The influence of developmental age on the early transcriptomic response of children with septic shock

The frequency and timing of sepsis-associated coagulopathy in the neonatal intensive care unit

Introduction

Sepsis is a common cause of morbidity and mortality in the neonatal intensive care unit (NICU). The frequency and severity of sepsis-associated coagulopathy as well as its relationship to illness severity are unclear.

Methods

We performed a single-center, retrospective, observational cohort study of all infants admitted to the University of Florida Health (UF Health), level IV NICU between January 1st 2012 to March 1st 2020 to measure the frequency of sepsis-associated coagulopathy as well as its temporal relationship to critical illness in the NICU population. All clinical data in the electronic health record were extracted and deposited into an integrated data repository that was used for this work.

Results

We identified 225 new sepsis episodes in 216 patients. An evaluation for sepsis-associated coagulopathy was performed in 96 (43%) episodes. Gram-negative pathogen, nSOFA score at evaluation, and mortality were greater among episodes that included a coagulopathy evaluation compared with those that did not. Abnormal coagulation results were common (271/339 evaluations; 80%) and were predominantly prothrombin times. Intervention (plasma or cryoprecipitate) followed a minority (84/271; 31%) of abnormal results, occurred in 40/96 (42%) episodes that were often associated with >1 intervention (29/40; 73%), and coincided with thrombocytopenia in 37/40 (93%) and platelet transfusion in 27/40 (68%). Shapley Additive Explanations modeling demonstrated strong predictive performance for the composite outcome of death and/or treatment for coagulopathy in neonates (f1 score 0.8, area under receiver operating characteristic curve 0.83 for those with abnormal coagulation values). The three most important features influencing the composite outcome of death or treatment for coagulopathy included administration of vasoactive medications, hematologic dysfunction assessed by the maximum nSOFA platelet score, and early sepsis (≤72 h after birth).

Conclusions

A coagulopathy evaluation was performed in a minority of NICU patients with sepsis and was associated with greater illness severity and mortality. Abnormal results were common but infrequently associated with intervention, and intervention was contemporaneous with thrombocytopenia. The most important feature that influenced the composite outcome of death or treatment for coagulopathy was the administration of vasoactive-inotropic medications. These data help to identify NICU patients at risk of sepsis-associated coagulopathy.

Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments

Cellular senescence is closely associated with the pathogenesis of sepsis. However, the diagnostic and prognostic value of senescence-related genes remain unclear. In this study, 866 senescence-related genes were collected from CellAge. The training cohort, GSE65682, which included 42 control and 760 sepsis samples, was obtained from the Gene Expression Omnibus (GEO). Feature selection was performed using gene expression difference detection, LASSO analysis, random forest, and Cox regression. TGFBI and MAD1L1 were ultimately selected for inclusion in the multivariate Cox regression model. Clustering based on the expressions of TGFBI and MAD1L1 was significantly associated with sepsis characteristics and prognoses (all P < 0.05). The risk signature served as a reliable prognostic predictor across the GSE65682, GSE95233, and GSE4607 cohorts (pooled hazard ratio = 4.27; 95% confidence interval [CI] = 1.63-11.17). Furthermore, it also served as a robust classifier to distinguish sepsis samples from control cases across 14 cohorts (pooled odds ratio = 5.88; 95% CI = 3.54-9.77). Single-cell RNA sequencing analyses from five healthy controls and four sepsis subjects indicated that the risk signature could reflect the senescence statuses of monocytes and B cells; this finding was then experimentally validated in THP-1 and IM-9 cells in vitro (both P < 0.05). In all, a senescence-related gene signature was developed as a prognostic and diagnostic biomarker for sepsis, providing cut-in points to uncover underlying mechanisms and a promising clinical tool to support precision medicine.

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

BACKGROUND

Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification of genes associated with a persistent MODS trajectory may shed light on underlying biology and allow for accurate prediction of those at-risk.

METHODS

Secondary analyses of publicly available gene-expression datasets. Supervised machine learning (ML) was used to identify a parsimonious set of genes associated with a persistent MODS trajectory in a training set of pediatric septic shock. We optimized model parameters and tested risk-prediction capabilities in independent validation and test datasets, respectively. We compared model performance relative to an established gene-set predictive of sepsis mortality.

FINDINGS

Patients with a persistent MODS trajectory had 568 differentially expressed genes and characterized by a dysregulated innate immune response. Supervised ML identified 111 genes associated with the outcome of interest on repeated cross-validation, with an AUROC of 0.87 (95% CI: 0.85-0.88) in the training set. The optimized model, limited to 20 genes, achieved AUROCs ranging from 0.74 to 0.79 in the validation and test sets to predict those with persistent MODS, regardless of host age and cause of organ dysfunction. Our classifier demonstrated reproducibility in identifying those with persistent MODS in comparison with a published gene-set predictive of sepsis mortality.

INTERPRETATION

We demonstrate the utility of supervised ML driven identification of the genes associated with persistent MODS. Pending validation in enriched cohorts with a high burden of organ dysfunction, such an approach may inform targeted delivery of interventions among at-risk patients.

FUNDING

H.R.W.'s NIHR35GM126943 award supported the work detailed in this manuscript. Upon his death, the award was transferred to M.N.A. M.R.A., N.S.P, and R.K were supported by NIHR21GM151703. R.K. was supported by R01GM139967.

Molecular subtypes based on N6-methyladenosine RNA methylation demonstrate the heterogeneity of immune and biological functions in pediatric septic shock

Introduction

Septic shock in children is a highly heterogeneous syndrome involving different immune states and biological processes. We used a bioinformatics approach to explore the relationship between N6-methyladenosine (m6A) methylation and septic shock in children.

Methods

A gene expression dataset including information on 98 children with septic shock was selected. To construct and evaluate a risk prediction model, machine learning was used to screen marker m6A regulators. Based on differentially expressed m6A regulators, molecular subtypes for paediatric septic shock were constructed. Subsequently, the differences in the m6Ascore, heterogeneity of immune cell infiltration, and heterogeneity of biological functions between the different subtypes were analyzed. Finally, real-time quantitative PCR (RT-qPCR) was performed to validate the expression of the marker m6A regulators.

Results

Fifteen differentially expressed m6A regulators were identified. Six marker m6A regulators, including LRPPRC, ELAVL1, RBM15, CBLL1, FTO, and RBM15B, were screened using the random forest method. The risk prediction model for paediatric septic shock constructed using m6A markers had strong consistency and high clinical practicability. Two subtypes of paediatric septic shock have been identified based on the differential expression pattern of m6A regulators. Significant differences were observed in RNA epigenetics, immune statuses, and biological processes between the two m6A subtypes. Differentially expressed genes between the two subtypes were enriched in cell number homeostasis, redox responses, and innate immune system responses. Finally, the six marker m6A regulators were verified in additional samples.

Conclusions

Based on the heterogeneity of m6A methylation-regulated genes, two different subtypes of septic shock in children with different RNA epigenetics, immune statuses, and biological processes were identified, revealing the heterogeneity of the disease largely attributable to differential m6A methylation. The findings will help explore and establish appropriate individualized treatments.

