A Transcriptomic Biomarker to Quantify Systemic Inflammation in Sepsis - A Prospective Multicenter Phase II Diagnostic Study.
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SUBMITTER: Bauer M
PROVIDER: S-EPMC4856796 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionVanin-1 plays a pivotal role in oxidative stress and the inflammatory response. However, its relationship with traumatic sepsis remains unknown. The aim of our study was to evaluate whether plasma vanin-1 could be used for the early prediction of traumatic sepsis.MethodsIn this three-stage prospective cohort study, severe trauma patients admitted from January 2015 to October 2018 at two hospitals were enrolled. Plasma vanin-1 levels were measured by enzyme-linked immunosorbent assay (ELISA). The associations among variables and traumatic sepsis were identified by logistic regression models and the receiver operating characteristic (ROC) curve was analyzed to evaluate the diagnostic efficiency.ResultsA total of 426 trauma patients (22 in the discovery cohort, 283 in the internal test cohort, and 121 in the external validation cohort) and 16 healthy volunteers were recruited. The plasma vanin-1 of trauma patients was significantly higher than that of healthy volunteers (P < 0.05). Patients with sepsis had higher plasma vanin-1 than patients without sepsis in the discovery trauma cohort (P < 0.05). In the internal test cohort, plasma vanin-1 at day 1 after trauma was significantly associated with the incidence of sepsis (OR = 3.92, 95% CI 2.68-5.72, P = 1.62 × 10-12). As a predictive biomarker, vanin-1 afforded a better area under the curve (AUC) (0.82, 95% CI 0.77-0.87) than C-reaction protein (CRP) (0.62, 95% CI 0.56-0.68, P < 0.0001), procalcitonin (PCT) (0.66, 95% CI 0.60-0.71, P < 0.0001), and Acute Physiology and Chronic Health Evaluation II (APACHE II) (0.71, 95% CI 0.65-0.76, P = 6.70 × 10-3). The relevance was further validated in the external validation cohort (OR = 4.26, 95% CI 2.22-8.17, P = 1.28 × 10-5), with an AUC of 0.83 (95% CI 0.75-0.89). Vanin-1 could also improve the diagnostic efficiency of APACHE II (AUC = 0.85).ConclusionsOur study demonstrated that plasma vanin-1 increased among trauma patients and was independently associated with the risk of sepsis. Vanin-1 might be a potential biomarker for the early prediction of traumatic sepsis.Trial registrationClinicaltrials.gov Identifier, NCT01713205.
| S-EPMC8116364 | biostudies-literature
Project description:BackgroundFew sepsis biomarkers accurately predict severity and mortality. Previously, we had reported that first-day histidine-rich glycoprotein (HRG) levels were significantly lower in patients with sepsis and were associated with mortality. Since the time trends of HRG are unknown, this study focused on the time course of HRG in patients with sepsis and evaluated the differences between survivors and non-survivors.MethodsA multicenter prospective observational study was conducted involving 200 patients with sepsis in 16 Japanese hospitals. Blood samples were collected on days 1, 3, 5, and 7, and 28-day mortality was used for survival analysis. Plasma HRG levels were determined using a modified quantitative sandwich enzyme-linked immunosorbent assay.ResultsFirst-day HRG levels in non-survivors were significantly lower than those in survivors (mean, 15.7 [95% confidence interval (CI), 13.4-18.1] vs 20.7 [19.5-21.9] μg/mL; P = 0.006). Although there was no time × survivors/non-survivors interaction in the time courses of HRG (P = 0.34), the main effect of generalized linear mixed models was significant (P < 0.001). In a univariate Cox proportional hazards model with each variable as a time-dependent covariate, higher HRG levels were significantly associated with a lower risk of mortality (hazard ratio, 0.85 [95% CI, 0.78-0.92]; P < 0.001). Furthermore, presepsin levels (P = 0.02) and Sequential Organ Function Assessment scores (P < 0.001) were significantly associated with mortality. Harrell's C-index values for the 28-day mortality effect of HRG, presepsin, procalcitonin, and C-reactive protein were 0.72, 0.70, 0.63, and 0.59, respectively.ConclusionsHRG levels in non-survivors were consistently lower than those in survivors during the first seven days of sepsis. Repeatedly measured HRG levels were significantly associated with mortality. Furthermore, the predictive power of HRG for mortality may be superior to that of other singular biomarkers, including presepsin, procalcitonin, and C-reactive protein.
