Host gene expression signatures to identify infection type and organ dysfunction in children evaluated for sepsis: a multicentre cohort study.

BACKGROUND: Sepsis is defined as dysregulated host response to infection that leads to life-threatening organ dysfunction. Biomarkers characterising the dysregulated host response in sepsis are lacking. We aimed to develop host gene expression signatures to predict organ dysfunction in children with bacterial or viral infection. METHODS: This cohort study was done in emergency departments and intensive care units of four hospitals in Queensland, Australia, and recruited children aged 1 month to 17 years who, upon admission, underwent a diagnostic test, including blood cultures, for suspected sepsis. Whole-blood RNA sequencing of blood was performed with Illumina NovaSeq (San Diego, CA, USA). Samples with completed phenotyping, monitoring, and RNA extraction by March 31, 2020, were included in the discovery cohort; samples collected or completed thereafter and by Oct 27, 2021, constituted the Rapid Paediatric Infection Diagnosis in Sepsis (RAPIDS) internal validation cohort. An external validation cohort was assembled from RNA sequencing gene expression count data from the observational European Childhood Life-threatening Infectious Disease Study (EUCLIDS), which recruited children with severe infection in nine European countries between 2012 and 2016. Feature selection approaches were applied to derive novel gene signatures for disease class (bacterial vs viral infection) and disease severity (presence vs absence of organ dysfunction 24 h post-sampling). The primary endpoint was the presence of organ dysfunction 24 h after blood sampling in the presence of confirmed bacterial versus viral infection. Gene signature performance is reported as area under the receiver operating characteristic curves (AUCs) and 95% CI. FINDINGS: Between Sept 25, 2017, and Oct 27, 2021, 907 patients were enrolled. Blood samples from 595 patients were included in the discovery cohort, and samples from 312 children were included in the RAPIDS validation cohort. We derived a ten-gene disease class signature that achieved an AUC of 94·1% (95% CI 90·6-97·7) in distinguishing bacterial from viral infections in the RAPIDS validation cohort. A ten-gene disease severity signature achieved an AUC of 82·2% (95% CI 76·3-88·1) in predicting organ dysfunction within 24 h of sampling in the RAPIDS validation cohort. Used in tandem, the disease class and disease severity signatures predicted organ dysfunction within 24 h of sampling with an AUC of 90·5% (95% CI 83·3-97·6) for patients with predicted bacterial infection and 94·7% (87·8-100·0) for patients with predicted viral infection. In the external EUCLIDS validation dataset (n=362), the disease class and disease severity predicted organ dysfunction at time of sampling with an AUC of 70·1% (95% CI 44·1-96·2) for patients with predicted bacterial infection and 69·6% (53·1-86·0) for patients with predicted viral infection. INTERPRETATION: In children evaluated for sepsis, novel host transcriptomic signatures specific for bacterial and viral infection can identify dysregulated host response leading to organ dysfunction. FUNDING: Australian Government Medical Research Future Fund Genomic Health Futures Mission, Children's Hospital Foundation Queensland, Brisbane Diamantina Health Partners, Emergency Medicine Foundation, Gold Coast Hospital Foundation, Far North Queensland Foundation, Townsville Hospital and Health Services SERTA Grant, and Australian Infectious Diseases Research Centre.

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.

Transcriptomic profiles of multiple organ dysfunction syndrome phenotypes in pediatric critical influenza.