Biomarkers estimating baseline mortality risk for neonatal sepsis: nPERSEVERE: neonate-specific sepsis biomarker risk model

BACKGROUND

Prognostic biomarker research neonatal sepsis is lacking. We assessed the utility of a validated pediatric prognostic tool called PERSEVERE II that uses decision tree methodology to predict mortality at discharge in neonates who experienced sepsis.

METHODS

Prospective study in a dual-center cohort of neonates with sepsis admitted between June 2020 and December 2021. Biomarker analysis was done on serum samples obtained at the time of evaluation for the event.

RESULTS

In a cohort of 59 neonates with a mortality rate of 15.3%, PERSEVERE II was 67% sensitive and 59% specific for mortality, p 0.27. Amongst PERSEVERE II biomarkers, IL-8 showed good prognostic performance for mortality prediction with a cutoff of 300 pg/mL (sensitivity 100%, specificity 65%, negative predictive value 100%, AUC 0.87, p 0.0003). We derived a new decision tree that is neonate specific (nPERSEVERE) with improved performance compared to IL-8 (sensitivity 100%, specificity 86%, negative predictive value 100%, AUC 0.95, p < 0.0001).

CONCLUSIONS

IL-8 and nPERSEVERE demonstrated good prognostic performance in a small cohort of neonates with sepsis. Moving toward precision medicine in sepsis, our study proposes an important tool for clinical trial prognostic enrichment that needs to be validated in larger studies.

IMPACT

Prognostic and predictive biomarker research is lacking in the newborn intensive care unit. Biomarkers can be used at the time of evaluation for neonatal sepsis (blood culture acquisition) to identify neonates with high baseline mortality risk. Stratification is an important step toward precision medicine in neonatal sepsis.

Activation of thousands of genes in the lungs and kidneys by sepsis is countered by the selective nuclear blockade

The steady rise of sepsis globally has reached almost 49 million cases in 2017, and 11 million sepsis-related deaths. The genomic response to sepsis comprising multi-system stage of raging microbial inflammation has been reported in the whole blood, while effective treatment is lacking besides anti-microbial therapy and supportive measures. Here we show that, astoundingly, 6,237 significantly expressed genes in sepsis are increased or decreased in the lungs, the site of acute respiratory distress syndrome (ARDS). Moreover, 5,483 significantly expressed genes in sepsis are increased or decreased in the kidneys, the site of acute injury (AKI). This massive genomic response to polymicrobial sepsis is countered by the selective nuclear blockade with the cell-penetrating Nuclear Transport Checkpoint Inhibitor (NTCI). It controlled 3,735 sepsis-induced genes in the lungs and 1,951 sepsis-induced genes in the kidneys. The NTCI also reduced without antimicrobial therapy the bacterial dissemination: 18-fold in the blood, 11-fold in the lungs, and 9-fold in the spleen. This enhancement of bacterial clearance was not significant in the kidneys. Cumulatively, identification of the sepsis-responsive host's genes and their control by the selective nuclear blockade advances a better understanding of the multi-system mechanism of sepsis. Moreover, it spurs much-needed new diagnostic, therapeutic, and preventive approaches.

Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study

Background

Septic shock occurs when sepsis is related to severe hypotension and leads to a remarkable high number of deaths. The early diagnosis of septic shock is essential to reduce mortality. High-quality biomarkers can be objectively measured and evaluated as indicators to accurately predict disease diagnosis. However, single-gene prediction efficiency is inadequate; therefore, we identified a risk-score model based on gene signature to elevate predictive efficiency.

Methods

The gene expression profiles of GSE33118 and GSE26440 were downloaded from the Gene Expression Omnibus (GEO) database. These two datasets were merged, and the differentially expressed genes (DEGs) were identified using the limma package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed. Subsequently, Lasso regression and Boruta feature selection algorithm were combined to identify the hub genes of septic shock. GSE9692 was then subjected to weighted gene co-expression network analysis (WGCNA) to identify the septic shock-related gene modules. Subsequently, the genes within such modules that matched with septic shock-related DEGs were identified as the hub genes of septic shock. To further understand the function and signaling pathways of hub genes, we performed gene set variation analysis (GSVA) and then used the CIBERSORT tool to analyze the immune cell infiltration pattern of diseases. The diagnostic value of hub genes in septic shock was determined using receiver operating characteristic (ROC) analysis and verified using quantitative PCR (qPCR) and Western blotting in our hospital patients with septic shock.

Results

A total of 975 DEGs in the GSE33118 and GSE26440 databases were obtained, of which 30 DEGs were remarkably upregulated. With the use of Lasso regression and Boruta feature selection algorithm, six hub genes (CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4) with expression differences in septic shock were screened as potential diagnostic markers for septic shock among the significant DEGs and were further validated in the GSE9692 dataset. WGCNA was used to identify the co-expression modules and module-trait correlation. Enrichment analysis showed significant enrichment in the reactive oxygen species pathway, hypoxia, phosphatidylinositol 3-kinases (PI3K)/Protein Kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, nuclear factor-κβ/tumor necrosis factor alpha (NF-κβ/TNF-α), and interleukin-6 (IL-6)/Janus Kinase (JAK)/Signal Transducers and Activators of Transcription 3 (STAT3) signaling pathways. The receiver operating characteristic curve (ROC) of these signature genes was 0.938, 0.914, 0.939, 0.956, 0.932, and 0.914, respectively. In the immune cell infiltration analysis, the infiltration of M0 macrophages, activated mast cells, neutrophils, CD8 T cells, and naive B cells was more significant in the septic shock group. In addition, higher expression levels of CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 messenger RNA (mRNA) were observed in peripheral blood mononuclear cells (PBMCs) isolated from septic shock patients than from healthy donors. Higher expression levels of CD177 and MMP8 proteins were also observed in the PBMCs isolated from septic shock patients than from control participants.

Conclusions

CD177, CLEC5A, CYSTM1, MCEMP1, MMP8, and RGL4 were identified as hub genes, which were of considerable value in the early diagnosis of septic shock patients. These preliminary findings are of great significance for studying immune cell infiltration in the pathogenesis of septic shock, which should be further validated in clinical studies and basic studies.

Similar hypothyroid and sepsis circulating mRNA expression could be useful as a biomarker in onthyroidal illness syndrome: a pilot study

Objective

Based on hypothetical hypothyroidism and nonthyroidal illness syndrome (NTIS) gene expression similarities, we decided to compare the patterns of expression of both as models of NTIS. The concordant profile between them may enlighten new biomarkers for NTIS challenging scenarios.

Materials and methods

We used Ion Proton System next-generation sequencing to build the hypothyroidism transcriptome. We selected two databanks in GEO2 platform datasets to find the differentially expressed genes (DEGs) in adults and children with sepsis. The ROC curve was constructed to calculate the area under the curve (AUC). The AUC, chi-square, sensitivity, specificity, accuracy, kappa and likelihood were calculated. We performed Cox regression and Kaplan-Meier analyses for the survival analysis.

Results

Concerning hypothyroidism DEGs, 70.42% were shared with sepsis survivors and 61.94% with sepsis nonsurvivors. Some of them were mitochondrial gene types (mitGenes), and 95 and 88 were related to sepsis survivors and nonsurvivors, respectively. BLOC1S1, ROMO1, SLIRP and TIMM8B mitGenes showed the capability to distinguish sepsis survivors and nonsurvivors.

