ 1.5 and false discovery rate ≤ 0.05. The majority of downregulated pathways in children with immunoparalysis were pathways that involved interactions between innate and adaptive immune cells necessary for cell-mediated immunity, crosstalk between dendritic cells and natural killer cells, and natural killer cell signaling pathways. Upregulated pathways included those involved in humoral immunity (T helper cell type 2), corticotropin signaling, platelet activation (GP6 signaling), and leukocyte migration and extravasation.

Conclusions

Our study suggests that gene expression data might be useful to identify children with immunoparalysis and identifies several key differentially regulated pathways involved in both innate and adaptive immunity. Our ongoing work in this area aims to dissect interactions between innate and adaptive immunity in septic children and to more fully elucidate patient-specific immunologic pathophysiology to guide individualized immunotherapeutic targets.

The relationship between adrenocortical candidate gene expression and clinical response to hydrocortisone in patients with septic shock

PURPOSE

To determine if adrenocortical gene expression is associated with clinical outcomes or response to corticosteroid treatment in septic shock.

METHODS

A pre-specified nested cohort study of a randomised controlled trial of hydrocortisone compared to placebo in septic shock. Blood was collected for RNAseq analysis prior to treatment with hydrocortisone or placebo. The expression of adrenocortical candidate genes related to pituitary releasing hormones, mineralocorticoid and glucocorticoid receptors, intracellular glucocorticoid metabolism and transport proteins was measured.

RESULTS

From May 2014 to April 2017, 671 patients were enrolled in the nested cohort study, from which 494 samples were available for analysis. We found no evidence of an association between candidate gene expression levels and either 90-day mortality, 28-day mortality or time to shock reversal. We observed evidence of a significant interaction between expression and treatment group for time to shock reversal in two genes; GLCCI1 (HR 3.81, 95%CI 0.57-25.47 vs. HR 0.64, 95%CI 0.13-3.07 for hydrocortisone and placebo respectively, p for interaction 0.008) and BHSD1 (HR 0.55, 95%CI 0.28-1.09 vs. HR 1.32 95%CI 0.67-2.60, p for interaction 0.01).

CONCLUSIONS

In patients with septic shock, there is no association between adrenocortical candidate gene expression and mortality. Patients with higher expression of GLCCI1 who received hydrocortisone achieved shock resolution faster than those receiving placebo; conversely, patients who had higher expression of BHSD1 who received hydrocortisone achieved shock resolution slower than those who received placebo. Variation in gene expression may be a mechanism for heterogeneity of treatment response to corticosteroids in septic shock.

Proprotein Convertase Subtilisin/Kexin Type 9 Loss-of-Function Is Detrimental to the Juvenile Host With Septic Shock

OBJECTIVES

Proprotein convertase subtilisin/kexin type 9 is a central regulator of lipid metabolism and has been implicated in regulating the host response to sepsis. Proprotein convertase subtilisin/kexin type 9 loss-of-function is associated with improved sepsis outcomes in the adult host through increased hepatic bacterial clearance. Thus, there is interest in leveraging proprotein convertase subtilisin/kexin type 9 inhibitors as a therapeutic strategy in adults with sepsis. We sought to validate this association in children with septic shock and in a juvenile murine model of sepsis.

DESIGN

Prospectively enrolled cohort of children with septic shock; experimental mice.

SETTING

Seventeen participating institutions; research laboratory.

PATIENTS AND SUBJECTS

Five-hundred twenty-two children with septic shock; juvenile (14 d old) and adult (10-14 wk) mice with constitutive proprotein convertase subtilisin/kexin type 9 null and wildtype control mice (C57BL/6).

INTERVENTIONS

Proprotein convertase subtilisin/kexin type 9 single-nucleotide polymorphisms, serum proprotein convertase subtilisin/kexin type 9, and lipid profiles in patients. Cecal slurry murine model of sepsis; survival studies in juvenile and adult mice, assessment of lipoprotein fractions, bacterial burden, and inflammation in juvenile mice.

MEASUREMENTS AND MAIN RESULTS

PCSK9 loss-of-function genetic variants were independently associated with increased odds of complicated course and mortality in children with septic shock. PCSK9, low-density lipoprotein, and high-density lipoprotein concentrations were lower among patients with complicated course relative to those without. PCSK9 concentrations negatively correlated with proinflammatory cytokine interleukin-8. Proprotein convertase subtilisin/kexin type 9 loss-of-function decreased survival in juvenile mice, but increased survival in adult mice with sepsis. PCSK9 loss-of-function resulted in low lipoproteins and decreased hepatic bacterial burden in juvenile mice.

CONCLUSIONS

In contrast to the adult host, proprotein convertase subtilisin/kexin type 9 loss-of-function is detrimental to the juvenile host with septic shock. PCSK9 loss-of-function, in the context of low lipoproteins, may result in reduced hepatic bacterial clearance in the juvenile host with septic shock. Our data indicate that children should be excluded in sepsis clinical trials involving proprotein convertase subtilisin/kexin type 9 inhibitors.