Background: Influenza virus is responsible for a large global burden of disease, especially in children. Multiple Organ Dysfunction Syndrome (MODS) is a life-threatening and fatal complication of severe influenza infection. Methods: We measured RNA expression of 469 biologically plausible candidate genes in children admitted to North American pediatric intensive care units with severe influenza virus infection with and without MODS. Whole blood samples from 191 influenza-infected children (median age 6.4 years, IQR: 2.2, 11) were collected a median of 27 hours following admission; for 45 children a second blood sample was collected approximately seven days later. Extracted RNA was hybridized to NanoString mRNA probes, counts normalized, and analyzed using linear models controlling for age and bacterial co-infections (FDR q<0.05). Results: Comparing pediatric samples collected near admission, children with Prolonged MODS for ≥7 days (n=38; 9 deaths) had significant upregulation of nine mRNA transcripts associated with neutrophil degranulation (RETN, TCN1, OLFM4, MMP8, LCN2, BPI, LTF, S100A12, GUSB) compared to those who recovered more rapidly from MODS (n=27). These neutrophil transcripts present in early samples predicted Prolonged MODS or death when compared to patients who recovered, however in paired longitudinal samples, they were not differentially expressed over time. Instead, five genes involved in protein metabolism and/or adaptive immunity signaling pathways (RPL3, MRPL3, HLA-DMB, EEF1G, CD8A) were associated with MODS recovery within a week. Conclusion: Thus, early increased expression of neutrophil degranulation genes indicated worse clinical outcomes in children with influenza infection, consistent with reports in adult cohorts with influenza, sepsis, and acute respiratory distress syndrome.

Longitudinal Analysis of Contrasts in Gene Expression Data.

We are interested in detecting a departure from the baseline in a longitudinal analysis in the context of multiple organ dysfunction syndrome (MODS). In particular, we are given gene expression reads at two time points for a fixed number of genes and individuals. The individuals can be subdivided into two groups, denoted as groups A and B. Using the two time points, we compute a contrast of gene expression reads per individual and gene. The age of each individual is known and it is used to compute, for each gene separately, a linear regression of the gene expression contrasts on the individual's age. Looking at the intercept of the linear regression to detect a departure from the baseline, we aim to reliably single out those genes for which there is a difference in the intercept among those individuals in group A and not in group B. In this work, we develop testing methodology for this setting based on two hypothesis tests-one under the null and one under an appropriately formulated alternative. We demonstrate the validity of our approach using a dataset created by bootstrapping from a real data application in the context of multiple organ dysfunction syndrome (MODS).

TREM-1 as a Marker of Multiple Organ Failure in Cardiac Surgery.

Systemic inflammatory response syndrome (SIRS) frequently accompanies early postoperative period after cardiac surgery and in some cases is complicated by multiple organ failure (MOF). Inherited variation in the innate immune response genes (e.g., TREM1) is among the major factors determining the development of SIRS and the risk of MOF. This research was aimed to study whether the polymorphisms within the TREM1 gene are associated with MOF after the coronary artery bypass graft (CABG) surgery. Here we enrolled 592 patients who underwent CABG surgery in the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia) and documented 28 cases of MOF. Genotyping was performed by allele-specific PCR using TaqMan probes. In addition, we measured serum soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) using enzyme-linked immunosorbent assay. Five polymorphisms (rs1817537, rs2234246, rs3804277, rs7768162 andrs4711668) within the TREM1 gene were significantly associated with MOF. Patients with MOF had higher serum sTREM-1 as compared with those without MOF at both pre- and post-intervention stages. Serum sTREM-1 was associated with the rs1817537,rs2234246 and rs3804277 polymorphisms within the TREM1 gene. Minor alleles within the TREM1 gene define the level of serum sTREM-1 and are associated with MOF after CABG surgery.

Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) is a common complication in sepsis. However, the trajectories of sepsis-induced AKI and their transcriptional profiles are not well characterized. METHODS: Sepsis patients admitted to centres participating in Chinese Multi-omics Advances In Sepsis (CMAISE) from November 2020 to December 2021 were enrolled, and gene expression in peripheral blood mononuclear cells was measured on Day 1. The renal function trajectory was measured by the renal component of the SOFA score (SOFArenal) on Days 1 and 3. Transcriptional profiles on Day 1 were compared between these renal function trajectories, and a support vector machine (SVM) was developed to distinguish transient from persistent AKI. RESULTS: A total of 172 sepsis patients were enrolled during the study period. The renal function trajectory was classified into four types: non-AKI (SOFArenal = 0 on Days 1 and 3, n = 50), persistent AKI (SOFArenal > 0 on Days 1 and 3, n = 62), transient AKI (SOFArenal > 0 on Day 1 and SOFArenal = 0 on Day 3, n = 50) and worsening AKI (SOFArenal = 0 on Days 1 and SOFArenal > 0 on Day 3, n = 10). The persistent AKI group showed severe organ dysfunction and prolonged requirements for organ support. The worsening AKI group showed the least organ dysfunction on day 1 but had higher serum lactate and prolonged use of vasopressors than the non-AKI and transient AKI groups. There were 2091 upregulated and 1,902 downregulated genes (adjusted p < 0.05) between the persistent and transient AKI groups, with enrichment in the plasma membrane complex, receptor complex, and T-cell receptor complex. A 43-gene SVM model was developed using the genetic algorithm, which showed significantly greater performance predicting persistent AKI than the model based on clinical variables in a holdout subset (AUC: 0.948 [0.912, 0.984] vs. 0.739 [0.648, 0.830]; p < 0.01 for Delong's test). CONCLUSIONS: Our study identified four subtypes of sepsis-induced AKI based on kidney injury trajectories. The landscape of host response aberrations across these subtypes was characterized. An SVM model based on a gene signature was developed to predict renal function trajectories, and showed better performance than the clinical variable-based model. Future studies are warranted to validate the gene model in distinguishing persistent from transient AKI.

Mitochondrial DNA as a Candidate Marker of Multiple Organ Failure after Cardiac Surgery.

Assess the level of mitochondrial DNA depending on the presence of multiple organ failure in patients after heart surgery. The study included 60 patients who underwent surgical treatment of valvular heart disease using cardiopulmonary bypass. Uncomplicated patients were included in the 1st group (n = 30), patients with complications and multiple organ failure (MOF) were included in the 2nd group (n = 30). Serum mtDNA levels were determined by quantitative real-time polymerase chain reaction with fluorescent dyes. Mitochondrial DNA gene expression did not differ between group before surgery. Immediately after the intervention, cytochrome B gene expression was higher in the group with MOF, and it remained high during entire follow-up period. A similar trend was observed in cytochrome oxidase gene expression. Increased NADH levels of gene expressions during the first postoperative day were noted in both groups, the expression showed tendency to increase on the third postoperative day. mtDNA gene expression in the "MOF present" group remained at a higher level compared with the group without complications. A positive correlation was reveled between the severity of MOF according to SOFA score and the level of mtDNA (r = 0.45; p = 0.028) for the end-point "First day". The ROC analysis showed that mtDNA circulating in plasma (AUC = 0.605) can be a predictor of MOF development. The level of mtDNA significantly increases in case of MOF, irrespective of its cause. (2) The expression of mtDNA genes correlates with the level of MOF severity on the SOFA score.

REGULATORY ROLE OF NONCODING RNA IN SEPSIS AND SEPSIS-ASSOCIATED ORGAN DYSFUNCTION: AN UPDATED SYSTEMATIC REVIEW.

ABSTRACT: Background: The exact molecular mechanisms underlying sepsis remain unclear. Accumulating evidence has shown that noncoding RNAs (ncRNAs) are involved in sepsis and sepsis-associated organ dysfunction (SAOD). Methods: We performed this updated systematic review focusing mainly on research conducted in the last 5 years regarding ncRNAs associated with sepsis and SAOD. The following medical subject headings were used in the PubMed database from October 1, 2016, to March 31, 2022: "microRNA," "long noncoding RNA," "circular RNA," "sepsis," and/or "septic shock." Studies investigating the role of ncRNAs in the pathogenesis of sepsis and as biomarkers or therapeutic targets in the disease were included. Data were extracted in terms of the role of ncRNAs in the pathogenesis of sepsis and their applicability for use as biomarkers or therapeutic targets in sepsis. The quality of the studies was assessed using a modified guideline from the Systematic Review Center for Laboratory Animal Experimentation. Results: A total of 537 original studies investigated the potential roles of ncRNAs in sepsis and SAOD. Experimental studies in the last 5 years confirmed that long ncRNAs have important regulatory roles in sepsis and SAOD. However, studies on circular RNAs and sepsis remain limited, and more studies should be conducted to elucidate this relationship. Among the included studies, the Systematic Review Center for Laboratory Animal Experimentation scores ranged from 3 to 7 (an average score of 3.78). Notably, 94 ncRNAs were evaluated as potential biomarkers for sepsis, and selective reporting of the sensitivity, specificity, and receiver operating characteristic curve was common. A total of 117 studies demonstrated the use of ncRNAs as potential therapeutic targets in sepsis and SAOD. At a molecular level, inflammation-related pathways, mitochondrial dysfunction, cell apoptosis, and/or oxidative stress were the most extensively studied. Conclusion: This review suggests that ncRNAs could be good biomarkers and therapeutic candidates for sepsis and SAOD. Prospective, large-scale, and multicenter cohort studies should be performed to evaluate specific ncRNAs as biomarkers and test the organ-specific delivery of these regulatory molecules when used as therapeutic targets.