Conclusion

We matched our hypothyroidism DEGs with those in adults and children with sepsis. Additionally, we observed different patterns of hypothyroid-related genes among sepsis survivors and nonsurvivors. Finally, we demonstrated that ROMO1, SLIRP and TIMM8B could be predictive biomarkers in children´s sepsis.

Differential gene expression in peripheral leukocytes of pre-weaned Holstein heifer calves with respiratory disease

Bovine respiratory disease (BRD) is a leading cause of calf morbidity and mortality, and prevalence remains high despite current management practices. Differential gene expression (DGE) provides detailed insight into individual immune responses and can illuminate enriched pathways and biomarkers that contribute to disease susceptibility and outcomes. The aims of this study were to investigate differences in peripheral leukocyte gene expression in Holstein preweaned heifer calves 1) with and without BRD, and 2) across weeks of age. Calves were enrolled for this short-term longitudinal study on two commercial dairies in Washington State. Calves were assessed every two weeks throughout the pre-weaning period using clinical respiratory scoring (CRS) and thoracic ultrasonography (TUS), and blood samples were collected. Calves were selected that were either healthy (n = 10) or had BRD diagnosed by CRS (n = 7), TUS (n = 6), or both (n = 6) in weeks 5 or 7 of life). Three consecutive time point samples were analyzed for each BRD calf consisting of PRE, ONSET, and POST samples. Nineteen genes of interest were selected based on previous gene expression studies in cattle: ALOX15, BPI, CATHL6, CXCL8, DHX58, GZMB, HPGD, IFNG, IL17D, IL1R2, ISG15, LCN2, LIF, MX1, OAS2, PGLYRP1, S100A8, SELP, and TNF. Comparisons were made between age and disease time point matched BRD and healthy calves as well as between calf weeks of age. No DGE was observed between diseased and healthy calves; however, DGE was observed between calf weeks of age regardless of disease state. Developmental differences in leukocyte gene expression, phenotype, and functionality make pre-weaned calves immunologically distinct from mature cattle, and early life shifts in calf leukocyte populations likely contribute to the age-related gene expression differences we observed. Age overshadows disease impacts to influence gene expression in young calves, and immune development progresses upon a common trajectory regardless of disease during the preweaning period.

Distinct gene programs underpinning disease tolerance and resistance in influenza virus infection

When challenged with an invading pathogen, the host-defense response is engaged to eliminate the pathogen (resistance) and to maintain health in the presence of the pathogen (disease tolerance). However, the identification of distinct molecular programs underpinning disease tolerance and resistance remained obscure. We exploited transcriptional and physiological monitoring across 33 mouse strains, during in vivo influenza virus infection, to identify two host-defense gene programs-one is associated with hallmarks of disease tolerance and the other with hallmarks of resistance. Both programs constitute generic responses in multiple mouse and human cell types. Our study describes the organizational principles of these programs and validates Arhgdia as a regulator of disease-tolerance states in epithelial cells. We further reveal that the baseline disease-tolerance state in peritoneal macrophages is associated with the pathophysiological response to injury and infection. Our framework provides a paradigm for the understanding of disease tolerance and resistance at the molecular level.

Beneficial Effects of O-GlcNAc Stimulation in a Young Rat Model of Sepsis: Beyond Modulation of Gene Expression

The young population, which is particularly at risk of sepsis, is, paradoxically, rarely studied. Acute stimulation of O-GlcNAcylation, a post-translational modification involved in metabolic regulation, cell survival and stress response, is beneficial in young rats with sepsis. Considering that sepsis impacts the gene expression profile and that O-GlcNAcylation is a regulator of transcription, the aims of this study are to (i) unveil beneficial mechanisms of O-GlcNAcylation and (ii) decipher the relationship between O-GlcNAcylation and transcription during sepsis. Endotoxemic challenge was induced in 28-day-old male rats using a lipopolysaccharide injection (E. coli O111:B4, 20 mg·kg−1) and compared to control rats (NaCl 0.9%). One hour after, rats were assigned to no therapy or fluidotherapy (NaCl 0.9%, 10 mL.kg−1) ± NButGT (10 mg·kg−1) to stimulate O-GlcNAc levels. Cardiac O-GlcNAcylation levels were evaluated via Western blot and gene transcription using 3′ SRP analysis. Lipopolysaccharide injection favorizes inflammatory state with the overexpression of genes involved in the NF-κB, JAK/STAT and MAPK pathways. NButGT treatment increased cardiac O-GlcNAcylation levels (p < 0.05). Yet, the mRNA expression was not impacted two hours after fluidotherapy or NButGT treatment. In conclusion, O-GlcNAc stimulation-induced beneficial effects are not dependent on the gene expression profile at the early phase of sepsis.

Identification of a Four-Gene Signature for Diagnosing Paediatric Sepsis

Aim

Early diagnosis of paediatric sepsis is crucial for the proper treatment of children and reduction of hospitalization and mortality. Biomarkers are a convenient and effective method for diagnosing any disease. However, huge differences among the studies reporting biomarkers for diagnosing sepsis have limited their clinical application. Therefore, in this study, we aimed to evaluate the diagnostic value of key genes involved in paediatric sepsis based on the data of the Gene Expression Omnibus database.

Methods

We used the GSE119217 dataset to identify differentially expressed genes (DEGs) between patients with and without paediatric sepsis. The most relevant gene modules of paediatric sepsis were screened through the weighted gene coexpression network analysis (WGCNA). Common genes (CGs) were found between DEGs and WGCNA. Genes with a potential diagnostic value in paediatric sepsis were selected from the CGs using least absolute shrinkage and selection operator regression and support vector machine recursive feature elimination. The principal component analysis, receiver operating characteristic curves, and C-index were used to verify the diagnostic value of the identified genes in six other independent sepsis datasets. Subsequently, a meta-analysis of the selected genes was performed to evaluate the value of these genes as biomarkers in paediatric sepsis.

Results

A total of 41 CGs were selected from the GSE119217 dataset. A four-gene signature composed of ANXA3, CD177, GRAMD1C, and TIGD3 effectively distinguished patients with paediatric sepsis from those in the control group. The signature was verified using six other independent datasets. In addition, the meta-analysis results showed that the pooled sensitivity, specificity, and area under the curve values were 1.00, 0.98, and 1.00, respectively.

Conclusion

The four-gene signature can be used as new biomarkers to distinguish patients with paediatric sepsis from healthy individuals.

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.

Transcriptome profiles discriminate between Gram-positive and Gram-negative sepsis in preterm neonates

BACKGROUND

Genome-wide expression profiles have been previously employed as clinical research diagnostic tools for newborn sepsis. We aimed to determine if transcriptomic profiles could discriminate between Gram-positive and Gram-negative bacterial sepsis in preterm infants.

METHODS

Prospective, observational, double-cohort study was conducted in very low birth weight infants with clinical signs and culture-positive sepsis. Blood samples were collected when clinical signs became apparent. Total RNA was processed for transcriptomic analysis. Results were validated by both reverse-transcription polymerase chain reaction and a mathematical model.

