Gene expression signatures identify paediatric patients with multiple organ dysfunction who require advanced life support in the intensive care unit

Analysis and validation of hub genes in neutrophil extracellular traps for the long-term prognosis of myocardial infarction

INTRODUCTION

The study focuses on the long-term prognosis of myocardial infarction (MI) influenced by neutrophil extracellular traps (NETs). It also aims to analyze and validate relative hub genes in this process, in order to further explore new therapeutic targets that can improve the prognosis of MI.

MATERIALS AND METHODS

We established a MI model in mice by ligating the left anterior descending branch (LAD) and conducted an 8-week continuous observation to study the dynamic changes in the structure and function of the heart in these mice. Meanwhile, we administered Apocynin, an inhibitor of NADPH Oxidase, which has also been shown to inhibit the formation of NETs, to mice undergoing MI surgery in order to compare. This study employed hematoxylin-eosin (HE) staining, echocardiography, immunofluorescence, and real-time quantitative PCR (RT-qPCR) to examine the impact of NETs on the long-term prognosis of MI. Next, datasets related to MI and NETs were downloaded from the GEO database, respectively. The Limma package of R software was used to identify differentially expressed genes (DEGs). After analyzing the "Robust Rank Aggregation (RRA)" package, we conducted a screening for robust differentially expressed genes (DEGs) and performed pathway enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to determine the functional roles of these robust DEGs. The protein-protein interaction (PPI) network was visualized and hub genes were filtered using Cytoscape.

RESULTS

Immunofluorescence and qPCR results showed an increase in the expression of Myeloperoxidase (MPO) at week 1 and week 8 in the hearts of mice after MI. HE staining reveals a series of pathological manifestations in the heart of the MI group during 8 weeks, including enlarged size, disordered arrangement of cardiomyocytes, infiltration of inflammatory cells, and excessive deposition of collagen fibers, among others. The utilization of Apocynin could significantly improve these poor performances. The echocardiography displayed the cardiac function of the heart in mice. The MI group has a reduced range of heart movement and decreased ejection ability. Moreover, the ventricular systolic movement was found to be abnormal, and its wall thickening rate decreased over time, indicating a progressive worsening of myocardial ischemia. The Apocynin group, on the contrary, showed fewer abnormal changes in the aforementioned aspects. A total of 81 DEGs and 4 hub genes (FOS, EGR1, PTGS2, and HIST1H4H) were obtained. The results of RT-qPCR demonstrated abnormal expression of these four genes in the MI group, which could be reversed by treatment of Apocynin.

CONCLUSION

The NETs formation could be highly related to MI and the long-term prognosis of MI can be significantly influenced by the NETs formation. Four hub genes, namely FOS, EGR1, PTGS2, and HIST1H4H, have the potential to be key genes related to this process. They could also serve as biomarkers for predicting MI prognosis and as targets for gene therapy.

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.

The Gene Expression Profiles Associated with Maternal Nicotine Exposure in the Liver of Offspring Mice

This study aims to investigate the effect of maternal nicotine exposure on the gene expression profiles in the liver of offspring mice. Pregnant mice were subcutaneously injected with either saline vehicle or nicotine twice a day on gestational days 11-21. Total RNA from the liver samples which collected from the offspring mice of postnatal day 7 and 21 was subjected to RNA sequencing. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were conducted to identify the functions of differentially expressed genes (DEGs). Four genes were selected for further validation by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A total of 448 DEGs and 186 DEGs were identified on postnatal day 7 and 21, respectively. GO analysis revealed that the DEGs on postnatal day 7 mainly participated in the biological functions of cell growth and proliferation, and the DEGs on postnatal day 21 mainly participated in ion transport/activity. KEGG enrichment analysis showed that the DEGs on postnatal day 7 were mainly enriched in the cell cycle, cytokine-cytokine receptor interactions, hypertrophic cardiomyopathy, and the p53 signaling pathway, while the DEGs on postnatal day 21 were mainly enriched in neuroactive ligand-receptor interactions, the calcium signaling pathway, retinol metabolism, and axon guidance. The qRT-PCR results were consistent with the RNA sequencing data. The DEGs may affect the growth of liver in early postnatal period while may affect ion transport/activity in late postnatal period.