Effect of zinc supplementation on relative expression of immune response genes in neonates with sepsis: A preliminary study

Background & objectives

Zinc alters gene expression mainly by binding to a site on the transcription factor. Genome-wide expression studies have shown early repression of genes related to zinc and immunity in adult patients with sepsis. The present study was conducted to evaluate the role of zinc supplementation on relative expression of immune response genes in neonatal sepsis.

Methods

In the present study, a sample of convenience of 22 neonates each was selected from the zinc supplemented and control groups using random numbers for expression of immune-related genes by zinc supplementation. These neonates with sepsis were earlier randomized into two groups: with and without zinc supplementation in addition to standard antibiotics and supportive care. Relative expression of immune response genes were analyzed for 22 neonates in each group using quantitative real-time PCR for calprotectin (S100A8/A9), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), toll-like receptor-4 (TLR-4), cluster of differentiation 14 (CD14) and lipopolysaccharide-binding protein (LBP) genes.

Results

An increase in serum zinc levels was observed in zinc-supplemented group compared to controls. S100A8 gene showed downregulation by three-fold (P <0.001) and S100A9 gene showed upregulation by two-fold (P <0.05) in zinc group compared to controls. CD14 gene showed upregulation by one-fold in zinc-supplemented group compared to controls (P <0.05). No significant fold changes were observed with respect to TNF-α, IL-6, LBP and TLR-4 genes between the two groups.

Interpretation & conclusions

The results of our preliminary study showed that the zinc supplementation might modulates the relative expression of immune-related genes involved in sepsis pathway among neonates. However, studies with larger sample size are needed to be done to provide a better picture on the outcome by gene expression in neonatal sepsis by zinc supplementation.

Hexosylceramides and Glycerophosphatidylcholine GPC(36:1) Increase in Multi-Organ Dysfunction Syndrome Patients with Pediatric Intensive Care Unit Admission over 8-Day Hospitalization

Glycero- and sphingo-lipids are important in plasma membrane structure, caloric storage and signaling. An un-targeted lipidomics approach for a cohort of critically ill pediatric intensive care unit (PICU) patients undergoing multi-organ dysfunction syndrome (MODS) was compared to sedation controls. After IRB approval, patients meeting the criteria for MODS were screened, consented (n = 24), and blood samples were collected from the PICU at HDVCH, Michigan; eight patients needed veno-arterial extracorporeal membrane oxygenation (VA ECMO). Sedation controls were presenting for routine sedation (n = 4). Plasma lipid profiles were determined by nano-electrospray (nESI) direct infusion high resolution/accurate mass spectrometry (MS) and tandem mass spectrometry (MS/MS). Biostatistics analysis was performed using R v 3.6.0. Sixty-one patient samples over three time points revealed a ceramide metabolite, hexosylceramide (Hex-Cer) was high across all time points (mean 1.63-3.19%; vs. controls 0.22%). Fourteen species statistically differentiated from sedation controls (p-value ≤ 0.05); sphingomyelin (SM) [SM(d18:1/23:0), SM(d18:1/22:0), SM(d18:1/23:1), SM(d18:1/21:0), SM(d18:1/24:0)]; and glycerophosphotidylcholine (GPC) [GPC(36:01), GPC(18:00), GPC(O:34:02), GPC(18:02), GPC(38:05), GPC(O:34:03), GPC(16:00), GPC(40:05), GPC(O:36:03)]. Hex-Cer has been shown to be involved in viral infection and may be at play during acute illness. GPC(36:01) was elevated in all MODS patients at all time points and is associated with inflammation and brain injury.

The Feasibility of Studying Metabolites in PICU Multi-Organ Dysfunction Syndrome Patients over an 8-Day Course Using an Untargeted Approach

Metabolites are generated from critical biological functions and metabolism. This pediatric study reviewed plasma metabolites in patients suffering from multi-organ dysfunction syndrome (MODS) in the pediatric intensive care unit (PICU) using an untargeted metabolomics approach. Patients meeting the criteria for MODS were screened for eligibility and consented (n = 24), and blood samples were collected at baseline, 72 h, and 8 days; control patients (n = 4) presented for routine sedation in an outpatient setting. A subset of MODS patients (n = 8) required additional support with veno-atrial extracorporeal membrane oxygenation (VA-ECMO) therapy. Metabolites from thawed blood plasma were determined from ion pairing reversed-phase liquid chromatography–mass spectrometry (LC-MS) analysis. Chromatographic peak alignment, identification, relative quantitation, and statistical and bioinformatics evaluation were performed using MAVEN and MetaboAnalyst 4.0. Metabolite analysis revealed 115 peaks per sample. From the partial least squares-discriminant analysis (PLS-DA) with variance of importance (VIP) scores above ≥2.0, 7 dynamic metabolites emerged over the three time points: tauro-chenodeoxycholic acid (TCDCA), hexose, p-hydroxybenzoate, hydroxyphenylacetic acid (HPLA), 2_3-dihydroxybenzoic acid, 2-keto-isovalerate, and deoxyribose phosphate. After Bonferroni adjustment for repeated measures, hexose and p-hydroxybenzoate were significant at one time point or more. Kendall’s tau-b test was used for internal validation of creatinine. Metabolites may be benign or significant in describing a patient’s pathophysiology and require operator interpretation.