RESULTS

We included 25 septic preterm infants, 17 with Gram-positive and 8 with Gram-negative bacteria. The principal component analysis identified these two clusters of patients. We performed a predictive model based on 21 genes that showed an area under the receiver-operating characteristic curve of 1. Eight genes were overexpressed in Gram-positive septic infants: CD37, CSK, MAN2B2, MGAT1, MOB3A, MYO9B, SH2D3C, and TEP1. The most significantly overexpressed pathways were related to metabolic and immunomodulating responses that translated into an equilibrium between pro- and anti-inflammatory responses.

CONCLUSIONS

The transcriptomic profile allowed identification of whether the causative agent was Gram-positive or Gram-negative bacteria. The overexpression of genes such as CD37 and CSK, which control cytokine production and cell survival, could explain the better clinical outcome in sepsis caused by Gram-positive bacteria.

IMPACT

Transcriptomic profiles not only enable an early diagnosis of sepsis in very low birth weight infants but also discriminate between Gram-positive and Gram-negative bacteria as causative agents. The overexpression of some genes related to cytokine production and cell survival could explain the better clinical outcome in sepsis caused by Gram-positive bacteria, and could lead us to a future, targeted therapy.

Identification of potential biomarkers and immune infiltration in pediatric sepsis via multiple-microarray analysis

Immune adjustment has become a sepsis occurring in the development of an important mechanism that cannot be ignored. This article from the perspective of immune infiltration of pediatric sepsis screening markers, and promote the understanding of disease mechanisms. Bioinformatics integrated six data sets of pediatric sepsis by using the surrogate variable analysis package and then analyzed differentially expressed genes (DEGs), immune infiltration and weighted gene co-expression network analysis of characteristics (WGCNA) of immune infiltration between pediatric sepsis and the control. Common genes of WGCNA and DEGs were used to functional annotation, pathway enrichment analysis and protein-protein interaction network. Support vector machine (SVM), least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to confirm the key genes for the diagnosis of pediatric sepsis. Receiver operating characteristic (ROC) curve, C index, principal component analysis (PCA) and GiViTi calibration band were used to evaluate the diagnostic performance of key genes. Decision curve analysis (DCA) was used to evaluate the clinical application value of key genes. Lastly, the correlation between key genes and immune cells was analyze. NK cells Resting and NK cell activated in pediatric sepsis during immune infiltration were significantly lower than those in the control group, while M1 Macrophages were higher than those in the control group. ROC, C-index, PCA, GiViTi calibration band and DCA indicated that MCEMP1, CD177, MMP8 and OLFM4 had high diagnostic performance for pediatric sepsis. There is a negative correlation between 4 key genes and NK cells resting, NK cells activated. Except for MCEMP1, the other 3 genes were positively correlated with M1 Macrophages. This study revealed differences in immune responses in pediatric sepsis and identified four key genes as potential biomarkers. Pediatric sepsis in pathology maybe understood better by learning about how it develops.

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Identification of transcriptomics biomarkers for the early prediction of the prognosis of septic shock from pneumopathies

Background

Identifying the biological subclasses of septic shock might provide specific targeted therapies for the treatment and prognosis of septic shock. It might be possible to find biological markers for the early prediction of septic shock prognosis.

Methods

The data were obtained from the Gene Expression Omnibus databases (GEO) in NCBI. GO enrichment and KEGG pathway analyses were performed to investigate the functional annotation of up- and downregulated DEGs. ROC curves were drawn, and their areas under the curves (AUCs) were determined to evaluate the predictive value of the key genes.

Results

117 DEGs were obtained, including 36 up- and 81 downregulated DEGs. The AUC for the MME gene was 0.879, as a key gene with the most obvious upregulation in septic shock. The AUC for the THBS1 gene was 0.889, as a key downregulated gene with the most obvious downregulation in septic shock.

Conclusions

The upregulation of MME via the renin-angiotensin system pathway and the downregulation of THBS1 through the PI3K–Akt signaling pathway might have implications for the early prediction of prognosis of septic shock in patients with pneumopathies.

Androgen Receptor Pathway Activity Assay for Sepsis Diagnosis and Prediction of Favorable Prognosis

Introduction: Sepsis is a life-threatening complication of a bacterial infection. It is hard to predict which patients with a bacterial infection will develop sepsis, and accurate and timely diagnosis as well as assessment of prognosis is difficult. Aside from antibiotics-based treatment of the causative infection and supportive measures, treatment options have remained limited. Better understanding of the immuno-pathophysiology of sepsis is expected to lead to improved diagnostic and therapeutic solutions. Functional activity of the innate (inflammatory) and adaptive immune response is controlled by a dedicated set of cellular signal transduction pathways, that are active in the various immune cell types. To develop an immune response-based diagnostic assay for sepsis and provide novel therapeutic targets, signal transduction pathway activities have been analyzed in whole blood samples from patients with sepsis. Methods: A validated and previously published set of signal transduction pathway (STP) assays, enabling determination of immune cell function, was used to analyze public Affymetrix expression microarray data from clinical studies containing data from pediatric and adult patients with sepsis. STP assays enable quantitative measurement of STP activity on individual patient sample data, and were used to calculate activity of androgen receptor (AR), estrogen receptor (ER), JAK-STAT1/2, JAK-STAT3, Notch, Hedgehog, TGFβ, FOXO-PI3K, MAPK-AP1, and NFκB signal transduction pathways. Results: Activity of AR and TGFβ pathways was increased in children and adults with sepsis. Using the mean plus two standard deviations of normal pathway activity (in healthy individuals) as threshold for abnormal STP activity, diagnostic assay parameters were determined. For diagnosis of pediatric sepsis, the AR pathway assay showed high sensitivity (77%) and specificity (97%), with a positive prediction value (PPV) of 99% and negative prediction value (NPV) of 50%. For prediction of favorable prognosis (survival), PPV was 95%, NPV was 21%. The TGFβ pathway activity assay performed slightly less for diagnosing sepsis, with a sensitivity of 64% and specificity of 98% (PPV 99%, NPV 39%). Conclusion: The AR and TGFβ pathways have an immunosuppressive role, suggesting a causal relation between increased pathway activity and sepsis immunopathology. STP assays have been converted to qPCR assays for further evaluation of clinical utility for sepsis diagnosis and prediction of prognosis, as well as for prediction of risk at developing sepsis in patients with a bacterial infection. STPs may present novel therapeutic targets in sepsis.

Immune Function in Critically Ill Septic Children

The inflammatory response in pediatric sepsis is highly dynamic and includes both pro- and anti-inflammatory elements that involve the innate and adaptive immune systems. While the pro-inflammatory response is responsible for the initial clinical signs and symptoms of sepsis, a concurrent compensatory anti-inflammatory response often results in an occult, but highly clinically relevant, form of acquired immunodeficiency. When severe, this is termed "immunoparalysis" and is associated with increased risks for nosocomial infection, prolonged organ dysfunction, and death. This review focuses on the pathophysiology and clinical implications of both over- and under-active immune function in septic children. Host-, disease-, and treatment-specific risk factors for immunoparalysis are reviewed along with immune phenotype-specific approaches for immunomodulation in pediatric sepsis which are currently the subject of clinical trials.