Exploring potential biomarkers and therapeutic targets of long COVID-associated inflammatory cardiomyopathy

Background

The negative impact of long COVID on social life and human health is increasingly prominent, and the elevated risk of cardiovascular disease in patients recovering from COVID-19 has also been fully confirmed. However, the pathogenesis of long COVID-related inflammatory cardiomyopathy is still unclear. Here, we explore potential biomarkers and therapeutic targets of long COVID-associated inflammatory cardiomyopathy.

Methods

Datasets that met the study requirements were identified in Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were obtained by the algorithm. Then, functional enrichment analysis was performed to explore the basic molecular mechanisms and biological processes associated with DEGs. A protein-protein interaction (PPI) network was constructed and analyzed to identify hub genes among the common DEGs. Finally, a third dataset was introduced for validation.

Results

Ultimately, 3,098 upregulated DEGs and 1965 downregulated DEGs were extracted from the inflammatory cardiomyopathy dataset. A total of 89 upregulated DEGs and 217 downregulated DEGs were extracted from the dataset of convalescent COVID patients. Enrichment analysis and construction of the PPI network confirmed VEGFA, FOXO1, CXCR4, and SMAD4 as upregulated hub genes and KRAS and TXN as downregulated hub genes. The separate dataset of patients with COVID-19 infection used for verification led to speculation that long COVID-associated inflammatory cardiomyopathy is mainly attributable to the immune-mediated response and inflammation rather than to direct infection of cells by the virus.

Conclusion

Screening of potential biomarkers and therapeutic targets sheds new light on the pathogenesis of long COVID-associated inflammatory cardiomyopathy as well as potential therapeutic approaches. Further clinical studies are needed to explore these possibilities in light of the increasingly severe negative impacts of long COVID.

Identification of potential biomarkers and therapeutic targets for posttraumatic acute respiratory distress syndrome

BACKGROUND

Despite improved supportive care, posttraumatic acute respiratory distress syndrome (ARDS) mortality has improved very little in recent years. Additionally, ARDS diagnosis is delayed or missed in many patients. We analyzed co-differentially expressed genes (co-DEGs) to explore the relationships between severe trauma and ARDS to reveal potential biomarkers and therapeutic targets for posttraumatic ARDS.

METHODS

Two gene expression datasets (GSE64711 and GSE76293) were downloaded from the Gene Expression Omnibus. The GSE64711 dataset included a subset of 244 severely injured trauma patients and 21 healthy controls. GSE76293 specimens were collected from 12 patients with ARDS who were recruited from trauma intensive care units and 11 age- and sex-matched healthy volunteers. Trauma DEGs and ARDS DEGs were identified using the two datasets. Subsequently, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction network analyses were performed to elucidate the molecular functions of the DEGs. Then, hub genes of the co-DEGs were identified. Finally, to explore whether posttraumatic ARDS and septic ARDS are common targets, we included a third dataset (GSE100159) for corresponding verification.

RESULTS

90 genes were upregulated and 48 genes were downregulated in the two datasets and were therefore named co-DEGs. These co-DEGs were significantly involved in multiple inflammation-, immunity- and neutrophil activation-related biological processes. Ten co-upregulated hub genes (GAPDH, MMP8, HGF, MAPK14, LCN2, CD163, ENO1, CD44, ARG1 and GADD45A) and five co-downregulated hub genes (HERC5, IFIT2, IFIT3, RSAD2 and IFIT1) may be considered potential biomarkers and therapeutic targets for posttraumatic ARDS. Through the verification of the third dataset, posttraumatic ARDS may have its own unique targets worthy of further exploration.