A Precision Medicine Approach to Biomarker Utilization in Pediatric Sepsis-Associated Acute Kidney Injury

Sepsis is a leading cause of morbidity and mortality in critically ill children, and acute kidney injury (AKI) is a frequent complication that confers an increased risk for poor outcomes. Despite the documented consequences of sepsis-associated AKI (SA-AKI), no effective disease-modifying therapies have been identified to date. As such, the only treatment options for these patients remain prevention and supportive care, both of which rely on the ability to promptly and accurately identify at risk and affected individuals. To achieve these goals, a variety of biomarkers have been investigated to help augment our currently limited predictive and diagnostic strategies for SA-AKI, however, these have had variable success in pediatric sepsis. In this mini-review, we will briefly outline the current use of biomarkers for SA-AKI, and propose a new framework for biomarker discovery and utilization that considers the individual patient's sepsis inflammatory response. Now recognized to be a key driver in the complex pathophysiology of SA-AKI, understanding the dysregulated host immune response to sepsis is a growing area of research that can and should be leveraged to improve the prediction and diagnosis of SA-AKI, while also potentially identifying novel therapeutic targets. Reframing SA-AKI in this manner - as a direct consequence of the individual patient's sepsis inflammatory response - will facilitate a precision medicine approach to its management, something that is required to move the care of this consequential disorder forward.

Barriers and Proposed Solutions to a Successful Implementation of Pediatric Sepsis Protocols

The implementation of managed protocols contributes to a systematized approach to the patient and continuous evaluation of results, focusing on improving clinical practice, early diagnosis, treatment, and outcomes. Advantages to the adoption of a pediatric sepsis recognition and treatment protocol include: a reduction in time to start fluid and antibiotic administration, decreased kidney dysfunction and organ dysfunction, reduction in length of stay, and even a decrease on mortality. Barriers are: absence of a written protocol, parental knowledge, early diagnosis by healthcare professionals, venous access, availability of antimicrobials and vasoactive drugs, conditions of work, engagement of healthcare professionals. There are challenges in low-middle-income countries (LMIC). The causes of sepsis and resources differ from high-income countries. Viral agent such as dengue, malaria are common in LMIC and initial approach differ from bacterial infections. Some authors found increased or no impact in mortality or increased length of stay associated with the implementation of the SCC sepsis bundle which reinforces the importance of adapting it to most frequent diseases, disposable resources, and characteristics of healthcare professionals. Conclusions: (1) be simple; (2) be precise; (3) education; (5) improve communication; (5) work as a team; (6) share and celebrate results.

Leukocyte glucocorticoid receptor expression and related transcriptomic gene signatures during early sepsis

PURPOSE

The study aimed to understand the molecular mechanisms that might lead to differences in the glucocorticoid response during sepsis.

METHODS

Patients diagnosed with sepsis (n = 198) and 40 healthy controls were enrolled. Glucocorticoid receptor (GR) expression in circulating leukocytes and plasma levels of adrenocorticotropic hormone and cortisol on days 1 and 7 were measured in all participants. Expression profiling of 16 genes associated with GR expression in peripheral blood mononuclear cells (PBMCs) in 12 healthy controls and 26 patients with sepsis was performed by PCR.

RESULTS

Cortisol levels were higher in patients with sepsis than in healthy controls on day 1 after admission and recovered to normal levels by day 7. GR expression was gradually downregulated in leukocyte subsets. Non-survivors showed lower GR and higher cortisol levels than survivors. GRα expression was lower in patients with sepsis than in controls, whereas GRβ showed the opposite trend. MicroRNAs related to GR resistance and suppression were altered in PBMCs during sepsis.

CONCLUSION

Patients with sepsis showed upregulated plasma cortisol levels along with downregulated GR expression on various leukocyte subtypes, portending poor cortisol response and outcome. Changes in GR-regulatory miRNAs may be responsible for GR low expression.

Peripheral blood transcriptomic sub-phenotypes of pediatric acute respiratory distress syndrome

Background

Acute respiratory distress syndrome (ARDS) is heterogeneous and may be amenable to sub-phenotyping to improve enrichment for trials. We aimed to identify subtypes of pediatric ARDS based on whole blood transcriptomics.

Methods

This was a prospective observational study of children with ARDS at the Children’s Hospital of Philadelphia (CHOP) between January 2018 and June 2019. We collected blood within 24 h of ARDS onset, generated expression profiles, and performed k-means clustering to identify sub-phenotypes. We tested the association between sub-phenotypes and PICU mortality and ventilator-free days at 28 days using multivariable logistic and competing risk regression, respectively.

