Exploring the miRNome of extracellular vesicles as diagnostic and prognostic biomarkers in postoperated patients with septic shock and severe systemic inflammatory response syndrome
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ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST1230 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description: Not available
| S-BSST1319 | biostudies-other
Project description:BackgroundSepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease.Material and methodsFirstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs (differentially expressed mRNAs). Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR (real-time polymerase chain reaction) verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers.ResultsA total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers (such as RAB13, KIF1B, CLEC5A, FCER1A, CACNA2D3, DUSP3, HMGN3, MGST1 and ARHGEF18) for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock.ConclusionIdentified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.
| S-EPMC8772133 | biostudies-literature
Project description:To evaluate the prevalence of myocardial dysfunction and its prognostic value in patients with severe sepsis and septic shock.Adult septic patients admitted to an intensive care unit were prospectively studied using transthoracic echocardiography within the first 48 hours after admission and thereafter on the 7th-10th days. Echocardiographic variables of biventricular function, including the E/e' ratio, were compared between survivors and non-survivors.A total of 99 echocardiograms (53 at admission and 46 between days 7 - 10) were performed on 53 patients with a mean age of 74 (SD 13) years. Systolic and diastolic dysfunction was present in 14 (26%) and 42 (83%) patients, respectively, and both types of dysfunction were present in 12 (23%) patients. The E/e' ratio, an index of diastolic dysfunction, was the best predictor of hospital mortality according to the area under the ROC curve (0.71) and was an independent predictor of outcome, as determined by multivariate analysis (OR = 1.36 [1.05 - 1.76], p = 0.02).In septic patients admitted to an intensive care unit, echocardiographic systolic dysfunction is not associated with increased mortality. In contrast, diastolic dysfunction is an independent predictor of outcome.
| S-EPMC4738818 | biostudies-other
Project description:Rationale: Acute kidney injury (AKI), a common complication of sepsis, is associated with substantial morbidity and mortality and lacks definitive disease-modifying therapy. Early, reliable identification of at-risk patients is important for targeted implementation of renal protective measures. The updated Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) is a validated, multibiomarker prognostic enrichment strategy to estimate baseline mortality risk in pediatric septic shock.Objectives: To assess the association between PERSEVERE-II mortality probability and the development of severe, sepsis-associated AKI on Day 3 (D3 SA-AKI) in pediatric septic shock.Methods: We performed secondary analysis of a prospective observational study of children with septic shock in whom the PERSEVERE biomarkers were measured to assign a PERSEVERE-II baseline mortality risk.Measurements and Main Results: Among 379 patients, 65 (17%) developed severe D3 SA-AKI. The proportion of patients developing severe D3 SA-AKI increased directly with increasing PERSEVERE-II risk category, and increasing PERSEVERE-II mortality probability was independently associated with increased odds of severe D3 SA-AKI after adjustment for age and illness severity (odds ratio, 1.4; 95% confidence interval, 1.2-1.7; P < 0.001). Similar associations were found between increasing PERSEVERE-II mortality probability and the need for renal replacement therapy. Lower PERSEVERE-II mortality probability was independently associated with increased odds of renal recovery among patients with early AKI. A newly derived model incorporating the PERSEVERE biomarkers and Day 1 AKI status predicted severe D3 SA-AKI with an area under the received operating characteristic curve of 0.95 (95% confidence interval, 0.92-0.98).Conclusions: Among children with septic shock, the PERSEVERE biomarkers predict severe D3 SA-AKI and identify patients with early AKI who are likely to recover.
| S-EPMC7124707 | biostudies-literature
Project description:IntroductionSeptic-shock-associated acute kidney injury (SSAKI) carries high morbidity in the pediatric population. Effective treatment strategies are lacking, in part due to poor detection and prediction. There is a need to identify novel candidate biomarkers of SSAKI. The objective of our study was to determine whether microarray data from children with septic shock could be used to derive a panel of candidate biomarkers for predicting SSAKI.MethodsA retrospective cohort study compared microarray data representing the first 24 hours of admission for 179 children with septic shock with those of 53 age-matched normal controls. SSAKI was defined as a >200% increase of baseline serum creatinine, persistent to 7 days after admission.ResultsPatients with SSAKI (n = 31) and patients without SSAKI (n = 148) were clinically similar, but SSAKI carried a higher mortality (45% vs. 10%). Twenty-one unique gene probes were upregulated in SSAKI patients versus patients without SSAKI. Using leave-one-out cross-validation and class prediction modeling, these probes predicted SSAKI with a sensitivity of 98% (95% confidence interval (CI) = 81 to 100) and a specificity of 80% (95% CI = 72 to 86). Serum protein levels of two specific genes showed high sensitivity for predicting SSAKI: matrix metalloproteinase-8 (89%, 95% CI = 64 to 98) and elastase-2 (83%, 95% CI = 58 to 96). Both biomarkers carried a negative predictive value of 95%. When applied to a validation cohort, although both biomarkers carried low specificity (matrix metalloproteinase-8: 41%, 95% CI = 28 to 50; and elastase-2: 49%, 95% CI = 36 to 62), they carried high sensitivity (100%, 95% CI = 68 to 100 for both).ConclusionsGene probes upregulated in critically ill pediatric patients with septic shock may allow for the identification of novel candidate serum biomarkers for SSAKI prediction.