CONCLUSION

This exploratory analysis supports a relationship between trauma and ARDS pathophysiology, specifically in relationship to the identified hub genes. These data may serve as potential biomarkers and therapeutic targets for posttraumatic ARDS.

Introduction to Personalized Medicine in Pediatrics

Exciting new developments in biomedical and computational sciences provide an extraordinary and unparalleled opportunity to compile, connect, and analyze multiple types of "big data," driving the development of personalized medicine. These insights must begin in early life (ie, pregnancy, neonatal, and infancy) and focus on early prevention, diagnosis, and intervention-areas of medicine where pediatricians are poised to lead the way to a personalized medicine future. The rapid growth of genomics (including pharmacogenomics), transcriptomics, and related "omics" has revolutionized the diagnosis of rare monogenic disorders. It is now clarifying the pathogenesis of complex conditions ranging from autism spectrum disorder to asthma. Collaborations between clinicians and basic scientists integrating multiomics approaches in evaluating children with severe illness are transforming the fields of perinatal, neonatal, and pediatric critical care medicine. Improvements in rapid diagnostic and prognostic information suggest that pediatric personalized medicine is under way and has an exciting future. [Pediatr Ann. 2022;51(10):e381-e386.].

Proteomic profiling of serum small extracellular vesicles reveals immune signatures of children with pneumonia

BACKGROUND

Pneumonia is the leading cause of death in young children globally. However, the underlying pathological mechanism of pediatric pneumonia remains unclear. In infection disease contexts, small extracellular vesicles (sEVs) have been shown to be a useful source of markers for pathogenesis and immune response. We hypothesized that functional molecules such as protein harbored by sEVs would provide mechanistic insights into the immune response in children with pneumonia.

METHODS

We isolated sEVs from serum collected from children with and without pneumonia, performed proteomic analysis of the sEVs with label-free mass spectrometry, and then conducted functional enrichment analysis of proteomic data.

RESULTS

We identified fifteen differentially expressed proteins and ten unique proteins in children with pneumonia as compared to healthy children. In the pneumonia group, immune-related processes and pathways were positively enriched as upregulated proteins were involved in neutrophil activation, complement regulation, defense against bacteria, humoral immune response and regulation of immune effector processes However, pathways associated with tissue development and extracellular matrix remodeling were negatively enriched, as downregulated proteins were linked to extracellular matrix structure and cell adhesions.

CONCLUSIONS

Our findings provided insights into host responses to pathogen infection, which has contributed to understanding the pathogenesis of children with pneumonia. Furthermore, our studies suggested that serum sEVs proteins could be considered a potential source of biomarkers for diagnosing pediatric pneumonia.

Screening the Potential Biomarkers of COVID-19-Related Thrombosis Through Bioinformatics Analysis

A high proportion of critically ill patients with coronavirus disease 2019 (COVID-19) experience thrombosis, and there is a strong correlation between anticoagulant therapy and the COVID-19 survival rate, indicating that common COVID-19 and thrombosis targets have potential therapeutic value for severe COVID-19.Gene expression profiling data were downloaded from Gene Expression Omnibus (GEO), and common differentially expressed genes (co-DEGs) were identified. The potential biological functions of these co-DEGs were explored by functional enrichment analysis, and protein–protein interaction (PPI) networks were constructed to elucidate the molecular mechanisms of the co-DEGs. Finally, hub genes in the co-DEG network were identified, and correlation analysis was performed.We identified 8320 upregulated genes and 7651 downregulated genes from blood samples of COVID-19 patients and 368 upregulated genes and 240 downregulated genes from blood samples of thrombosis patients. The enriched cellular component terms were mainly related to cytosolic ribosomes and ribosomal subunits. The enriched molecular function terms were mainly related to structural constituents of ribosomes and electron transfer activity. Construction of the PPI network and identification of hub genes ultimately confirmed that RPS7, IGF1R, DICER1, ERH, MCTS1, and TNPO1 were jointly upregulated hub genes, and FLNA and PXN were jointly downregulated hub genes.The identification of novel potential biomarkers provides new options for treating COVID-19-related thrombosis and reducing the rate of severe COVID-19.