Results

We enrolled 106 subjects, of whom 96 had usable samples. We identified three sub-phenotypes, dubbed CHOP ARDS Transcriptomic Subtypes (CATS) 1, 2, and 3. CATS-1 subjects (n = 31) demonstrated persistent hypoxemia, had ten subjects (32%) with immunocompromising conditions, and 32% mortality. CATS-2 subjects (n = 29) had more immunocompromising diagnoses (48%), rapidly resolving hypoxemia, and 24% mortality. CATS-3 subjects (n = 36) had the fewest comorbidities and also had rapidly resolving hypoxemia and 8% mortality. The CATS-3 subtype was associated with lower mortality (OR 0.18, 95% CI 0.04–0.86) and higher probability of extubation (subdistribution HR 2.39, 95% CI 1.32–4.32), relative to CATS-1 after adjustment for confounders.

Conclusions

We identified three sub-phenotypes of pediatric ARDS using whole blood transcriptomics. The sub-phenotypes had divergent clinical characteristics and prognoses. Further studies should validate these findings and investigate mechanisms underlying differences between sub-phenotypes.

Machine learning based refined differential gene expression analysis of pediatric sepsis

Background

Differential expression (DE) analysis of transcriptomic data enables genome-wide analysis of gene expression changes associated with biological conditions of interest. Such analysis often provides a wide list of genes that are differentially expressed between two or more groups. In general, identified differentially expressed genes (DEGs) can be subject to further downstream analysis for obtaining more biological insights such as determining enriched functional pathways or gene ontologies. Furthermore, DEGs are treated as candidate biomarkers and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches.

Methods

In this work, we present a novel approach for identifying biomarkers from a list of DEGs by re-ranking them according to the Minimum Redundancy Maximum Relevance (MRMR) criteria using repeated cross-validation feature selection procedure.

Results

Using gene expression profiles for 199 children with sepsis and septic shock, we identify 108 DEGs and propose a 10-gene signature for reliably predicting pediatric sepsis mortality with an estimated Area Under ROC Curve (AUC) score of 0.89.

Conclusions

Machine learning based refinement of DE analysis is a promising tool for prioritizing DEGs and discovering biomarkers from gene expression profiles. Moreover, our reported 10-gene signature for pediatric sepsis mortality may facilitate the development of reliable diagnosis and prognosis biomarkers for sepsis.

Subphenotypes in critical care: translation into clinical practice

Despite progress in the supportive care available for critically ill patients, few advances have been made in the search for effective disease-modifying therapeutic options. The fact that many trials in critical care medicine have not identified a treatment benefit is probably due, in part, to the underlying heterogeneity of critical care syndromes. Numerous approaches have been proposed to divide populations of critically ill patients into more meaningful subgroups (subphenotypes), some of which might be more useful than others. Subclassification systems driven by clinical features and biomarkers have been proposed for acute respiratory distress syndrome, sepsis, acute kidney injury, and pancreatitis. Identifying the systems that are most useful and biologically meaningful could lead to a better understanding of the pathophysiology of critical care syndromes and the discovery of new treatment targets, and allow recruitment in future therapeutic trials to focus on predicted responders. This Review discusses proposed subphenotypes of critical illness syndromes and highlights the issues that will need to be addressed to translate subphenotypes into clinical practice.

Biomarker Panels in Critical Care

Biomarker panels have the potential to advance the field of critical care medicine by stratifying patients according to prognosis and/or underlying pathophysiology. This article discusses the discovery and validation of biomarker panels, along with their translation to the clinical setting. The current literature on the use of biomarker panels in sepsis, acute respiratory distress syndrome, and acute kidney injury is reviewed.

Development of a biomarker mortality risk model in acute respiratory distress syndrome

Background

There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.

Methods

This is a secondary analysis using a cohort of 252 mechanically ventilated subjects with the diagnosis of acute respiratory distress syndrome. Survival to day 7 with both day 0 (first day of presentation) and day 7 sample availability was required. Blood was collected for biomarker measurements at first presentation to the intensive care unit and on the seventh day. Biomarkers included cytokine-chemokines, dual-functioning cytozymes, and vascular injury markers. Logistic regression, latent class analysis, and classification and regression tree analysis were used to identify the plasma biomarkers most predictive of 28-day ARDS mortality.

Results

From eight biologically relevant biomarker candidates, six demonstrated an enhanced capacity to predict mortality at day 0. Latent-class analysis identified two biomarker-based phenotypes. Phenotype A exhibited significantly higher plasma levels of angiopoietin-2, macrophage migration inhibitory factor, interleukin-8, interleukin-1 receptor antagonist, interleukin-6, and extracellular nicotinamide phosphoribosyltransferase (eNAMPT) compared to phenotype B. Mortality at 28 days was significantly higher for phenotype A compared to phenotype B (32% vs 19%, p = 0.04).

Conclusions

An adult biomarker-based risk model reliably identifies ARDS subjects at risk of death within 28 days of hospitalization.

Murine sepsis phenotypes and differential treatment effects in a randomized trial of prompt antibiotics and fluids

BACKGROUND

Clinical and biologic phenotypes of sepsis are proposed in human studies, yet it is unknown whether prognostic or drug response phenotypes are present in animal models of sepsis. Using a biotelemetry-enhanced, murine cecal ligation and puncture (CLP) model, we determined phenotypes of polymicrobial sepsis prior to physiologic deterioration, and the association between phenotypes and outcome in a randomized trial of prompt or delayed antibiotics and fluids.