Expression of MicroRNAs in Sepsis-Related Organ Dysfunction: A Systematic Review.

Sepsis is a critical condition characterized by increased levels of pro-inflammatory cytokines and proliferating cells such as neutrophils and macrophages in response to microbial pathogens. Such processes lead to an abnormal inflammatory response and multi-organ failure. MicroRNAs (miRNA) are single-stranded non-coding RNAs with the function of gene regulation. This means that miRNAs are involved in multiple intracellular pathways and thus contribute to or inhibit inflammation. As a result, their variable expression in different tissues and organs may play a key role in regulating the pathophysiological events of sepsis. Thanks to this property, miRNAs may serve as potential diagnostic and prognostic biomarkers in such life-threatening events. In this narrative review, we collect the results of recent studies on the expression of miRNAs in heart, blood, lung, liver, brain, and kidney during sepsis and the molecular processes in which they are involved. In reviewing the literature, we find at least 122 miRNAs and signaling pathways involved in sepsis-related organ dysfunction. This may help clinicians to detect, prevent, and treat sepsis-related organ failures early, although further studies are needed to deepen the knowledge of their potential contribution.

Potential of circulating lncRNA CASC2 as a biomarker in reflecting the inflammatory cytokines, multi-organ dysfunction, disease severity, and mortality in sepsis patients.

BACKGROUND: Long noncoding RNA (lncRNA) cancer susceptibility candidate gene 2 (CASC2) inhibits inflammation and multi-organ dysfunction in various ways. The present study was intended to explore the potency of blood lncRNA CASC2 as a biomarker for sepsis management. METHODS: Totally, 184 sepsis patients and 30 healthy controls were enrolled. The reverse transcription-quantitative polymerase chain reaction was used to detect lncRNA CASC2 expression in peripheral blood mononuclear cell samples from the subjects. Mortality during 28 days was recorded in sepsis patients. RESULTS: LncRNA CASC2 was decreased in sepsis patients [median (interquartile range [IQR]): 0.473 (0.241-0.773)] by comparison to healthy controls [median (IQR): 1.019 (0.676-1.685)] (p < 0.001). In sepsis patients, lncRNA CASC2 was negatively correlated with Acute Physiology and Chronic Health Evaluation II (APACHE II) (p = 0.001), Sequential Organ Failure Assessment (SOFA) (p < 0.001), SOFA-respiratory system (p = 0.010), SOFA-coagulation (p = 0.020), SOFA-liver (p = 0.019), and SOFA-renal (p = 0.010) scores, but was not related to SOFA-nervous (p = 0.466) and SOFA-cardio vascular system (p = 0.059) scores. Additionally, lncRNA CASC2 was negatively related to tumor necrosis factor-α (p = 0.024), interleukin (IL)-1ß (p = 0.013), and IL-17A (p = 0.002), but was not linked to IL-6 (p = 0.112) or IL-10 (p = 0.074). Furthermore, lncRNA CASC2 was lower in sepsis deaths [median (IQR): 0.286 (0.166-0.475)] than in survivors [median (IQR): 0.534 (0.296-0.811)] (p < 0.001). Simultaneously, Kaplan-Meier (KM) curve analysis also observed that lncRNA CASC2 was inversely related to accumulating mortality in sepsis patients (p = 0.003). While lncRNA CASC2 could independently predict lower mortality risk. CONCLUSION: Circulating lncRNA CASC2 inadequacy indicates the release of inflammatory cytokines, severe multi-organ injuries, and increased mortality in sepsis patients.