Luteolin can ameliorate renal interstitial fibrosis-induced renal anaemia through the SIRT1/FOXO3 pathway

Luteolin is a natural flavonoid exhibiting multiple pharmacological activities.

Multiple Organ Dysfunction Interactions in Critically Ill Children

INTRODUCTION

Multiple organ dysfunction (MOD) is a common pathway to morbidity and death in critically ill children. Defining organ dysfunction is challenging, as we lack a complete understanding of the complex pathobiology. Current pediatric organ dysfunction criteria assign the same diagnostic value-the same "weight"- to each organ system. While each organ dysfunction in isolation contributes to the outcome, there are likely complex interactions between multiple failing organs that are not simply additive.

OBJECTIVE

Determine whether certain combinations of organ system dysfunctions have a significant interaction associated with higher risk of morbidity or mortality in critically ill children.

METHODS

We conducted a retrospective observational cohort study of critically ill children at two large academic medical centers from 2010 and 2018. Patients were included in the study if they had at least two organ dysfunctions by day 3 of PICU admission based on the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) criteria. Mortality was described as absolute number of deaths and mortality rate. Combinations of two pediatric organ dysfunctions were analyzed with interaction terms as independent variables and mortality or persistent MOD as the dependent variable in logistic regression models.

RESULTS

Overall, 7,897 patients met inclusion criteria and 446 patients (5.6%) died. The organ dysfunction interactions that were significantly associated with the highest absolute number of deaths were cardiovascular + endocrinologic, cardiovascular + neurologic, and cardiovascular + respiratory. Additionally, the interactions associated with the highest mortality rates were liver + cardiovascular, respiratory + hematologic, and respiratory + renal. Among patients with persistent MOD, the most common organ dysfunctions with significant interaction terms were neurologic + respiratory, hematologic + immunologic, and endocrinologic + respiratory. Further analysis using classification and regression trees (CART) demonstrated that the absence of respiratory and liver dysfunction was associated with the lowest likelihood of mortality.

IMPLICATIONS AND FUTURE DIRECTIONS

Certain combinations of organ dysfunctions are associated with a higher risk of persistent MOD or death. Notably, the three most common organ dysfunction interactions were associated with 75% of the mortality in our cohort. Critically ill children with MOD presenting with these combinations of organ dysfunctions warrant further study.

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.

Identification of COVID-19 subtypes based on immunogenomic profiling

Although previous studies have shown that the host immune response is crucial in determining clinical outcomes in COVID-19 patients, the association between host immune signatures and COVID-19 patient outcomes remains unclear. Based on the enrichment levels of 11 immune signatures (eight immune-inciting and three immune-inhibiting signatures) in leukocytes of 100 COVID-19 patients, we identified three COVID-19 subtypes: Im-C1, Im-C2, and Im-C3, by clustering analysis. Im-C1 had the lowest immune-inciting signatures and high immune-inhibiting signatures. Im-C2 had medium immune-inciting signatures and high immune-inhibiting signatures. Im-C3 had the highest immune-inciting signatures while the lowest immune-inhibiting signatures. Im-C3 and Im-C1 displayed the best and worst clinical outcomes, respectively, suggesting that antiviral immune responses alleviated the severity of COVID-19 patients. We further demonstrated that the adaptive immune response had a stronger impact on COVID-19 outcomes than the innate immune response. The patients in Im-C3 were younger than those in Im-C1, indicating that younger persons have stronger antiviral immune responses than older persons. Nevertheless, we did not observe a significant association between sex and immune responses in COVID-19 patients. In addition, we found that the type II IFN response signature was an adverse prognostic factor for COVID-19. Our identification of COVID-19 immune subtypes has potential clinical implications for the management of COVID-19 patients.