METHODS

We performed a secondary analysis of male C57BL/6J mice in two observational cohorts and two randomized, laboratory animal experimental trials. In cohort 1, mice (n = 118) underwent biotelemetry-enhanced CLP, and we applied latent class mixed models to determine optimal number of phenotypes using clinical data collected between injury and physiologic deterioration. In cohort 2 (N = 73 mice), inflammatory cytokines measured at 24 h after deterioration were explored by phenotype. In a subset of 46 mice enrolled in two trials from cohort 1, we tested the association of phenotypes with the response to immediate (0 h) vs. delayed (2 to 4 h) antibiotics or fluids initiated after physiologic deterioration.

RESULTS

Latent class mixture modeling derived a two-class model in cohort 1. Class 2 (N = 97) demonstrated a shorter time to deterioration (mean SD 7.3 (0.9) vs. 9.7 (3.2) h, p < 0.001) and lower heart rate at 7 h after injury (mean (SD) 564 (55) vs. 626 (35) beats per minute, p < 0.001). Overall mortality was similar between phenotypes (p = 0.75). In cohort 2 used for biomarker measurement, class 2 mice had greater plasma concentrations of IL6 and IL10 at 24 h after CLP (p = 0.05). In pilot randomized trials, the effects of sepsis treatment (immediate vs. delayed antibiotics) differed by phenotype (p = 0.03), with immediate treatment associated with greater survival in class 2 mice only. Similar differential treatment effect by class was observed in the trial of immediate vs. delayed fluids (p = 0.02).

CONCLUSIONS

We identified two sepsis phenotypes in a murine cecal ligation and puncture model, one of which is characterized by faster deterioration and more severe inflammation. Response to treatment in a randomized trial of immediate versus delayed antibiotics and fluids differed on the basis of phenotype.

Precision Medicine in Critical Illness: Sepsis and Acute Respiratory Distress Syndrome

Sepsis and the acute respiratory distress syndrome (ARDS) each cause substantial morbidity and mortality. In contrast to other lung diseases, the entire course of disease in these syndromes is measured in days to weeks rather than months to years, which raises unique challenges in achieving precision medicine. We review advances in sepsis and ARDS resulting from omics studies, including those involving genome-wide association, gene expression, targeted proteomics, and metabolomics approaches. We focus on promising evidence of biological subtypes in both sepsis and ARDS that consistently display high risk for death. In sepsis, a gene expression signature with dysregulated adaptive immune signaling has evidence for a differential response to systemic steroid therapy, whereas in ARDS, a hyperinflammatory pattern identified in plasma using targeted proteomics responded more favorably to randomized interventions including high positive end-expiratory pressure, volume conservative fluid therapy, and simvastatin therapy. These early examples suggest heterogeneous biology that may be challenging to detect by clinical factors alone and speak to the promise of a precision approach that targets the right treatment at the right time to the right patient.

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

OBJECTIVES

To find and validate generalizable sepsis subtypes using data-driven clustering.

DESIGN

We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from eight different countries (n = 700).

SETTING

Retrospective analysis.

SUBJECTS

Persons admitted to the hospital with bacterial sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed "Inflammopathic, Adaptive, and Coagulopathic." We then validated these subtypes in nine independent datasets from five different countries (n = 600). In both discovery and validation data, the Adaptive subtype is associated with a lower clinical severity and lower mortality rate, and the Coagulopathic subtype is associated with higher mortality and clinical coagulopathy. Further, these clusters are statistically associated with clusters derived by others in independent single sepsis cohorts.

CONCLUSIONS

The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.

Prognostic and predictive enrichment in sepsis

Sepsis is a heterogeneous disease state that is both common and consequential in critically ill patients. Unfortunately, the heterogeneity of sepsis at the individual patient level has hindered advances in the field beyond the current therapeutic standards, which consist of supportive care and antibiotics. This complexity has prompted attempts to develop a precision medicine approach, with research aimed towards stratifying patients into more homogeneous cohorts with shared biological features, potentially facilitating the identification of new therapies. Several investigators have successfully utilized leukocyte-derived mRNA and discovery-based approaches to subgroup patients on the basis of biological similarities defined by transcriptomic signatures. A critical next step is to develop a consensus sepsis subclassification system, which includes transcriptomic signatures as well as other biological and clinical data. This goal will require collaboration among various investigative groups, and validation in both existing data sets and prospective studies. Such studies are required to bring precision medicine to the bedside of critically ill patients with sepsis.

Endotype Transitions During the Acute Phase of Pediatric Septic Shock Reflect Changing Risk and Treatment Response

OBJECTIVE

We previously identified septic shock endotypes A and B based on 100 genes reflecting adaptive immunity and glucocorticoid receptor signaling. The endotypes differ with respect to outcome and corticosteroid responsiveness. We determined whether endotypes change during the initial 3 days of illness, and whether changes are associated with outcomes.

DESIGN

Observational cohort study including existing and newly enrolled participants.

SETTING

Multiple PICUs.