Reverse Engineering of the Pediatric Sepsis Regulatory Network and Identification of Master Regulators

Sepsis remains a leading cause of death in ICUs all over the world, with pediatric sepsis accounting for a high percentage of mortality in pediatric ICUs. Its complexity makes it difficult to establish a consensus on genetic biomarkers and therapeutic targets. A promising strategy is to investigate the regulatory mechanisms involved in sepsis progression, but there are few studies regarding gene regulation in sepsis. This work aimed to reconstruct the sepsis regulatory network and identify transcription factors (TFs) driving transcriptional states, which we refer to here as master regulators. We used public gene expression datasets to infer the co-expression network associated with sepsis in a retrospective study. We identified a set of 15 TFs as potential master regulators of pediatric sepsis, which were divided into two main clusters. The first cluster corresponded to TFs with decreased activity in pediatric sepsis, and GATA3 and RORA, as well as other TFs previously implicated in the context of inflammatory response. The second cluster corresponded to TFs with increased activity in pediatric sepsis and was composed of TRIM25, RFX2, and MEF2A, genes not previously described as acting in a coordinated way in pediatric sepsis. Altogether, these results show how a subset of master regulators TF can drive pathological transcriptional states, with implications for sepsis biology and treatment.

miRNomic Signature in Very Low Birth-Weight Neonates Discriminates Late-Onset Gram-Positive Sepsis from Controls

Background and Objectives. Neonatal sepsis is a serious condition with a high rate of mortality and morbidity. Currently, the gold standard for sepsis diagnosis is a positive blood culture, which takes 48–72 h to yield results. We hypothesized that identifying differentially expressed miRNA pattern in neonates with late-onset Gram-positive sepsis would help with an earlier diagnosis and therapy. Methods. This is a prospective observational study in newborn infants with late-onset Gram positive bacterial sepsis and non-septic controls. Complementary to blood culture, an aliquot of 0.5 mL of blood was used to determine small non-coding RNA expression profiling using the GeneChip miRNA 4.0 Array. Results. A total of 11 very low birth-weight neonates with late-onset Gram-positive sepsis and 16 controls were analyzed. Further, 217 differentially expressed miRNAs were obtained between both groups. Subsequently, a combined analysis was performed with these miRNAs and 4297 differentially expressed genes. We identified 33 miRNAs that regulate our mRNAs, and the most relevant biological processes are associated with the immune system and the inflammatory response. Conclusions. The miRNA profiling in very low birth-weight neonates distinguishes late-onset Gram-positive sepsis versus control neonates.

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data

We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analysis. Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI ArrayExpress to create a comprehensive meta-analysis microarray expression set (meta-expression set). Measurements had to be obtained via microarray-technique from whole blood samples of adult or pediatric patients with sepsis diagnosed based on international consensus definition immediately after admission to the intensive care unit. We aggregate trauma patients, systemic inflammatory response syndrome (SIRS) patients, and healthy controls in a non-septic entity. Differential expression (DE) analysis is compared with machine-learning-based solutions like decision tree (DT), random forest (RF), support vector machine (SVM), and deep-learning neural networks (DNNs). We evaluated classifier training and discrimination performance in 100 independent iterations. To test diagnostic resilience, we gradually degraded expression data in multiple levels. Clustering of expression values based on DE genes results in partial identification of sepsis samples. In contrast, RF, SVM, and DNN provide excellent diagnostic performance measured in terms of accuracy and area under the curve (>0.96 and >0.99, respectively). We prove DNNs as the most resilient methodology, virtually unaffected by targeted removal of DE genes. By surpassing most other published solutions, the presented approach substantially augments current diagnostic capability in intensive care medicine.

Why COVID-19 is less frequent and severe in children: a narrative review

BACKGROUND

Despite the streaks of severity, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection is, in general, less frequent and severe in children than in adults. We searched for causal evidence of this mystery.

DATA SOURCES

An extensive search strategy was designed to identify papers on coronavirus disease 2019 (COVID-19). We searched Ovid MEDLINE, PubMed, EMBASE databases, and Cochrane library and carried out a review on the causes of this dilemma.

RESULTS

Our searches produced 81 relevant articles. The review showed that children accounted for a lower percentage of reported cases, and they also experienced less severe illness courses. Some potential explanations, including the tendency to engage the upper airway, the different expression in both receptors of angiotensin-converting enzyme and renin-angiotensin system, a less vigorous immune response, the lower levels of interleukin (IL)-6, IL-10, myeloperoxidase, and P-selectin and a higher intracellular adhesion molecule-1, a potential protective role of lymphocytes, and also lung infiltrations might have protective roles in the immune system-respiratory tract interactions. Finally, what have shed light on this under representation comes from two studies that revealed high-titer immunoglobulin-G antibodies against respiratory syncytial virus and mycoplasma pneumonia, may carry out cross-protection against SARS-CoV-2 infection, just like what suggested about the vaccines.

CONCLUSIONS

These results require an in-depth look. Properties of the immune system including a less vigorous adaptive system beside a preliminary potent innate response and a trained immunity alongside a healthier respiratory system, and their interactions, might protect children against SARS-CoV-2 infection. However, further studies are needed to explore other possible causes of this enigma.

Transcriptomic markers in pediatric septic shock prognosis: an integrative analysis of gene expression profiles

The goal of this study was to identify potential transcriptomic markers in pediatric septic shock prognosis by an integrative analysis of multiple public microarray datasets. Using the R software and bioconductor packages, we performed a statistical analysis to identify differentially expressed (DE) genes in pediatric septic shock non-survivors, and further performed functional interpretation (enrichment analysis and co-expression network construction) and classification quality evaluation of the DE genes identified. Four microarray datasets (3 training datasets and 1 testing dataset, 252 pediatric patients with septic shock in total) were collected for the integrative analysis. A total of 32 DE genes (18 upregulated genes; 14 downregulated genes) were identified in pediatric septic shock non-survivors. Enrichment analysis revealed that those DE genes were strongly associated with acute inflammatory response to antigenic stimulus, response to yeast, and defense response to bacterium. A support vector machine classifier (non-survivors vs survivors) was also trained based on DE genes. In conclusion, the DE genes identified in this study are suggested as candidate transcriptomic markers for pediatric septic shock prognosis and provide novel insights into the progression of pediatric septic shock.

Stratified Management for Bacterial Infections in Late Preterm and Term Neonates: Current Strategies and Future Opportunities Toward Precision Medicine

Bacterial infections remain a major cause of morbidity and mortality in the neonatal period. Therefore, many neonates, including late preterm and term neonates, are exposed to antibiotics in the first weeks of life. Data on the importance of inter-individual differences and disease signatures are accumulating. Differences that may potentially influence treatment requirement and success rate. However, currently, many neonates are treated following a "one size fits all" approach, based on general protocols and standard antibiotic treatment regimens. Precision medicine has emerged in the last years and is perceived as a new, holistic, way of stratifying patients based on large-scale data including patient characteristics and disease specific features. Specific to sepsis, differences in disease susceptibility, disease severity, immune response and pharmacokinetics and -dynamics can be used for the development of treatment algorithms helping clinicians decide when and how to treat a specific patient or a specific subpopulation. In this review, we highlight the current and future developments that could allow transition to a more precise manner of antibiotic treatment in late preterm and term neonates, and propose a research agenda toward precision medicine for neonatal bacterial infections.