Pediatric Multi-Organ Dysfunction Syndrome: Analysis by an Untargeted "Shotgun" Lipidomic Approach Reveals Low-Abundance Plasma Phospholipids and Dynamic Recovery over 8-Day Period, a Single-Center Observational Study

Lipids are molecules involved in metabolism and inflammation. This study investigates the plasma lipidome for markers of severity and nutritional status in critically ill children. Children with multi-organ dysfunction syndrome (MODS) (n = 24) are analyzed at three time-points and cross-referenced to sedation controls (n = 4) for a total of N = 28. Eight of the patients with MODS, needed veno-arterial extracorporeal membrane oxygenation (VA ECMO) support to survive. Blood plasma lipid profiles are quantified by nano-electrospray (nESI), direct infusion high resolution/accurate mass spectrometry (MS), and tandem mass spectrometry (MS/MS), and compared to nutritional profiles and pediatric logistic organ dysfunction (PELOD) scores. Our results show that PELOD scores were not significantly different between MODS and ECMO cases across time-points (p = 0.66). Lipid profiling provides stratification between sedation controls and all MODS patients for total lysophosphatidylserine (lysoPS) (p-value = 0.004), total phosphatidylserine (PS) (p-value = 0.015), and total ether-linked phosphatidylethanolamine (ether-PE) (p-value = 0.03) after adjusting for sex and age. Nutrition intake over time did not correlate with changes in lipid profiles, as measured by caloric and protein intake. Lipid measurement in the intensive care environment shows dynamic changes over an 8-day pediatric intensive care unit (PICU) course, suggesting novel metabolic indicators for defining critically ill children.

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.

circST6GALNAC6 suppresses bladder cancer metastasis by sponging miR-200a-3p to modulate the STMN1/EMT axis

Bladder cancer (BCa) is an aggressive malignancy because of its distant metastasis and high recurrence rate. Circular RNAs (circRNAs) exert critical regulatory functions in cancer progression. However, the expression patterns and roles of circRNAs in BCa have not been well investigated. In this study, we first screened circRNA expression profiles using a circRNA microarray of paired BCa and normal tissues, and the expression of circST6GALNAC6 was confirmed by qRT-PCR and fluorescence in situ hybridization (FISH). MTT, colony formation and Transwell assays were performed to measure cell proliferation, migration and invasion. We investigated the regulatory effect of circST6GALNAC6 on miRNA and its target genes to explore the potential regulatory mechanisms of circST6GALNAC6 by chromatin immunoprecipitation (ChIP), RNA immunoprecipitation (RIP), MS2-tagged RNA affinity purification (MS2-TRAP), immunofluorescence (IF) and dual luciferase activity assays. A nude mouse xenograft model was used to examine the functions of circST6GALNAC6/STMN1 in tumour metastasis in vivo. We found that 881 circRNAs were significantly dysregulated in BCa tissues compared to normal tissues. circST6GALNAC6(hsa_circ_0088708) was downregulated in BCa tissues and cells. Overexpression of circST6GALNAC6 effectively inhibited the cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in vitro and suppressed BCa metastasis in vivo. Mechanistically, we showed that the SP1 transcription factor, which binds to the circST6GALNAC6 mRNA transcript, activates circST6GALNAC6 transcription. Next, we verified that circST6GALNAC6 serves as a sponge that directly binds miR-200a-3p to regulate stathmin (STMN1) expression. Furthermore, we found that STMN1 is involved in circST6GALNAC6/miR-200a-3p axis-regulated BCa EMT and metastasis. Thus, our findings indicate an important underlying mechanism in BCa metastasis by which SP1-induced circST6GALNAC6 sponges miR-200a-3p to promote STMN1/EMT signalling. This mechanism could provide pivotal potential prognostic biomarkers and therapeutic targets for BCa.