Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA134645 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Sepsis is a time-sensitive condition associated with significant mortality, morbidity, and healthcare costs, especially when the diagnosis is delayed. Clinicians often fail to accurately differentiate between sepsis and a sterile systemic inflammatory response syndrome (SIRS) among patients who incur sterile tissue damage from major surgery. Sepsis is driven by a dysregulated host response to pathogens; SIRS is driven by tissue damage. Transcriptomic profiling of whole blood or of specific cellular components of blood have been utilized for discovering underlying etiological differences between sepsis and uninfected SIRS. Blood-based gene microarrays have demonstrated efficacy in differentiating sepsis from SIRS. Urine is often collected from critically ill patients as standard clinical care, but the diagnostic utility of urine sepsis biomarkers is unknown. In this study we used single-center prospective cohorts of SIRS and sepsis patients, we tested the hypothesis that machine learning feature selection from whole genome transcriptomic urinary RNA signatures can identify gene expression patterns that differentiate between sepsis and sterile SIRS within twelve hours of sepsis onset.
2021-07-12 | GSE168440 | GEO
Project description:Sepsis is a time-sensitive condition associated with significant mortality, morbidity, and healthcare costs, especially when the diagnosis is delayed. Clinicians often fail to accurately differentiate between sepsis and a sterile systemic inflammatory response syndrome (SIRS) among patients who incur sterile tissue damage from major surgery. Sepsis is driven by a dysregulated host response to pathogens; SIRS is driven by tissue damage. Transcriptomic profiling of whole blood or of specific cellular components of blood have been utilized for discovering underlying etiological differences between sepsis and uninfected SIRS. Blood-based gene microarrays have demonstrated efficacy in differentiating sepsis from SIRS. Urine is often collected from critically ill patients as standard clinical care, but the diagnostic utility of urine sepsis biomarkers is unknown. In this study we used single-center prospective cohorts of SIRS and sepsis patients, we tested the hypothesis that machine learning feature selection from whole genome transcriptomic urinary RNA signatures can identify gene expression patterns that differentiate between sepsis and sterile SIRS within twelve hours of sepsis onset.
2021-07-12 | GSE168442 | GEO
Project description:The host response in critically ill patients with sepsis, septic shock remains poorly defined. Considerable research has been conducted to accurately distinguish patients with sepsis from those with non-infectious causes of disease. Technological innovations have positioned systems biology at the forefront of biomarker discovery. Analysis of the whole-blood leukocyte transcriptome enables the assessment of thousands of molecular signals beyond simply measuring several proteins in plasma, which for use as biomarkers is important since combinations of biomarkers likely provide more diagnostic accuracy than the measurement of single ones or a few. Evidence suggests that genome-wide transcriptional profiling of blood leukocytes can assist in differentiating between infection and non-infectious causes of severe disease. Of importance, RNA biomarkers have the potential advantage that they can be measured reliably in rapid quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)-based point of care tests. PAXgene blood RNA was isolated at intensive-care unit (ICU) admission and throughout ICU length-of-stay. Through the use of genome-wide microarrays we aimed to identify molecular features that enbale the adequate discrimination of infectious and non-infectious sources of critical illness. Moreover, biological pathway analysis was used to tease out the most relevant biological units in sepsis and septic shock.
2015-07-06 | E-GEOD-65682 | biostudies-arrayexpress
Project description:Neonates manifest a unique host response to sepsis even among other children. Preterm neonates may experience sepsis soon after birth or during often protracted birth hospitalizations as they attain physiologic maturity. We examined the transcriptome using genome-wide expression profiling on prospectively collected peripheral blood samples from infants evaluated for sepsis within 24 hours after clinical presentation. Simultaneous plasma samples were examined for alterations in inflammatory mediators. Group designation (sepsis or uninfected) was determined retrospectively based on clinical exam and laboratory results over the next 72 hours from the time of evaluation. Unsupervised analysis showed the major node of separation between groups was timing of sepsis episode relative to birth (early, <3 days or late, >3 days). Principal component analyses revealed significant differences between patients with early or late sepsis despite the presence of similar key immunologic pathway aberrations in both groups. Unique to neonates, the uninfected state and host response to sepsis is significantly affected by timing relative to birth. Future therapeutic approaches may need to be tailored to the timing of the infectious event based on post-natal age. We used human microarrays to detail the molecular profile of the events that occur following sepsis in hospitalized neonates Please note that 'uninfected chorio' represents babies who were not infected but had chorioamnionitis exposure
2015-07-06 | E-GEOD-69686 | biostudies-arrayexpress
Project description:Neonatal gram-negative sepsis is often characterized by a fulminat clinical course compared to adults resulting in higher morbidity and mortality. Genome-wide gene expression analysis can provide insights into the molecular alterations in sepsis. To evaluate in vitro activation of the neonatal and adult immune system, gene expression patterns were compared in mononuclear cells from cord (CBMNC) and adult peripheral blood (APBMNC). To better understand the influence of early molecular signals on the effects of sepsis, Affymetrix gene profiling (8475 genes) was done on RNA isolated from CBMNC and APBMNC without and after incubation with 100 ng/ml lipopolysaccharide (LPS). We demonstrated significant alterations in the expression of 108 CBMNC and APBMNC genes compared with basal levels, 188 significant changes in CBMNC, and 97 in APBMNC, including cytokines, chemokines, and immunoregulatory genes. Furthermore, we found five genes showing a significant interaction effect between cell-type and LPS-stimulation, including tumor necrosis factor receptor superfamily, member 6 (FAS), absent in melanoma 2 (AIM2), malic enzyme 1 (ME1), hemoglobin epsilon 1 (HBE1), and trans-prenyltransferase (TPRT). These results provide further support for a marked difference in the pathogenesis of neonatal and adult sepsis and may stimulate additional studies to investigate some of the altered genes as potential new targets for diagnostic tools and therapeutic strategies. Keywords: LPS response
2005-08-21 | GSE3140 | GEO
Project description:We aimed to identify the gene network and pathway biology associated with neonatal sepsis by determining genome-wide alterations in host RNA in infected infants Samples were obtained from control and infected human neonates.