Whole blood genome-wide transcriptome profiling and metagenomics next-generation sequencing in young infants with suspected sepsis in a low-and middle-income country: A study protocol

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis

Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack of easy-to-use predictive tools that can accurately diagnose sepsis in children. This study aimed to develop an optimal gene model for the diagnosis of pediatric sepsis using statistics and machine learning approaches. Combining gene expression profiles from a training cohort of 364 pediatric samples with a Least Absolute Shrinkage and Selection Operator analysis produced eighteen genes as diagnostic markers. With the implementation of a Gradient Boosting algorithm, a model designated PEDSEPS-GBM, that aggregated these markers was developed with optimal performance for the diagnosis of pediatric samples in the validation and two independent cohorts. Moreover, a web calculator with a user-friendly interface was established for PEDSEPS-GBM. This study presents a diagnostic model that holds great potential for the detection of pediatric sepsis, and demonstrates the biologic and clinical relevance of this model.

Whole blood genome-wide transcriptome profiling and metagenomics next-generation sequencing in young infants with suspected sepsis in low-and middle-income countries: A study protocol

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

Virus-induced genetics revealed by multidimensional precision medicine transcriptional workflow applicable to COVID-19

Precision medicine requires the translation of basic biological understanding to medical insights, mainly applied to characterization of each unique patient. In many clinical settings, this requires tools that can be broadly used to identify pathology and risks. Patients often present to the intensive care unit with broad phenotypes, including multiple organ dysfunction syndrome (MODS) resulting from infection, trauma, or other disease processes. Etiology and outcomes are unique to individuals, making it difficult to cohort patients with MODS, but presenting a prime target for testing/developing tools for precision medicine. Using multitime point whole blood (cellular/acellular) total transcriptomics in 27 patients, we highlight the promise of simultaneously mapping viral/bacterial load, cell composition, tissue damage biomarkers, balance between syndromic biology versus environmental response, and unique biological insights in each patient using a single platform measurement. Integration of a transcriptome workflow yielded unexpected insights into the complex interplay between host genetics and viral/bacterial specific mechanisms, highlighted by a unique case of virally induced genetics (VIG) within one of these 27 patients. The power of RNA-Seq to study unique patient biology while investigating environmental contributions can be a critical tool moving forward for translational sciences applied to precision medicine.

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.

Gene Expression Profiles in Children With Suspected Sepsis

STUDY OBJECTIVE

Sepsis recognition is a clinical challenge in children. We aim to determine whether peripheral blood gene expression profiles are associated with pathogen type and sepsis severity in children with suspected sepsis.

METHODS

This was a prospective pilot observational study in a tertiary pediatric emergency department with a convenience sample of children enrolled. Participants were older than 56 days and younger than 18 years, had suspected sepsis, and had not received broad-spectrum antibiotics in the previous 4 hours. Primary outcome was source pathogen, defined as confirmed bacterial source from sterile body fluid or confirmed viral source. Secondary outcome was sepsis severity, defined as maximum therapy required for shock reversal in the first 3 hospital days. We drew peripheral blood for ribonucleic acid isolation at the sepsis protocol activation, obtained gene expression measures with the GeneChip Human Gene 2.0 ST Array, and conducted differential expression analysis.

RESULTS

We collected ribonucleic acid samples from a convenience sample of 122 children with suspected sepsis and 12 healthy controls. We compared the 66 children (54%) with confirmed bacterial or viral infection and found 558 differentially expressed genes, many related to interferon signaling or viral immunity. We did not find statistically significant gene expression differences in patients according to sepsis severity.

CONCLUSION

The study demonstrates feasibility of evaluating gene expression profiling data in children evaluated for sepsis in the pediatric emergency department setting. Our results suggest that gene expression profiling may facilitate identification of source pathogen in children with suspected sepsis, which could ultimately lead to improved tailoring of sepsis treatment and antimicrobial stewardship.

Immunometabolic approaches to prevent, detect, and treat neonatal sepsis

The first days of postnatal life are energetically demanding as metabolic functions change dramatically to accommodate drastic environmental and physiologic transitions after birth. It is increasingly appreciated that metabolic pathways are not only crucial for nutrition but also play important roles in regulating inflammation and the host response to infection. Neonatal susceptibility to infection is increased due to a functionally distinct immune response characterized by high reliance on innate immune mechanisms. Interactions between metabolism and the immune response are increasingly recognized, as changes in metabolic pathways drive innate immune cell function and activation and consequently host response to pathogens. Moreover, metabolites, such as acetyl-coenzyme A (acetyl-CoA) and succinate have immunoregulatory properties and serve as cofactors for enzymes involved in epigenetic reprogramming or "training" of innate immune cells after an initial infectious exposure. Highly sensitive metabolomic approaches allow us to define alterations in metabolic signatures as they change during ontogeny and as perturbed by immunization or infection, thereby linking metabolic pathways to immune cell effector functions. Characterizing the ontogeny of immunometabolism will offer new opportunities to prevent, diagnose, and treat neonatal sepsis.

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.

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.

Role of SOCS3 in enhanced acute-phase protein genes by neonatal macrophages in response to IL-6

BACKGROUND

Interleukin 6 (IL-6) induce the inflammatory response directly related with the morbidity and mortality of neonatal. Here we aimed to explore the mechanism of IL-6 in neonatal inflammatory response by studying the IL-6/STAT3 signaling pathway.

METHODS

Cord blood samples from health term neonatal and peripheral venous blood from health volunteers were collected. The monocytes of adults and cord blood were isolated and induced into macrophages. Then the macrophages were pretreated with or without MG132 before IL-6 stimulation. Proteins were analyzed by Western blot, mRNA by real time PCR and membrane molecule by flow cytometry.

RESULTS

The acute phase protein gene expression in neonatal macrophages after stimulated with IL-6 were higher than that in adult. Significantly enhanced phosphorylation of STAT3 was seen in neonatal macrophages. Both mRNA and protein expression of SOCS3 in neonatal macrophages were lower than that in adult. After pretreated with MG132, the expression of SOCS3 protein was increased which lead to attenuate the STAT3 phosphorylation and APP gene expression.

CONCLUSION

Neonatal exhibit an enhanced expression of downstream target genes and IL-6/STAT3 signal pathway which is related with the diminished SOCS3. This provides a new sight into inflammatory responses in neonatal.

Neutrophil extracellular traps (NETs) exacerbate severity of infant sepsis

Background

Neutrophil extracellular traps (NETs) are innate defense mechanisms that are also implicated in the pathogenesis of organ dysfunction. However, the role of NETs in pediatric sepsis is unknown.

Methods

Infant (2 weeks old) and adult (6 weeks old) mice were submitted to sepsis by intraperitoneal (i.p.) injection of bacteria suspension or lipopolysaccharide (LPS). Neutrophil infiltration, bacteremia, organ injury, and concentrations of cytokine, NETs, and DNase in the plasma were measured. Production of reactive oxygen and nitrogen species and release of NETs by neutrophils were also evaluated. To investigate the functional role of NETs, mice undergoing sepsis were treated with antibiotic plus rhDNase and the survival, organ injury, and levels of inflammatory markers and NETs were determined. Blood samples from pediatric and adult sepsis patients were collected and the concentrations of NETs measured.