| S-EPMC10057827 | biostudies-literature
Project description:The Pediatric Sepsis Biomarker Risk Model (PERSEVERE), a pediatric sepsis risk model, uses biomarkers to estimate baseline mortality risk for pediatric septic shock. It is unknown how PERSEVERE performs within distinct septic shock phenotypes. We tested PERSEVERE in children with septic shock and thrombocytopenia-associated multiple organ failure (TAMOF), and in those without new onset thrombocytopenia but with multiple organ failure (MOF).PERSEVERE-based mortality risk was generated for each study subject (n = 660). A priori, we determined that if PERSEVERE did not perform well in both the TAMOF and the MOF cohorts, we would revise PERSEVERE to incorporate admission platelet counts.Multiple PICUs in the United States.Standard care.PERSEVERE performed well in the TAMOF cohort (areas under the receiver operating characteristic curves [AUC], 0.84 [95% CI, 0.77-0.90]), but less well in the MOF cohort (AUC, 0.71 [0.61-0.80]). PERSEVERE was revised using 424 subjects previously reported in the derivation phase. PERSEVERE-II had an AUC of 0.89 (0.85-0.93) and performed equally well across TAMOF and MOF cohorts. PERSEVERE-II performed well when tested in 236 newly enrolled subjects. Sample size calculations for a clinical trial testing the efficacy of plasma exchange for children with septic shock and TAMOF indicated PERSEVERE-II-based stratification could substantially reduce the number of patients necessary, when compared with no stratification.Testing PERSEVERE in the context of septic shock phenotypes prompted a revision incorporating platelet count. PERSEVERE-II performs well upon testing, independent of TAMOF or MOF status. PERSEVERE-II could potentially serve as a prognostic enrichment tool.
| S-EPMC5201138 | biostudies-literature
Project description:PurposeThere are no satisfactory diagnostic biomarkers for sepsis. Accordingly, this study screened biomarkers valuable for sepsis diagnosis and prognosis using data-independent acquisition (DIA) combined with clinical data analysis.Patients and methodsSerine protease inhibitor Kazal-type 1 (SPINK1) is a differentially expressed protein that was screened using DIA and bioinformatics in sepsis patients (n = 22) and healthy controls (n = 10). The plasma SPINK1 levels were detected using an enzyme-linked immunosorbent assay (ELISA) in an expanded population (sepsis patients, n = 52; healthy controls, n = 10). The diagnostic value of SPINK1 in sepsis was evaluated using receiver operating characteristic (ROC) curve analysis based on clinical data. The prognostic value of SPINK1 for sepsis was evaluated using correlation and survival analyses.ResultsDIA quality control identified 78 differential proteins (72 upregulated and six downregulated), among which SPINK1 was highly expressed in sepsis. The ELISA results suggested that SPINK1 expression was significantly elevated in the sepsis group (P < 0.05). ROC analysis of SPINK1 yielded an area under the curve (AUC) of 0.9096. Combining SPINK1 with procalcitonin (PCT) for ROC analysis yielded an AUC of 1. SPINK1 expression was positively correlated with the Sequential Organ Failure Assessment (SOFA) score (r = 3497, P = 0.0053) and APACHE II score (r = 3223, P = 0.0106). High plasma SPINK1 protein expression was negatively correlated with the 28-day survival rate of patients with sepsis (P = 0.0149).ConclusionThe plasma of sepsis patients contained increased SPINK1 protein expression. Combining SPINK1 with PCT might have a high diagnostic value for sepsis. SPINK1 was associated with the SOFA score, APACHE II score, and the 28-day survival rate in patients with sepsis.
| S-EPMC10929552 | biostudies-literature
Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20). This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. The GEO data represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).
2011-11-01 | E-GEOD-28750 | biostudies-arrayexpress
Project description:The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), a long noncoding RNA, for predicting the risk of PCa before biopsy. The MALAT-1 score was tested in a discovery phase and a multi-center validation phase. The predictive power of the MALAT-1 score was evaluated by the area under receiver operating characteristic (ROC) curve (AUC) and by decision curve analysis. As an independent predictor of PCa, the MALAT-1 score was significantly higher in men with a positive biopsy than in those with a negative biopsy. The ROC analysis showed a higher AUC for the MALAT-1 score (0.670 and 0.742) vs. the total PSA (0.545 and 0.601) and percent free PSA (0.622 and 0.627) in patients with PSA values of 4.0-10 ng/ml. According to the decision curve analysis, using a probability threshold of 25%, the MALAT-1 model would prevent 30.2%-46.5% of unnecessary biopsies in PSA 4-10 ng/ml cohorts, without missing any high-grade cancers. Our results demonstrate that urine MALAT-1 is a promising biomarker for predicting prostate cancer risk.