2014-08-12 | E-GEOD-25504 | biostudies-arrayexpress
Project description:We aimed to identify the gene network and pathway biology associated with neonatal sepsis by determining genome-wide alterations in host RNA in infected infants
2014-08-12 | GSE25504 | GEO
Project description:The host response in critically ill patients with sepsis, septic shock remains poorly defined. Considerable research has been conducted to accurately distinguish patients with sepsis from those with non-infectious causes of disease. Technological innovations have positioned systems biology at the forefront of biomarker discovery. Analysis of the whole-blood leukocyte transcriptome enables the assessment of thousands of molecular signals beyond simply measuring several proteins in plasma, which for use as biomarkers is important since combinations of biomarkers likely provide more diagnostic accuracy than the measurement of single ones or a few. Evidence suggests that genome-wide transcriptional profiling of blood leukocytes can assist in differentiating between infection and non-infectious causes of severe disease. Of importance, RNA biomarkers have the potential advantage that they can be measured reliably in rapid quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)-based point of care tests.
2015-07-06 | GSE65682 | GEO
Project description:DNA methylation is the current strategy in the field of biomarker discovery due to its prognostic efficiency. Its role in prognosis and early diagnosis has been recognized in various types of cancer. Sepsis still remains one of the major causes of neonatal mortality due to the lack of sensitive diagnostic and prognostic biomarkers. Delay in sepsis diagnosis leads to treatment difficulties and poor outcomes. In this study, we have done an epigenome wide search to identify potential markers for prognosis of neonatal sepsis which may improve the treatment strategies. Illumina 450K methylation microarray revealed that the genes involved in transendothelial leukocyte migration were differentially methylated in septic newborns compared to non-septic newborns, especially the Protocadherin Beta group. Genes like ITGB2-AS1, CCS were found to be differentially methylated significantly, which gives the hope of developing novel, potential epigenetic markers for neonatal sepsis. From this study, we conclude that DNA methylation might play crucial functions in the pathophysiology of neonatal sepsis which was obvious from the difference in methylation level among septic and non-septic babies. In future, the potentiality of these epigenetic biomarkers can be studied in large scale with appropriate techniques which will give further in depth knowledge in this context. DNA methylation analysis of three septic newborns and three non-septic newborns were performed with Illumina Infinium HumanMethylation450 BeadChip. Peripheral venous blood sample was collected from the babies during the third day of birth while taking blood for routine investigations. Non-septic babies are babies admitted to NICU and sampled for other minor ailments. Genomic DNA was extracted using QIAmp DNA Blood Mini kit (Qiagen, Hilden, Germany) and bisulfite treated using EZ DNA methylation kit (Zymoresearch, USA).
2014-06-20 | E-GEOD-58651 | biostudies-arrayexpress
Project description:A phenotypically and functinoally distinct subset of human blood dendritic cells expressing CD11b is specific of the neonatal environment. We have employed whole genome microarray expression profiling to identify the specific gene signature of CD11b+ cord blood dendritic cells as compared to their adult peripheral blood counterparts. Peripheral blood adult cDC2 (CD20- CD11c+ CD14- BDCA1+ CD11b- ), neonatal cord blood cDC2 (CD20- CD11c+ CD14- BDCA1+ CD11b-) and neonatal cord blood cDC2b (CD20- CD11c+ CD14- BDCA1+ CD11b+) were FACS purified from BDCA1+ magnetically. Neonatal monocytes (CD11c+ CD14+) and neonatal naive T cells (CD3+ CD4+ CD56- CD25- CD45RO-) were used as controls.
2018-09-21 | GSE104110 | GEO