Identification of Immune-Related Genes Concurrently Involved in Critical Illnesses Across Different Etiologies: A Data-Driven Analysis.

Severe trauma and sepsis can lead to multiple organ dysfunction syndrome, which is a leading cause of death in intensive care units with mortality rates in excess of 50%. In addition to infection, the degree of immuno-inflammatory response also influences the outcome. The genomic changes observed after a variety of pathophysiological insults, such as trauma, sepsis, burns are similar, and consist of innate immune activation and adaptive immunity suppression. However, the characteristics of the shared mechanisms of aforementioned critical illnesses and the clinical relevance remain less explored. In the present study, we performed a data analysis to identify functional genes concurrently involved in critical illnesses across differing etiologies (trauma and sepsis derived from community-acquired pneumonia/abdominal source) and explored the shared signaling pathways these common genes involved in to gain insight into the underlying molecular mechanisms. A number of immune-related biological functions were found to be dysregulated in both trauma and sepsis in the present study, so we continued to identify immune-related common genes, profiled the immune cell proportion, and explored the relationships between them. The diagnostic and prognostic value of the immune-related common genes was also evaluated to address their potential clinical utilization as novel biomarkers. Notably, we identified a list of 14 immune-related genes concurrently dysregulated in trauma and sepsis showing favorable diagnostic value, among which S100P can predict prognosis of sepsis patients. Moreover, a spectrum of immune cell subsets including naïve B cells, CD8+ T cells, CD4+ memory resting T cells, activated NK cells, resting dendritic cells, plasma cells, Tregs, macrophages M0 and macrophages M1 was found to be concurrently dysregulated in both trauma and sepsis, and a close relation between above identified immune-related genes and immune cell subsets was observed. Our data-driven findings lay a foundation for future research to elucidate the pathophysiology regarding the aspect of inflammatory and immune response in critical illnesses, and suggest future studies focus on interpreting the function roles of the identified immune-related genes, as well as the reactive immune cell subsets.

Blood long non-coding RNA intersectin 1-2 is highly expressed and links with increased Th17 cells, inflammation, multiple organ dysfunction, and mortality risk in sepsis patients.

BACKGROUND: Long non-coding RNA intersectin 1-2 (lnc-ITSN1-2) exacerbates inflammation and promotes T-helper (Th) cell differentiation, also serves as a biomarker in critical illness diseases. However, its clinical role in sepsis remains obscure. Hence, the study aimed to explore the relationship of lnc-ITSN1-2 with Th cells, inflammation, disease severity, multiple organ dysfunction, and mortality risk in sepsis. METHODS: Peripheral blood mononuclear cells (PBMC) were isolated from 95 sepsis patients and 50 health controls, followed by lnc-ITSN1-2 evaluation using RT-qPCR. PBMC Th1, Th17 cells and their secreted cytokines in serum were detected by flow cytometry and ELISA, respectively. RESULTS: Lnc-ITSN1-2 in sepsis patients was higher than it in health controls (Z = -7.328, p < 0.001). Lnc-ITSN1-2 correlated with increased interferon-gamma (p = 0.009), Th17 cells (p = 0.022), and interleukin-17A (p = 0.006), but not Th1 cells (p = 0.169) in sepsis patients. Moreover, lnc-ITSN1-2 had a positive connection with C-reactive protein (p = 0.001), acute pathologic and chronic health evaluation (APACHE) II (p = 0.024), and sequential organ failure assessment (SOFA) scores (p = 0.022). Regarding SOFA subscales, lnc-ITSN1-2 linked with elevated respiratory system score (p = 0.005), cardiovascular system score (p = 0.007), and renal system score (p = 0.004) but no other subscales. Besides, lnc-ITSN1-2 had an increasing trend, but no statistical difference, in septic deaths compared to survivors (Z = -1.852, p = 0.064). CONCLUSION: Lnc-ITSN1-2 reflects sepsis progression and unfavorable prognosis to some extent, which may serve as a potential biomarker to improve the management of sepsis patients.

