A Transcriptomic Biomarker to Quantify Systemic Inflammation in Sepsis - A Prospective Multicenter Phase II Diagnostic Study.
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ABSTRACT:
SUBMITTER: Bauer M
PROVIDER: S-EPMC4856796 | biostudies-literature | 2016 Apr
REPOSITORIES: biostudies-literature
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A Transcriptomic Biomarker to Quantify Systemic Inflammation in Sepsis - A Prospective Multicenter Phase II Diagnostic Study.
Bauer Michael M Giamarellos-Bourboulis Evangelos J EJ Kortgen Andreas A Möller Eva E Felsmann Karen K Cavaillon Jean Marc JM Guntinas-Lichius Orlando O Rutschmann Olivier O Ruryk Andriy A Kohl Matthias M Wlotzka Britta B Rußwurm Stefan S Marshall John C JC Reinhart Konrad K
EBioMedicine 20160308
Development of a dysregulated immune response discriminates sepsis from uncomplicated infection. Currently used biomarkers fail to describe simultaneously occurring pro- and anti-inflammatory responses potentially amenable to therapy. Marker candidates were screened by microarray and, after transfer to a platform allowing point-of-care testing, validated in a confirmation set of 246 medical and surgical patients. We identified up-regulated pathways reflecting innate effector mechanisms, while do ...[more]
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Project description:Understanding the plasma proteome dynamics in sepsis patients is crucial for improving prognostic and therapeutic strategies, as sepsis remains a leading cause of mortality in intensive care units. In this study, 363 patients with newly diagnosed sepsis were enrolled and plasma was collected on the first and fourth day after diagnosis. Proteome analysis was performed using liquid chromatography–tandem mass spectrometry. The plasma proteome was analyzed via classical statistical analysis and machine learning to identify associations with 30-day survival. Out of 363 sepsis patients, 224 survived and 139 did not survive the 30-day period. Significant differences in the abundance of 87 proteins on day 1 and 95 proteins on day 4 were found between survivors and non-survivors. Additionally, between days 1 and 4, 63 proteins were differentially regulated between both groups. We found that protein regulations within the first days of sepsis were generally associated with a worse outcome. Statistical analysis revealed the underlying proteins to be foremost related to blood coagulation, immune response and complement activation. Complementarily, the machine learning classifier achieved an area under the receiver operating characteristic curve of 0.75 for predicting 30-day survival. The feature importance analysis highlighted additional proteins and substantiated the findings of univariate statistics. This study describes the temporal alterations of the plasma proteome and the underlying protein networks that are associated with survival. These findings enhance the understanding of sepsis pathophysiology and the identified proteins might serve as starting points for further investigations and guide the development of targeted therapeutic strategies.
2024-12-16 | PXD055932 | Pride
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:IntroductionThe recent discovery of TAK981(Subasumstat), the first-in-class selective inhibitor of SUMOylation, enables new immune treatments. TAK981 is already in clinical trials to potentiate immunotherapy in metastatic tumors and hematologic malignancies. Cancer patients have more than ten times higher risk of infections, but the effects of TAK981 in sepsis are unknown and previous studies on SUMO in infections are conflicting.MethodsWe used TAK981 in two sepsis models; polymicrobial peritonitis (CLP) and LPS endotoxemia. Splenectomy was done in both models to study the role of spleen. Western blotting of SUMO-conjugated proteins in spleen lysates was done. Global SUMO1 and SUMO3 knockout mice were used to study the specific SUMO regulation of inflammation in LPS endotoxemia. Splenocytes adoptive transfer was done from SUMO knockouts to wild type mice to study the role of spleen SUMOylation in experimental sepsis.Results and discussionHere, we report that inhibition of SUMOylation with TAK981 improved survival in mild polymicrobial peritonitis by enhancing innate immune responses and peritoneal bacterial clearance. Thus, we focused on the effects of TAK981 on the immune responses to bacterial endotoxin, showing that TAK981 enhanced early TNFα production but did not affect the resolution of inflammation. Splenectomy decreased serum TNFα levels by nearly 60% and TAK981-induced TNFα responses. In the spleen, endotoxemia induced a distinct temporal and substrate specificity for SUMO1 and SUMO2/3, and both were inhibited by TAK981. Global genetic depletion of SUMO1, but not SUMO3, enhanced TNFα production and metabolic acidosis. The transfer of SUMO1-null, but not wild-type, splenocytes into splenectomized wild-type mice exacerbated TNFα production and metabolic acidosis in endotoxemia.ConclusionThese results suggest that specific regulation of splenic SUMO1 can modulate immune and metabolic responses to bacterial infection.
| S-EPMC10374847 | biostudies-literature
Project description:BackgroundSystemic inflammation and insulin resistance (IR) are often associated with poor prognosis in cancer. This study aimed to investigate the prognostic value of surrogate systemic inflammation and IR indices in patients with cancer.MethodsThis multicenter prospective study included 5,221 patients with cancer, with a mean age of 59.41±11.15 years, of whom 3,061 (58.6%) were male. The surrogate IR indices included low-density lipoprotein cholesterol to high-density lipoprotein cholesterol (LHR) ratio, total cholesterol to high-density lipoprotein cholesterol (TC/ HDL-c) ratio, triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio, and fasting triglyceride glucose (TyG). Prognostic receiver operator characteristic (ROC) curves and C-indices were used to select a better surrogate IR index in patients with cancer. The prognostic value of the indicators was evaluated using univariate and multivariate survival analyses.ResultsIn this study, the median survival time of patients was 44.5 (40.5-51.4) months, and the overall mortality in the 12-month period was 1,115 (53.7%), with 196 mortality events per 1,000 patient-years of patients' follow-up. The prognostic ROC curve and C-index suggested that the prognostic value of LHR was better than that of the other IR indices. The multivariate-adjusted hazard ratios (HRs) for overall survival (OS) were higher in patients with high C-reactive protein (CRP) (HR, 1.51; 95% confidence interval [CI]: 1.38-1.65) and high LHR (HR, 1.20; 95% CI: 1.06-1.37), respectively. The mortality rate of patients with both high CRP and LHR was 1.75-fold higher than that of patients with both low CRP and LHR.ConclusionBoth CRP and LHR showed good survival predictions in patients with cancer. CRP combined with LHR can improve the predictive power of patients with cancer.