| S-EPMC3388679 | biostudies-literature
Project description:Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients. Background: We measured gene expression levels and profiles of children with systemic inflammatory response syndrome (SIRS) and septic shock as a means for discovering patient sub-groups and gene signatures that are active in disease-affected individuals and potentially in patients with poor outcomes. Methods: Microarray and bioinformatics analyses of 123 microarray chips representing whole blood derived RNA from controls, children with SIRS, and children with septic shock. Results: A discovery-based filtering approach was undertaken to identify genes whose expression levels were altered in patients with SIRS or septic shock. Clustering of these genes identified 3 Major and several minor sub-groups of patients with SIRS or septic shock. The three groups differed with respect to incidence of septic shock and trended toward differences in mortality. Statistical analyses demonstrated that 6,435 gene probes were differentially regulated between the three patient sub-groups (false discovery rate < 0.001%). Of these gene probes, 623 gene probes within 7 major gene ontologies accounted for the majority of group differentiation. Network analyses of these 623 gene probes demonstrated 5 major gene networks that were differentially expressed between the 3 groups. Statistical comparison of septic shock survivors and non-survivors identified one major gene network that was under expressed in a high fraction of the non-survivors and identified potential biomarkers for poor outcome. Conclusions: This is the first genome-level demonstration of pediatric patient sub-groups with SIRS and septic shock. The sub-groups differ clinically and differentially express 5 major gene networks. We have identified gene signatures and potential biomarkers associated with poor outcome in children with septic shock. These data represent a major advancement in our genome-level understanding of pediatric SIRS and septic shock. Keywords: Septic shock, SIRS, pediatrics, outcome, infection, inflammation
2006-04-30 | GSE4607 | GEO
Project description:Sepsis is a life-threatening organ dysfunction caused by a dysregulated host-response to infections. Osteopontin (OPN) is an extracellular matrix protein involved in the inflammatory response. Our aim was to evaluate the diagnostic and prognostic performance in sepsis of a single OPN determination in the Emergency Department (ED). We conducted a single-centre prospective observational study in an Italian ED where we enrolled 102 consecutive patients presenting with suspected infection and qSOFA ≥ 2. OPN plasma concentration was found to be an independent predictor of sepsis (OR = 1.020, 95% CI 1.002⁻1.039, P = 0.031) and the diagnostic receiver operating characteristic (ROC) curve resulted in an area under the curve (AUC) of 0.878. OPN levels were positively correlated to plasma creatinine (r = 0.401 with p = 0.0001), but this relation was not explained by the development of acute kidney injury (AKI), since no difference was found in OPN concentration between AKI and non-AKI patients. The analysis of 30-days mortality showed no significant difference in OPN levels between alive and dead patients (p = 0.482). In conclusion, a single determination of OPN concentration helped to identify patients with sepsis in the ED, but it was not able to predict poor prognosis in our cohort of patients.
| S-EPMC6407102 | biostudies-literature
Project description: Not available
| S-EPMC8409473 | biostudies-literature
Project description:Sepsis is a major health concern, with high morbidity and mortality workdwide. In order to identify prognostic biomarkers in septic shock patients, we performed a microarray study exploring the early modulation of gene expression according to day 28 mortality. Several candidate biomarkers including CX3CR1 and LILRB2 were identified as prognostic biomarkers.
2017-11-27 | GSE95233 | GEO
Project description:The aim of this study was to evaluate the diagnostic and prognostic value of presepsin in patients with severe sepsis and septic shock during the first week of ICU treatment.In total, 116 patients with suspected severe sepsis or septic shock were included during the first 24 hours of ICU treatment. Blood samples for biomarker measurements of presepsin, procalcitonin (PCT), interleukin 6 (IL-6), C reactive protein (CRP) and white blood cells (WBC) were drawn at days 1, 3 and 8. All patients were followed up for six months. Biomarkers were tested for diagnosis of sepsis, severe sepsis, septic shock and for prognosis of 30-days and 6-months all-cause mortality at days 1, 3 and 8. Diagnostic and prognostic utilities were tested by determining diagnostic cutoff levels, goodness criteria, C-statistics and multivariable Cox regression models.Presepsin increased significantly from the lowest to most severe sepsis groups at days 1, 3 and 8 (test for linear trend P <0.03). Presepsin levels revealed valuable diagnostic capacity to diagnose severe sepsis and septic shock at days 1, 3 and 8 (range of diagnostic area under the curves (AUC) 0.72 to 0.84, P?=?0.0001) compared to IL-6, PCT, CRP and WBC. Goodness criteria for diagnosis of sepsis severity were analyzed (?sepsis, cutoff?=?530 pg/ml; ?severe sepsis, cutoff?=?600 pg/ml; ?septic shock, cutoff?=?700 pg/ml; P <0.03). Presepsin levels revealed significant prognostic value for 30 days and 6 months all-cause mortality (presepsin: range of AUC 0.64 to 0.71, P <0.02). Patients with presepsin levels of the 4th quartile were 5 to 7 times more likely to die after six months than patients with lower levels. The prognostic value for all-cause mortality of presepsin was comparable to that of IL-6 and better than that of PCT, CRP or WBC.In patients with suspected severe sepsis and septic shock, presepsin reveals valuable diagnostic capacity to differentiate sepsis severity compared to PCT, IL-6, CRP, WBC. Additionally, presepsin and IL-6 reveal prognostic value with respect to 30 days and 6 months all-cause mortality throughout the first week of ICU treatment.ClinicalTrials.gov http://NCT01535534. Registered 14 February 2012.
| S-EPMC4174283 | biostudies-literature