PATIENTS

Children with septic shock.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We measured the 100 endotyping genes at day 1 and day 3 of illness in 375 patients. We determined if endotype assignment changes over time, and whether changing endotype is associated with corticosteroid response and outcomes. We used multivariable logistic regression to adjust for illness severity, age, and comorbidity burden. Among the 132 subjects assigned to endotype A on day 1, 56 (42%) transitioned to endotype B by day 3. Among 243 subjects assigned to endotype B on day 1, 77 (32%) transitioned to endotype A by day 3. Assignment to endotype A on day 1 was associated with increased odds of mortality. This risk was modified by the subsequent day 3 endotype assignment. Corticosteroids were associated with increased risk of mortality among subjects who persisted as endotype A.

CONCLUSIONS

A substantial proportion of children with septic shock transition endotypes during the acute phase of illness. The risk of poor outcome and the response to corticosteroids change with changes in endotype assignment. Patients persisting as endotype A are at highest risk of poor outcomes.

Glucocorticosteroids for sepsis in children. A protocol for a systematic review

BACKGROUND

Sepsis is the primary diagnosis in more than 8% of all critically ill children and sepsis is among the ten leading causes of death in children <10 years. Glucocorticosteroids are currently recommended in septic children with fluid or catecholamine resistant refractory shock. Glucocorticosteroids are widely used for severe sepsis in paediatric intensive care units worldwide. However, the evidence on the clinical effects of glucocorticosteroids for sepsis in children is unclear.

METHODS

We will perform a systematic review with meta-analysis and Trial Sequential Analysis of randomised clinical trials. We will include randomised clinical trials assessing the effects of glucocorticosteroids vs placebo or no intervention as an add-on therapy to standard care for sepsis in children. For the assessment of harms, we will also include quasi-randomised studies and observational studies identified during our searches for randomised clinical trials.

DISCUSSION

This review will seek to assess whether glucocorticosteroids indeed have their therapeutic place in the standard treatment for sepsis in children.

Precision medicine in pediatric sepsis

PURPOSE OF REVIEW

Pediatric sepsis is a heterogeneous state associated with significant morbidity and mortality, but treatment strategies are limited. Clinical trials of immunomodulators in sepsis have shown no benefit, despite having a strong biological rationale. There is considerable interest in application of a precision medicine approach to pediatric sepsis to identify patients who are more likely to benefit from targeted therapeutic interventions.

RECENT FINDINGS

Precision medicine requires a clear understanding of the molecular basis of disease. 'Omics data' and bioinformatics tools have enabled identification of endotypes of pediatric septic shock, with corresponding biological pathways. Further, using a multibiomarker-based approach, patients at highest risk of poor outcomes can be identified at disease onset. Enrichment strategies, both predictive and prognostic, may be used to optimize patient selection in clinical trials and identify a subpopulation in whom therapy of interest may be trialed. A bedside-to-bench-to-bedside model may offer clinicians pragmatic tools to aid in decision-making.

SUMMARY

Precision medicine approaches may be used to subclassify, risk-stratify, and select pediatric patients with sepsis who may benefit from new therapies. Application of precision medicine will require robust basic and translational research, rigorous clinical trials, and infrastructure to collect and analyze big data.

PPARα contributes to protection against metabolic and inflammatory derangements associated with acute kidney injury in experimental sepsis

Sepsis-associated acute kidney injury (AKI) is a significant problem in critically ill children and adults resulting in increased morbidity and mortality. Fundamental mechanisms contributing to sepsis-associated AKI are poorly understood. Previous research has demonstrated that peroxisome proliferator-activated receptor α (PPARα) expression is associated with reduced organ system failure in sepsis. Using an experimental model of polymicrobial sepsis, we demonstrate that mice deficient in PPARα have worse kidney function, which is likely related to reduced fatty acid oxidation and increased inflammation. Ultrastructural evaluation with electron microscopy reveals that the proximal convoluted tubule is specifically injured in septic PPARα deficient mice. In this experimental group, serum metabolomic analysis reveals unanticipated metabolic derangements in tryptophan-kynurenine-NAD+ and pantothenate pathways. We also show that a subgroup of children with sepsis whose genome-wide expression profiles are characterized by repression of the PPARα signaling pathway has increased incidence of severe AKI. These findings point toward interesting associations between sepsis-associated AKI and PPARα-driven fatty acid metabolism that merit further investigation.

Global Case-Fatality Rates in Pediatric Severe Sepsis and Septic Shock: A Systematic Review and Meta-analysis

IMPORTANCE

The global patterns and distribution of case-fatality rates (CFRs) in pediatric severe sepsis and septic shock remain poorly described.

OBJECTIVE

We performed a systematic review and meta-analysis of studies of children with severe sepsis and septic shock to elucidate the patterns of CFRs in developing and developed countries over time. We also described factors associated with CFRs.

DATA SOURCES

We searched PubMed, Web of Science, Excerpta Medica database, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and Cochrane Central systematically for randomized clinical trials and prospective observational studies from earliest publication until January 2017, using the keywords "pediatric," "sepsis," "septic shock," and "mortality."