Results

Infant C57BL/6 mice subjected to sepsis or LPS-induced endotoxemia produced significantly higher levels of NETs than the adult mice. Moreover, compared to that of the adult mice, this outcome was accompanied by increased organ injury and production of inflammatory cytokines. The increased NETs were associated with elevated expression of Padi4 and histone H3 citrullination in the neutrophils. Furthermore, treatment of infant septic mice with rhDNase or a PAD-4 inhibitor markedly attenuated sepsis. Importantly, pediatric septic patients had high levels of NETs, and the severity of pediatric sepsis was positively correlated with the level of NETs.

Conclusion

This study reveals a hitherto unrecognized mechanism of pediatric sepsis susceptibility and suggests that NETs represents a potential target to improve clinical outcomes of sepsis.

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2407-8) contains supplementary material, which is available to authorized users.

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.

Phosphatidylglycerols are induced by gut dysbiosis and inflammation, and favorably modulate adipose tissue remodeling in obesity

Lipidomic techniques can improve our understanding of complex lipid interactions that regulate metabolic diseases. Here, a serum phospholipidomics analysis identified associations between phosphatidylglycerols (PGs) and gut microbiota dysbiosis. Compared with the other phospholipids, serum PGs were the most elevated in patients with low microbiota gene richness, which were normalized after a dietary intervention that restored gut microbial diversity. Serum PG levels were positively correlated with metagenomic functional capacities for bacterial LPS synthesis and host markers of low-grade inflammation; transcriptome databases identified PG synthase, the first committed enzyme in PG synthesis, as a potential mediator. Experiments in mice and cultured human-derived macrophages demonstrated that LPS induces PG release. Acute PG treatment in mice altered adipose tissue gene expression toward remodeling and inhibited ex vivo lipolysis in adipose tissue, suggesting that PGs favor lipid storage. Indeed, several PG species were associated with the severity of obesity in mice and humans. Finally, despite enrichment in PGs in bacterial membranes, experiments employing gnotobiotic mice colonized with recombinant PG overproducing Lactococcus lactis showed limited direct contribution of microbial PGs to the host. In summary, PGs are inflammation-responsive lipids indirectly regulated by the gut microbiota via endotoxins and regulate adipose tissue homeostasis in obesity.-Kayser, B. D., Lhomme, M., Prifti, E., Da Cunha, C., Marquet, F., Chain, F., Naas, I., Pelloux, V., Dao, M.-C., Kontush, A., Rizkalla, S. W., Aron-Wisnewsky, J., Bermúdez-Humarán, L. G., Oakley, F., Langella, P., Clément, K., Dugail, I. Phosphatidylglycerols are induced by gut dysbiosis and inflammation, and favorably modulate adipose tissue remodeling in obesity.

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.

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 key genes and pathways using bioinformatics analysis in septic shock children

Background and hypothesis

Sepsis is still one of the reasons for serious infectious diseases in pediatric intensive care unit patients despite the use of anti-infective therapy and organ support therapy. As it is well-known, the effect of single gene or pathway does not play a role in sepsis. We want to explore the interaction of two more genes or pathways in sepsis patients for future works. We hypothesize that the discovery from the available gene expression data of pediatric sepsis patients could know the process or improve the situation.

Methods and results

The gene expression profile dataset GSE26440 of 98 septic shock samples and 32 normal samples using whole blood-derived RNA samples were generated. A total of 1,108 upregulated and 142 downregulated differentially expressed genes (DEGs) were identified in septic shock children using R software packages. The Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were analyzed using DAVID software; Gene Set Enrichment Analysis method was also used for enrichment analysis of the DEGs. The protein-protein interaction (PPI) network and the top 10 hub genes construction of the DEGs were constructed via plug-in Molecular Complex Detection and cytoHubba of Cytoscape software. From the PPI network, the top 10 hub genes, which are all upregulated DEGs in the septic shock children, were identified as GAPDH, TNF, EGF, MAPK3, IL-10, TLR4, MAPK14, IL-1β, PIK3CB, and TLR2. Some of them were involved in one or more significant inflammatory pathways, such as the enrichment of tumor necrosis factor (TNF) pathway in the activation of mitogen-activated protein kinase activity, toll-like receptor signaling pathway, nuclear factor-κB signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway. These findings support future studies on pediatric septic shock.

Network analysis of inflammatory responses to sepsis by neutrophils and peripheral blood mononuclear cells

Sepsis is a life-threatening syndrome causing thousands of deaths yearly worldwide. Sepsis is a result of infection and could lead to systemic inflammatory responses and organ failures. Additionally, blood cells, as the main cells in the immune systems, could be also affected by sepsis. Here, we have used different network analysis approaches, including Weighted Gene Co-expression Network Analysis (WGCNA), Protein-Protein Interaction (PPI), and gene regulatory network, to dissect system-level response to sepsis by the main white blood cells. Gene expression profiles of Neutrophils (NTs), Dendritic Cells (DCs), and Peripheral Blood Mononuclear Cells (PBMCs) that were exposed to septic plasma were obtained and analyzed using bioinformatics approaches. Individual gene expression matrices and the list of differentially expressed genes (DEGs) were prepared and used to construct several networks. Consequently, key regulatory modules and hub genes were detected through network analysis and annotated through ontology analysis extracted from DAVID database. Our results showed that septic plasma affected the regulatory networks in NTs, PBMCs more than the network in DCs. Gene ontology of DEGs revealed that signal transduction and immune cells responses are the most important biological processes affected by sepsis. On the other hand, network analysis detected modules and hub genes in each cell types. It was found that pathways involved in immune cells, signal transduction, and apoptotic processes are among the most affected pathways in the responses to sepsis. Altogether, we have found several hub genes including ADORA3, CD83 CDKN1A, FFAR2, GNAQ, IL1B, LTB, MAPK14, SAMD9L, SOCS1, and STAT1, which might specifically respond to sepsis infection. In conclusion, our results uncovered the system-level responses of the main white blood cells to sepsis and identified several hub genes with potential applications for therapeutic and diagnostic purposes.

Immunomodulation to Prevent or Treat Neonatal Sepsis: Past, Present, and Future

Despite continued advances in neonatal medicine, sepsis remains a leading cause of death worldwide in neonatal intensive care units. The clinical presentation of sepsis in neonates varies markedly from that in older children and adults, and distinct acute inflammatory responses results in age-specific inflammatory and protective immune response to infection. This review first provides an overview of the neonatal immune system, then covers current mainstream, and experimental preventive and adjuvant therapies in neonatal sepsis. We also discuss how the distinct physiology of the perinatal period shapes early life immune responses and review strategies to reduce neonatal sepsis-related morbidity and mortality. A summary of studies that characterize immune ontogeny and neonatal sepsis is presented, followed by discussion of clinical trials assessing interventions such as breast milk, lactoferrin, probiotics, and pentoxifylline. Finally, we critically appraise future treatment options such as stem cell therapy, other antimicrobial protein and peptides, and targeting of pattern recognition receptors in an effort to prevent and/or treat sepsis in this highly vulnerable neonatal population.