Evaluating the potency of blood long noncoding RNA PVT1 as candidate biomarker reflecting inflammation, multiple organ dysfunction, and mortality risk in sepsis patients.

OBJECTIVE: Long noncoding RNA plasmacytoma variant translocation 1 (lnc-PVT1) promotes septic inflammation and organ injuries via multiple ways, while its clinical engagement in sepsis management is indistinct. This study aimed to investigate its relationship with inflammation, multiple organ dysfunction, and mortality risk in sepsis patients. METHODS: Sepsis patients and age-/gender-matched healthy controls were enrolled; their lnc-PVT1 expression in plasma were detected by RT-qPCR. For sepsis patients only, the inflammatory cytokine levels (tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-17A) in plasma were detected by ELISA. According to the survival data during 28-day follow-up, sepsis patients were divided into sepsis survivors and sepsis deaths. RESULTS: Lnc-PVT1 expression was increased in sepsis patients (N = 157) compared with healthy controls (N = 80) (p < 0.001). In sepsis patients, lnc-PVT1 was linked with higher acute physiology and chronic health evaluation II (APACHEII) score (p = 0.001), total sequential organ failure assessment (SOFA) score, and its most subitems (SOFA-respiratory system, SOFA-coagulation, SOFA-liver, SOFA-cardiovascular system, and SOFA-renal system scores) (all p < 0.01), but not SOFA-nervous system score (p = 0.091); it did not relate to primary infection sites either (p = 0.204). Furthermore, lnc-PVT1 correlated with increased C-reactive protein, TNF-α, IL-1ß, and IL-17 in sepsis patients (all p < 0.01). Additionally, lnc-PVT1 expression was higher in sepsis deaths than that in sepsis survivors (p < 0.001), following receiver-operating characteristic curve disclosed that lnc-PVT1 predicted 28-day septic mortality risk (area under the curve: 0.789, 95% confidence interval: 0.702-0.875). CONCLUSION: Circulating lnc-PVT1 exhibits the potential as a biomarker in sepsis patients to inform inflammation, multiple organ dysfunction, and mortality risk.

miR-126 ameliorates multiple organ dysfunction in septic rats by regulating the differentiation of Th17/Treg.

BACKGROUND: The most common cause of death in sepsis is MODS. We hope that miR-126 can regulate the differentiation of Th17/Treg, reduce the infiltration of inflammatory factors in peripheral blood and various organs and tissues, and improve organ function and prognosis in sepsis. METHODS AND RESULTS: Septic rat model was established by cecal perforation and ligation. miR-126 mimic and inhibitor were used to intervene sepsis. The experimental results showed that miR-126 mimic reduced the differentiation of Th17 and increased the differentiation of Treg in septic rats, resulting in the TNF-α, IL-6 and IL-17 were decreased in peripheral blood, the infiltration levels of TNF-α, IL-6 and IL-17 were decreased in lung, liver and kidney, the tissue damage degree of lung, liver and kidney were weakened, and the corresponding histopathological score decreased. Finally, the survival rate of septic rats was increased. However, after using miR-126 inhibitor, the levels of inflammatory factors and the degree of multiple organ injury in septic rats increased in varying degrees, and the prognosis of septic rats was worse. CONCLUSION: This study confirmed that miR-126 can regulate the differentiation of Th17/Treg, change the infiltration of inflammatory factors in peripheral blood, lung, liver and kidney of septic rats, alleviate MODS, and improve the organ function and prognosis of septic rats.

Neutrophil-derived long noncoding RNA IL-7R predicts development of multiple organ dysfunction syndrome in patients with trauma.