STUDY SELECTION

Studies involving children with severe sepsis and septic shock that reported CFRs were included. Retrospective studies and studies including only neonates were excluded.

DATA EXTRACTION AND SYNTHESIS

We conducted our systematic review and meta-analysis in close accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Pooled case-fatality estimates were obtained using random-effects meta-analysis. The associations of study period, study design, sepsis severity, age, and continents in which studies occurred were assessed with meta-regression.

MAIN OUTCOMES AND MEASURES

Meta-analyses to provide pooled estimates of CFR of pediatric severe sepsis and septic shock over time.

RESULTS

Ninety-four studies that included 7561 patients were included. Pooled CFRs were higher in developing countries (31.7% [95% CI, 27.3%-36.4%]) than in developed countries (19.3% [95% CI, 16.4%-22.7%]; P < .001). Meta-analysis of CFRs also showed significant heterogeneity across studies. Continents that include mainly developing countries reported higher CFRs (adjusted odds ratios: Africa, 7.89 [95% CI, 6.02-10.32]; P < .001; Asia, 3.81 [95% CI, 3.60-4.03]; P < .001; South America, 2.91 [95% CI, 2.71-3.12]; P < .001) than North America. Septic shock was associated with higher CFRs than severe sepsis (adjusted odds ratios, 1.47 [95% CI, 1.41-1.54]). Younger age was also a risk factor (adjusted odds ratio, 0.95 [95% CI, 0.94-0.96] per year of increase in age). Earlier study eras were associated with higher CFRs (adjusted odds ratios for 1991-2000, 1.24 [95% CI, 1.13-1.37]; P < .001) compared with 2011 to 2016. Time-trend analysis showed higher CFRs over time in developing countries than developed countries.

CONCLUSIONS AND RELEVANCE

Despite the declining trend of pediatric severe sepsis and septic shock CFRs, the disparity between developing and developed countries persists. Further characterizations of vulnerable populations and collaborations between developed and developing countries are warranted to reduce the burden of pediatric sepsis globally.

Point of care technologies for sepsis diagnosis and treatment

Sepsis is a rapidly progressing, life threatening immune response triggered by infection that affects millions worldwide each year. Current clinical diagnosis relies on broad physiological parameters and time consuming lab-based cell culture. If proper treatment is not provided, cases of sepsis can drastically increase in severity over the course of a few hours. Development of new point of care tools for sepsis has the potential to improve diagnostic speed and accuracy, leading to prompt administration of appropriate therapeutics, thereby reducing healthcare costs and improving patient outcomes. In this review we examine developing and commercially available technologies to assess the feasibility of rapid, accurate sepsis diagnosis, with emphasis on point of care.

Profile of the SeptiCyte™ LAB gene expression assay to diagnose infection in critically ill patients

Sepsis is a severe and frequently occurring clinical syndrome, caused by the inflammatory response to infections. Recent studies on the human transcriptome during sepsis have yielded several gene-expression assays that might assist physicians during clinical assessment of patients suspected of sepsis. SeptiCyte™ LAB (Immunexpress, Seattle, WA) is the first gene expression assay that was cleared by the FDA in the United States to distinguish infectious from non-infectious causes of systemic inflammation in critically ill patients. The test consists of the simultaneous amplification of four RNA transcripts (CEACAM4, LAMP1, PLAC8, and PLA2G7) in whole blood using a quantitative real-time PCR reaction. This review provides an overview of the challenges in the diagnosis of sepsis, the development of gene expression signatures, and a detailed description of available clinical performance studies evaluating SeptiCyte™ LAB.

Evidence of Endotypes in Pediatric Acute Hypoxemic Respiratory Failure Caused by Sepsis

OBJECTIVES

Subclassification based on clinical or biologic commonalities (endotypes) is one approach to reduce heterogeneity in acute hypoxemic respiratory failure. In adults, biomarker-defined endotypes of respiratory failure have been described, with differential outcome profiles and response to therapy. To date, no studies have tested whether endotypes exist in pediatric acute hypoxemic respiratory failure, although messenger RNA expression-based endotypes have been described in pediatric sepsis. The aim of the present study was to test whether endotypes identified in pediatric sepsis are applicable to pediatric acute hypoxemic respiratory failure.

DESIGN

Secondary analysis of a previously reported microarray-based study of pediatric sepsis.

SETTING

Multiple PICUs in the United States.

PATIENTS

Sixty-seven children with acute hypoxemic respiratory failure caused by sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of the larger septic shock cohort, 67 met eligibility for acute hypoxemic respiratory failure. Twenty-three subjects were assigned to endotype A, and 44 to endotype B. Subjects assigned to endotype A had over four-fold greater unadjusted 28-day mortality, and nearly three-fold greater rates of complicated course. The association with mortality (odds ratio, 8.0; 95% CI, 1.6-41.0) and complicated course (odds ratio, 4.2; 95% CI, 1.2-14.9) persisted after adjustment for age, severity of illness, and PaO2/FIO2.