Review and Meta-Analyses of TAAR1 Expression in the Immune System and Cancers

Since its discovery in 2001, the major focus of TAAR1 research has been on its role in monoaminergic regulation, drug-induced reward and psychiatric conditions. More recently, TAAR1 expression and functionality in immune system regulation and immune cell activation has become a topic of emerging interest. Here, we review the immunologically-relevant TAAR1 literature and incorporate open-source expression and cancer survival data meta-analyses. We provide strong evidence for TAAR1 expression in the immune system and cancers revealed through NCBI GEO datamining and discuss its regulation in a spectrum of immune cell types as well as in numerous cancers. We discuss connections and logical directions for further study of TAAR1 in immunological function, and its potential role as a mediator or modulator of immune dysregulation, immunological effects of psychostimulant drugs of abuse, and cancer progression.

The relative resistance of children to sepsis mortality: from pathways to drug candidates

Attempts to develop drugs that address sepsis based on leads developed in animal models have failed. We sought to identify leads based on human data by exploiting a natural experiment: the relative resistance of children to mortality from severe infections and sepsis. Using public datasets, we identified key differences in pathway activity (Pathprint) in blood transcriptome profiles of septic adults and children. To find drugs that could promote beneficial (child) pathways or inhibit harmful (adult) ones, we built an in silico pathway drug network (PDN) using expression correlation between drug, disease, and pathway gene signatures across 58,475 microarrays. Specific pathway clusters from children or adults were assessed for correlation with drug‐based signatures. Validation by literature curation and by direct testing in an endotoxemia model of murine sepsis of the most correlated drug candidates demonstrated that the Pathprint‐PDN methodology is more effective at generating positive drug leads than gene‐level methods (e.g., CMap). Pathway‐centric Pathprint‐PDN is a powerful new way to identify drug candidates for intervention against sepsis and provides direct insight into pathways that may determine survival.

Validation of the Sepsis MetaScore for Diagnosis of Neonatal Sepsis

WHAT’S KNOWN ON THIS SUBJECT

Neonates are at increased risk for developing sepsis, but this population often exhibits ambiguous clinical signs that complicate the diagnosis of infection. No biomarker has yet shown enough diagnostic accuracy to rule out sepsis at the time of clinical suspicion.

WHAT THIS STUDY ADDS

We show that a gene-expression-based signature is an accurate objective measure of the risk of sepsis in a neonate or preterm infant, and it substantially improves diagnostic accuracy over that of commonly used laboratory-based testing. Implementation might decrease inappropriate antibiotic use.

BACKGROUND

Neonatal sepsis can have devastating consequences, but accurate diagnosis is difficult. As a result, up to 200 neonates with suspected sepsis are treated with empiric antibiotics for every 1 case of microbiologically confirmed sepsis. These unnecessary antibiotics enhance bacterial antibiotic resistance, increase economic costs, and alter gut microbiota composition. We recently reported an 11-gene diagnostic test for sepsis (Sepsis MetaScore) based on host whole-blood gene expression in children and adults, but this test has not been evaluated in neonates.

METHODS

We identified existing gene expression microarray-based cohorts of neonates with sepsis. We then tested the accuracy of the Sepsis MetaScore both alone and in combination with standard diagnostic laboratory tests in diagnosing sepsis.

RESULTS

We found 3 cohorts with a total of 213 samples from control neonates and neonates with sepsis. The Sepsis MetaScore had an area under the receiver operating characteristic curve of 0.92-0.93 in all 3 cohorts. We also found that, as a diagnostic test for sepsis, it outperformed standard laboratory measurements alone and, when used in combination with another test(s), resulted in a significant net reclassification index (0.3-0.69) in 5 of 6 comparisons. The mean point estimates for sensitivity and specificity were 95% and 60%, respectively, which, if confirmed prospectively and applied in a high-risk cohort, could reduce inappropriate antibiotic usage substantially.

CONCLUSIONS

The Sepsis MetaScore had excellent diagnostic accuracy across 3 separate cohorts of neonates from 3 different countries. Further prospective targeted study will be needed before clinical application.

Hyperchloremia Is Associated With Complicated Course and Mortality in Pediatric Patients With Septic Shock

OBJECTIVE

Hyperchloremia is associated with poor outcome among critically ill adults, but it is unknown if a similar association exists among critically ill children. We determined if hyperchloremia is associated with poor outcomes in children with septic shock.

DESIGN

Retrospective analysis of a pediatric septic shock database.

SETTING

Twenty-nine PICUs in the United States.

PATIENTS

Eight hundred ninety children 10 years and younger with septic shock.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We considered the minimum, maximum, and mean chloride values during the initial 7 days of septic shock for each study subject as separate hyperchloremia variables. Within each category, we considered hyperchloremia as a dichotomous variable defined as a serum concentration greater than or equal to 110 mmol/L. We used multivariable logistic regression to determine the association between the hyperchloremia variables and outcome, adjusted for illness severity. We considered all cause 28-day mortality and complicated course as the primary outcome variables. Complicated course was defined as mortality by 28 days or persistence of greater than or equal to two organ failures at day 7 of septic shock. Secondarily, we conducted a stratified analysis using a biomarker-based mortality risk stratification tool. There were 226 patients (25%) with a complicated course and 93 mortalities (10%). Seventy patients had a minimum chloride greater than or equal to 110 mmol/L, 179 had a mean chloride greater than or equal to 110 mmol/L, and 514 had a maximum chloride greater than or equal to 110 mmol/L. A minimum chloride greater than or equal to 110 mmol/L was associated with increased odds of complicated course (odds ratio, 1.9; 95% CI, 1.1-3.2; p = 0.023) and mortality (odds ratio, 3.7; 95% CI, 2.0-6.8; p < 0.001). A mean chloride greater than or equal to 110 mmol/L was also associated with increased odds of mortality (odds ratio, 2.1; 95% CI, 1.3-3.5; p = 0.002). The secondary analysis yielded similar results.

CONCLUSION

Hyperchloremia is independently associated with poor outcomes among children with septic shock.

IL-17 in neonatal health and disease

Over the last few years, scientific interest in the cytokine IL-17A has intensified as its role in human health and disease has been elucidated. Discovered almost a quarter century ago, IL-17A is known to have poor biologic activity when acting alone, but attains robust actions when working synergistically with potent mediators of proinflammatory immune responses, such as IL-6 and IL-8. IL-17A is produced by specialized innate immune cells that protect host barriers from the outside world. Like sentries, these innate immune cells can "sound the alarm" through increased production of IL-17A, causing activation and recruitment of primed neutrophils and monocytes when pathogens escape initial host defenses. In this way, IL-17A promulgates mechanisms responsible for pathogen death and clearance. However, when IL-17A pathways are triggered during fetal development, due to chorioamnionitis or in utero inflammatory conditions, IL-17A can instigate and/or exacerbate fetal inflammatory responses that increase neonatal morbidities and mortality associated with common neonatal conditions such as sepsis, bronchopulmonary dysplasia (BPD), patent ductus arteriosus (PDA), and necrotizing enterocolitis (NEC). This review details the ontogeny of IL-17A in the fetus and newborn, discusses how derangements in its production can lead to pathology, and describes known and evolving therapies that may attenuate IL-17A-mediated human conditions.