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ABSTRACT:
PROVIDER: PRJEB53323 | ENA |
REPOSITORIES: ENA
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Project description:Here we developed a new approach to sepsis diagnosis that integrates host transcriptional profiling with metagenomic broad-range pathogen detection from cell-free plasma RNA and DNA.
2022-08-03 | GSE189400 | GEO
Project description:Here we developed a new approach to sepsis diagnosis that integrates host transcriptional profiling with metagenomic broad-range pathogen detection from cell-free plasma RNA and DNA.
2022-08-03 | GSE189401 | GEO
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans. Transcriptomic analysis of lungs from Cynomolgus macaques challenged with E. coli
2015-07-03 | E-GEOD-59075 | biostudies-arrayexpress
Project description:Around 42,000 children suffer from severe sepsis each year in the US alone, resulting in significant morbidity, mortality and billion dollar expenditures in the US healthcare system. Sepsis recognition is a clinical challenge in children. Biomarkers are needed to tailor appropriate antimicrobial therapies and improve risk stratification. The goal of this study was to determine if gene expression profiles from peripheral blood were associated with pathogen type and sepsis severity in children treated for suspected sepsis.
2020-01-01 | GSE119217 | GEO
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans.
2015-07-03 | GSE59075 | GEO
Project description:Background: Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. Results: The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (infection with SIRS), including 78 sepsis survivors and 28 sepsis nonsurvivors, who had previously undergone plasma proteomic and metabolomic profiling. The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflective of immune activation in sepsis. The expression of 1,238 genes differed with sepsis outcome: Nonsurvivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease â rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors, and these were associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. Conclusions: Host response in sepsis survivors â activation of immune response-related genes â was muted in sepsis nonsurvivors. The association of sepsis survival with robust immune response and presence of missense variants in VPS9D1 warrants replication and further functional studies. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS, n=23) or sepsis (infection with SIRS), including 78 sepsis survivors and 28 sepsis nonsurvivors, who had previously undergone plasma proteomic and metabolomic profiling.
2015-01-01 | E-GEOD-63042 | biostudies-arrayexpress
Project description:1364 plasma proteome samples taken at time-of-admission to the emergency department from patients suspected of sepsis.
Used initially with the following abstract:
Sepsis is one of the leading causes of mortality in the world. Currently, the heterogeneity of sepsis makes it challenging to determine the molecular mechanisms that define the syndrome. Here, we leverage population scale proteomics to analyze a well-defined cohort of 1364 blood samples taken at time-of-admission to the emergency department from patients suspected of sepsis. We identified panels of proteins using explainable artificial intelligence that predict clinical outcomes and applied these panels to reduce high-dimensional proteomics data to a low-dimensional interpretable latent space (ILS). Using the ILS, we constructed an adaptive digital twin model that accurately predicted organ dysfunction, mortality, and early-mortality-risk patients using only data available at time-of-admission. In addition to being highly effective for investigating sepsis, this approach supports the flexible incorporation of new data and can generalize to other diseases to aid in translational research and the development of precision medicine.
2024-04-08 | MSV000094486 | MassIVE
Project description:Background: Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. Results: The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (infection with SIRS), including 78 sepsis survivors and 28 sepsis nonsurvivors, who had previously undergone plasma proteomic and metabolomic profiling. The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflective of immune activation in sepsis. The expression of 1,238 genes differed with sepsis outcome: Nonsurvivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease – rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors, and these were associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. Conclusions: Host response in sepsis survivors – activation of immune response-related genes – was muted in sepsis nonsurvivors. The association of sepsis survival with robust immune response and presence of missense variants in VPS9D1 warrants replication and further functional studies.
2015-01-01 | GSE63042 | GEO
Project description:We used next-generation sequencing (NGS) to sequence and differentially quantitate miRNAs in 10 pools of plasma derived from individuals with sepsis and SIRS.Plasma pools were preferred to individual samples because they decrease the impact of individual outliers on the analysis. Total RNA was then extracted from equal volumes of plasma and technical duplicates of cDNA libraries for Illumina NGS created. Results from 10 pools representative of 89 individuals (including no-SIRS controls) are uploaded to the repository.
2016-12-01 | E-MTAB-4637 | biostudies-arrayexpress