PURPOSE: Overactive neutrophils are thought to be key drivers in the development of post-traumatic multiple organ dysfunction syndrome (MODS). Little is known about the role of inflammation-related lnc-IL7R in trauma. Thus, we aimed to explore the association between neutrophil-derived lnc-IL7R and post-traumatic MODS. METHODS: Total RNA was extracted from the isolated circulating neutrophils in 60 patients with trauma and 33 healthy volunteers for lnc-IL7R expression determination by real-time PCR. The correlation of lnc-IL7R expression with disease severity and the development of post-traumatic MODS was analyzed. RESULTS: The lnc-IL7R levels were significantly lower in trauma patients, especially in those with severe trauma [Injury Severity Score (ISS) ≥ 16], and correlated negatively with the ISS, Acute Physiology and Chronic Health Evaluation II score, and length of ICU stay. The lnc-IL7R levels were also significantly decreased in patients who developed MODS than in those who did not. Lnc-IL7R was an independent predictor of MODS [odds ratio (OR) 0.654, (0.435-0.982), p = 0.041]. The area under the curve for predicting post-traumatic MODS was 0.799 (sensitivity 76.9%, specificity 71.4%), with a cutoff value of 0.024. CONCLUSIONS: Neutrophil-derived lnc-IL7R is an independent predictor of post-traumatic MODS; therefore, it could be a useful predictive marker for MODS.

Whole-exome Sequencing Identifies SLC52A1 and ZNF106 Variants as Novel Genetic Risk Factors for (Early) Multiple-organ Failure in Acute Pancreatitis.

OBJECTIVE: The aim of this study was to identify genetic variants associated with early multiple organ failure (MOF) in acute pancreatitis. SUMMARY BACKGROUND DATA: MOF is a life-threatening complication of acute pancreatitis, and risk factors are largely unknown, especially in early persistent MOF. Genetic risk factors are thought to enhance severity in complex diseases such as acute pancreatitis. METHODS: A 2-phase study design was conducted. First, we exome sequenced 9 acute pancreatitis patients with early persistent MOF and 9 case-matched patients with mild edematous pancreatitis (phenotypic extremes) from our initial Dutch cohort of 387 patients. Secondly, 48 candidate variants that were overrepresented in MOF patients and 10 additional variants known from literature were genotyped in a replication cohort of 286 Dutch and German patients. RESULTS: Exome sequencing resulted in 161,696 genetic variants, of which the 38,333 non-synonymous variants were selected for downstream analyses. Of these, 153 variants were overrepresented in patients with multiple-organ failure, as compared with patients with mild acute pancreatitis. In total, 58 candidate variants were genotyped in the joined Dutch and German replication cohort. We found the rs12440118 variant of ZNF106 to be overrepresented in patients with MOF (minor allele frequency 20.4% vs 11.6%, Padj=0.026). Additionally, SLC52A1 rs346821 was found to be overrepresented (minor allele frequency 48.0% vs 42.4%, Padj= 0.003) in early MOF. None of the variants known from literature were associated.Conclusions: This study indicates that SLC52A1, a riboflavin plasma membrane transporter, and ZNF106, a zinc finger protein, may be involved in disease progression toward (early) MOF in acute pancreatitis.

Potential of long non-coding RNA KCNQ1OT1 as a biomarker reflecting systemic inflammation, multiple organ dysfunction, and mortality risk in sepsis patients.

BACKGROUND: Long non-coding RNA potassium voltage-gated channel subfamily Q member 1 opposite strand 1 (lnc-KCNQ1OT1) represses inflammation and multiple organ dysfunction, whereas its clinical value in sepsis is unclear. Thus, this study aimed to explore this issue. METHODS: Lnc-KCNQ1OT1 from peripheral blood mononuclear cells were detected by RT-qPCR in 116 sepsis patients and 60 healthy controls (HCs). Moreover, sepsis patients were followed-up until death or up to 28 days. RESULTS: Lnc-KCNQ1OT1 decreased in patients with sepsis than in HCs (p < 0.001). In sepsis patients, lnc-KCNQ1OT1 was negatively correlated with sequential organ failure assessment (SOFA) scores (r = -0.344, p < 0.001) and several SOFA subscale scores (including respiratory system, coagulation, liver, and renal systems) (all r < 0, p < 0.05). Furthermore, lnc-KCNQ1OT1 was negatively correlated with CRP (r = -0.386, p < 0.001), TNF-α (r = -0.332, p < 0.001), IL-1ß (r = -0.319, p < 0.001), and IL-6 (r = -0.255, p = 0.006). Additionally, lnc-KCNQ1OT1 levels were lower in sepsis deaths than in sepsis survivors (p < 0.001), and the receiver operating characteristic curve showed that lnc-KCNQ1OT1 had an acceptable ability to predict 28-day mortality (area under the curve: 0.780, 95% confidence interval: 0.678-0.882). Meanwhile, its ability to predict 28-day mortality risk was higher than that of CRP, TNF-α, IL-1ß, and IL-6, but slightly lower than the SOFA score and acute physiology and chronic health evaluation II score. CONCLUSION: Lnc-KCNQ1OT1 serves as a potential biomarker for monitoring disease severity and prognosis in patients with sepsis.