| S-EPMC9233357 | 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.
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Project description:ObjectiveThe 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).DesignPERSEVERE-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.SettingMultiple PICUs in the United States.InterventionsStandard care.Measurements and main resultsPERSEVERE 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.ConclusionsTesting 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.
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Project description:ObjectiveSystemic inflammation and malnutrition are correlated with cancer sarcopenia and have deleterious effects on oncological outcomes. However, the combined effect of inflammation and malnutrition in patients with cancer sarcopenia remains unclear.MethodsWe prospectively collected information on 1,204 patients diagnosed with cancer sarcopenia. the mean (SD) age was 64.5 (11.4%) years, and 705 (58.60%) of the patients were male. The patients were categorized into the high advanced lung cancer inflammation index (ALI) group (≥18.39) and the low ALI group (<18.39) according to the optimal survival cut-off curve. We selected the optimal inflammation marker using the C-index, decision curve analysis (DCA), and a prognostic receiver operating characteristic curve. Univariate and multivariate survival analyses were performed to determine the prognostic value of the optimal inflammation indicator. We also analyzed the association between inflammation and malnutrition in patients with cancer.ResultsThe C-index, DCA, and prognostic area under the curve of ALI in patients with cancer sarcopenia were higher or better than those of neutrophil-lymphocyte ratio (NLR), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), and platelet-lymphocyte ratio (PLR). The prognosis for patients in the low ALI group was worse than that of patients in the high ALI group [HR (95%CI) = 1.584 (1.280-1.959), P < 0.001]. When the ALI was divided into quartiles, we observed that decreased ALI scores strongly correlated with decreased overall survival (OS). Patients with both a low ALI and severe malnutrition (vs. patients with high ALI and well-nourished) had a 2.262-fold death risk (P < 0.001). Subgroup analysis showed a significant interactive association between the ALI and death risk in terms of TNM stage (P for interaction = 0.030).ConclusionsThe inflammation indicator of the ALI was better than those of the NLR, PNI, SII, and PLR in patients with cancer sarcopenia. Inflammation combined with severe malnutrition has a nearly 3-fold death risk in patients with cancer sarcopenia, suggesting that reducing systemic inflammation, strengthening nutritional intervention, and improving skeletal muscle mass are necessary.
| S-EPMC8859438 | 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:BackgroundNeonatal sepsis is a leading cause of morbidity and mortality in low-and middle-income countries (LMICs). There are several sophisticated biomarkers; however, they are still insufficient in precision. In this perspective, our study aims to search for a pragmatic diagnostic biomarker in the age category.MethodsA cross-sectional study was conducted over six months(April-September 2018). All neonates with a diagnosis of probable sepsis were included. Logistic regression analysis of demographic variables was done to elucidate any association with confirmed sepsis cases. The median with interquartile range (IQR)] and mean with standard deviation (SD) were calculated, and then compared. The area under the receiver operating characteristic curve (AUROC) of the commonly opted biomarker tests [distribution width of red blood cells (RDW) and platelets(PDW), mean platelet volume(MPV), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR)] was compared to the culture-confirmed case.ResultsOf the 171 suspected sepsis subjects, we discovered a significant burden of newborn sepsis, with 18.7% of cases being culture-confirmed. 66 Early-onset sepsis(EOS) and 105 Late-onset sepsis(LOS) probable sepsis cases were enrolled. A higher incidence was revealed among male infants 24(14%) compared to females 8(4.7%). On logistic regression analysis, preterm birth [odds ratio (OR): 10.9, 95% confidence interval (CI): 4.5-26.9] and low birth weight (OR: 6.5, 95% CI: 2.4-17.9) were significantly associated. Coagulase-negative Staphylococcus aureus (CoNS) (n =6) among gram-positive, and Pseudomonas aeruginosa (n =6) was among gram-negative, were the leading etiologies. Escherichia coli (n =3) was the predominant bacteria in EOS subjects, while Pseudomonas aeruginosa (n =6) among LOS. Median interquartile range(IQR): platelet count 144.5(99-192), red cell distribution width 18(16.9-20), CRP 6(3-18.3); and mean ± SD: MPV (11.7 ± 1.7); PDW (15.2 ± 3.5) were attained, among confirmed cases. The AUROC, of biomarker tests was attained in the order: PDW(0.86) > MPV(0.81) > RDW(0.76) > CRP(0.67) > ESR(0.59); similarly, the cut-off order was >11.2, >10.4, >16.8, >2.9, >4.5, respectively.ConclusionsOur finding shows an increment in the width and volume of RBCand platelet: RDW, MPV, and PDW have a diagnostic role in neonatal sepsis.
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