CONCLUSIONS

Applying a previously reported endotyping strategy in children with septic shock identified endotypes of pediatric acute hypoxemic respiratory failure secondary to sepsis, with differential risk for poor outcomes. To our knowledge, this is the first demonstration of endotypes in pediatric respiratory failure. Our results support an investigation into using transcriptomics to identify messenger RNA-based endotypes in a dedicated, well-defined acute hypoxemic respiratory failure cohort.

Sepsis Biomarkers

Sepsis-related biomarkers have a variety of potential applications. The most well-known application is to differentiate patients with signs of systemic inflammation caused by infection, from those with systemic inflammation due to a non-infectious cause. This application is important for timely and judicious prescription of antibiotics. Apart from diagnostic applications, biomarkers can also be used to identify patients with sepsis who are at risk for poor outcome and to subgroup patients with sepsis based on biological commonalities. The latter two applications embody the concepts of prognostic and predictive enrichment, which are fundamental to precision medicine. This review will elaborate on these concepts, provide relevant examples, and discuss important considerations in the process of biomarkers discovery and development.

Identification of subclasses of sepsis that showed different clinical outcomes and responses to amount of fluid resuscitation: a latent profile analysis

BACKGROUND AND OBJECTIVE

Sepsis is a heterogeneous disease and identification of its subclasses may facilitate and optimize clinical management. This study aimed to identify subclasses of sepsis and its responses to different amounts of fluid resuscitation.

METHODS

This was a retrospective study conducted in an intensive care unit at a large tertiary care hospital. The patients fulfilling the diagnostic criteria of sepsis from June 1, 2001 to October 31, 2012 were included. Clinical and laboratory variables were used to perform the latent profile analysis (LPA). A multivariable logistic regression model was used to explore the independent association of fluid input and mortality outcome.

RESULTS

In total, 14,993 patients were included in the study. The LPA identified four subclasses of sepsis: profile 1 was characterized by the lowest mortality rate and having the largest proportion and was considered the baseline type; profile 2 was characterized by respiratory dysfunction; profile 3 was characterized by multiple organ dysfunction (kidney, coagulation, liver, and shock), and profile 4 was characterized by neurological dysfunction. Profile 3 showed the highest mortality rate (45.4%), followed by profile 4 (27.4%), 2 (18.2%), and 1 (16.9%). Overall, the amount of fluid needed for resuscitation was the largest on day 1 (median 5115 mL, interquartile range (IQR) 2662 to 8800 mL) and decreased rapidly on day 2 (median 2140 mL, IQR 900 to 3872 mL). Higher cumulative fluid input in the first 48 h was associated with reduced risk of hospital mortality for profile 3 (odds ratio (OR) 0.89, 95% CI 0.83 to 0.95 for each 1000 mL increase in fluid input) and with increased risk of death for profile 4 (OR 1.20, 95% CI 1.11 to 1.30).

CONCLUSION

The study identified four subphenotypes of sepsis, which showed different mortality outcomes and responses to fluid resuscitation. Prospective trials are needed to validate our findings.

Characterization of the Glucocorticoid Receptor in Children Undergoing Cardiac Surgery

OBJECTIVES

Postoperative administration of corticosteroids is common practice for managing catecholamine refractory low cardiac output syndrome. Since corticosteroid activity is dependent on the glucocorticoid receptor, we sought to characterize glucocorticoid receptor levels in children undergoing cardiac surgery and examined the association between glucocorticoid receptor levels and cardiovascular dysfunction.

DESIGN

Prospective observational cohort study.

SETTING

Large, tertiary pediatric cardiac center.

SUBJECTS

Children undergoing corrective or palliative cardiac surgery.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A prospective observational cohort study was conducted in 83 children with congenital heart disease. Total glucocorticoid receptor levels were measured in the peripheral WBCs using flow cytometry. In addition, blood samples were collected for total cortisol levels. The primary outcome studied was the time to being inotrope free. An increase in glucocorticoid receptor level from postoperative day 1 to postoperative day 3 was associated with a longer time to being inotrope free (hazard ratio, 0.49 [0.29-0.81]; p = 0.01) in the univariate analysis. This association remained significant after adjusting for age, weight, cardiopulmonary bypass time, cross clamp time, Risk Adjustment for Congenital Heart Surgery-1 score, and postoperative steroid use (hazard ratio, 0.53 [0.29-0.99]; p = 0.05). Postoperative day 3 glucocorticoid receptor level showed a trend to have longer time to being inotrope free (hazard ratio, 0.66 [0.42-1.02]; p = 0.0.06). The cortisol levels minimally increased during the study duration and did not correlate with glucocorticoid receptor levels.

CONCLUSIONS

Increasing glucocorticoid receptor levels in peripheral WBCs of children undergoing cardiac surgery are associated with a longer time to being inotrope free. Cortisol levels minimally increased during the study duration. These results suggest that exposure to high-dose perioperative corticosteroids may suppress the hypothalamic-pituitary-adrenal axis leading to increase in glucocorticoid receptor levels in response to a low cortisol environment. Further studies are required to better delineate the interplay between glucocorticoid receptor levels, cortisol levels, corticosteroid exposure, and postoperative inotropic requirements.