| S-EPMC4294360 | biostudies-literature
Project description:Background: Accumulating evidence suggests that differentially expressed non-coding circular RNAs (circRNAs) play critical roles in the progress of autoimmune diseases. However, the role of circRNAs in systemic lupus erythematosus (SLE) remains unclear. Methods: We initially used next-generation sequencing (NGS) to comprehensively analyze circRNA expression profiles in peripheral blood mononuclear cells (PBMCs) from 10 SLE patients, stratified by their disease activity characteristics (stable or active SLE), and 10 healthy controls (HCs). Candidate circRNAs identified were first validated by quantitative reverse-transcription (qRT)-PCR in PBMC samples from a training-phase cohort of five SLE patients and five HCs. The significantly dysregulated circRNAs were then confirmed by qRT-PCR in a validation cohort of 23 SLE patients and 21 HCs, and in an external validation cohort with 64 SLE patients, 58 HCs, and 50 patients with rheumatoid arthritis (RA). In addition, we conducted bioinformatics analysis and western blotting investigating the relationships between the candidate circRNAs and SLE progression. Results: Multilayer integrative analysis of circRNA regulation showed that 84 circRNAs were upregulated and 30 were downregulated in patients with SLE compared with HCs. We then analyzed the intersection of these differentially expressed circRNAs in an SLE-stable cohort, an SLE-active cohort, and HCs. This enabled us to narrow down dysregulated circRNAs to 15 upregulated circRNAs. Only hsa_circ_0000479 was significantly upregulated in PBMCs of patients with SLE compared with HCs (P < 0.05). Furthermore, the diagnostic potential of hsa_circ_0000479 expression to distinguish SLE patients from HCs and RA patients was also significantly increased in the validation-phase and external-validation-phase cohorts (P < 0.05). When distinguishing SLE patients from HCs, the diagnostic specificities of hsa_circ_0000479 were 0.619 and 1.0 in two validation cohorts, respectively (AUCs = 0.731 and 0.730, respectively). It was also significantly increased in either stable SLE patients or active SLE patients compared with HCs in these two cohorts (P < 0.05). We also used bioinformatics analysis to show that hsa_circ_0000479 regulates SLE progression by modulating metabolic pathways and the Wnt signaling pathway. Western blotting revealed that the expression of Wnt-16 protein was significantly decreased in SLE. Conclusion: Our results suggest that hsa_circ_0000479 has potential as a novel biomarker for the diagnosis of SLE.
| S-EPMC6771011 | biostudies-literature
Project description:Sepsis is an uncontrolled, systemic response to infection with life-threatening consequences. Our understanding of the pathogenesis of sepsis across organs of the body is rudimentary. Here, using mouse models of sepsis, we generate a dynamic, organism-wide map of the pathogenesis of the disease, revealing the spatiotemporal patterns of well-known and previously unrecognized effects of sepsis on the body. By combining functional perturbations with organism-wide profiling, we discover two interorgan mechanisms that are key to the pathophysiology of sepsis. First, we find that a hierarchical cytokine circuit arising from the pairwise effects of TNF plus IL-18, IFN-γ, or IL-1β suffices to explain a large fraction of the molecular effects of sepsis on the body. Moreover, the effects of these three cytokine pairs on the abundance of nearly two hundred cell types across nine organ types recapitulate half of all the cellular effects of sepsis. Second, we uncover an interorgan pathway whereby a gut-derived, secreted phospholipase, Pla2g5, mediates hemolysis in the blood circulation and contributes to multi-organ failure during sepsis. Thus, a simplifying principle in the systemic behavior of the cytokine network and a lipase misdirected from gut to blood provide fundamental insights to help build a unifying mechanistic framework for the pathophysiological effects of sepsis on the organ systems of the body.
2024-01-11 | GSE253061 | GEO
Project description:BackgroundLong 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.MethodsLnc-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.ResultsLnc-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-1β (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-1β, and IL-6, but slightly lower than the SOFA score and acute physiology and chronic health evaluation II score.ConclusionLnc-KCNQ1OT1 serves as a potential biomarker for monitoring disease severity and prognosis in patients with sepsis.
| S-EPMC8649371 | biostudies-literature
Project description:Sepsis is an infection-induced systemic inflammatory response syndrome. Upstream recognition molecules, like CD14, play key roles in the pathogenesis. The aim of the present study was to investigate the effect of systemic CD14 inhibition on local inflammatory responses in organs from septic pigs. Pigs (n = 34) receiving Escherichia coli-bacteria or E. coli-lipopolysaccharide (LPS) were treated with an anti-CD14 monoclonal antibody or an isotype-matched control. Lungs, liver, spleen, and kidneys were examined for bacteria and inflammatory biomarkers. E. coli and LPS were found in large amounts in the lungs compared to the liver, spleen, and kidneys. Notably, the bacterial load did not predict the respective organ inflammatory response. There was a marked variation in biomarker induction in the organs and in the effect of anti-CD14. Generally, the spleen produced the most cytokines per weight unit, whereas the liver contributed the most to the total load. All cytokines were significantly inhibited in the spleen. Interleukin-6 (IL-6) was significantly inhibited in all organs, IL-1? and IP-10 were significantly inhibited in liver, spleen, and kidneys, and tumor necrosis factor, IL-8, and PAI-1 were inhibited only in the spleen. ICAM-1 and VCAM-1 was significantly inhibited in the kidneys. Systemic CD14-inhibition efficiently, though organ dependent, attenuated local inflammatory responses. Detailed knowledge on how the different organs respond to systemic inflammation in vivo, beyond the information gained by blood examination, is important for our understanding of the nature of systemic inflammation and is required for future mediator-directed therapy in sepsis. Inhibition of CD14 seems to be a good candidate for such treatment.
| S-EPMC3754210 | biostudies-literature