The Molecular Mechanism of Multiple Organ Dysfunction and Targeted Intervention of COVID-19 Based on Time-Order Transcriptomic Analysis.

Coronavirus disease 2019 (COVID-19) pandemic is caused by the novel coronavirus that has spread rapidly around the world, leading to high mortality because of multiple organ dysfunction; however, its underlying molecular mechanism is unknown. To determine the molecular mechanism of multiple organ dysfunction, a bioinformatics analysis method based on a time-order gene co-expression network (TO-GCN) was performed. First, gene expression profiles were downloaded from the gene expression omnibus database (GSE161200), and a TO-GCN was constructed using the breadth-first search (BFS) algorithm to infer the pattern of changes in the different organs over time. Second, Gene Ontology enrichment analysis was used to analyze the main biological processes related to COVID-19. The initial gene modules for the immune response of different organs were defined as the research object. The STRING database was used to construct a protein-protein interaction network of immune genes in different organs. The PageRank algorithm was used to identify five hub genes in each organ. Finally, the Comparative Toxicogenomics Database played an important role in exploring the potential compounds that target the hub genes. The results showed that there were two types of biological processes: the body's stress response and cell-mediated immune response involving the lung, trachea, and olfactory bulb (olf) after being infected by COVID-19. However, a unique biological process related to the stress response is the regulation of neuronal signals in the brain. The stress response was heterogeneous among different organs. In the lung, the regulation of DNA morphology, angiogenesis, and mitochondrial-related energy metabolism are specific biological processes related to the stress response. In particular, an effect on tracheal stress response was made by the regulation of protein metabolism and rRNA metabolism-related biological processes, as biological processes. In the olf, the distinctive stress responses consist of neural signal transmission and brain behavior. In addition, myeloid leukocyte activation and myeloid leukocyte-mediated immunity in response to COVID-19 can lead to a cytokine storm. Immune genes such as SRC, RHOA, CD40LG, CSF1, TNFRSF1A, FCER1G, ICAM1, LAT, LCN2, PLAU, CXCL10, ICAM1, CD40, IRF7, and B2M were predicted to be the hub genes in the cytokine storm. Furthermore, we inferred that resveratrol, acetaminophen, dexamethasone, estradiol, statins, curcumin, and other compounds are potential target drugs in the treatment of COVID-19.

Gasdermin D inhibition prevents multiple organ dysfunction during sepsis by blocking NET formation.

Multiple organ dysfunction is the most severe outcome of sepsis progression and is highly correlated with a worse prognosis. Excessive neutrophil extracellular traps (NETs) are critical players in the development of organ failure during sepsis. Therefore, interventions targeting NET release would likely effectively prevent NET-based organ injury associated with this disease. Herein, we demonstrate that the pore-forming protein gasdermin D (GSDMD) is active in neutrophils from septic humans and mice and plays a crucial role in NET release. Inhibition of GSDMD with disulfiram or genic deletion abrogated NET formation, reducing multiple organ dysfunction and sepsis lethality. Mechanistically, we demonstrate that during sepsis, activation of the caspase-11/GSDMD pathway controls NET release by neutrophils during sepsis. In summary, our findings uncover a novel therapeutic use for disulfiram and suggest that GSDMD is a therapeutic target to improve sepsis treatment.