T cell and Monocyte Specific RNAseq Analysis in Septic and Non Septic Critically-Ill Patients and in Patients with Cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA552599 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9642740_1.fastq.gz | Fastqsanger.gz | |||
| SRR9642740_2.fastq.gz | Fastqsanger.gz | |||
| SRR9642750_1.fastq.gz | Fastqsanger.gz | |||
| SRR9642750_2.fastq.gz | Fastqsanger.gz | |||
| SRR9642760_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 471 |
Similar Datasets
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: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:Transcriptomic clustering of critically-ill COVID-19 patients
| PRJNA809558 | ENA
Project description:To determine whether differential expression of cellular microRNAs plays a role in the host response to Influenza A (H1N1) infection, we have employed the Agilent miRNA microarray (V3) as a discovery platform to identify microRNAs between the critically ill Patients with Influenza A (H1N1) and the healthy controls. Five critically ill patients with a diagnosis of 2009 Inflluenza A (H1N1) and three healthy controls were included in the study. The Peripheral Blood Mononuclear Cells (PBMCs) were isolated and total RNA was extracted respectively.
2012-12-28 | E-GEOD-24956 | biostudies-arrayexpress
Project description:The PREVAIL study was a Phase II/III randomized controlled trial examining the use of lactoferrin to prevent nosocomial infections in critically ill patients undergoing mechanical ventilation. Gene expression data was generated from a consecutive subset of patients at the lead study site. We used the Affymetrix PrimeView array to generate expression data at various time points during the ICU stay.
2018-08-22 | GSE118657 | GEO
Project description:Longitudinal Gene expression profiling of whole blood from critically ill influenza and bacterial pneumonia patients. In addition before vs 7 days post influenza vaccination volunteer samples are assayed.
2011-06-30 | GSE20346 | GEO
Project description:Background: COVID-19 has revealed novel pathological mechanisms, particularly hypercoagulability leading to increased thrombotic risk in critically ill patients. This study investigates transcriptional signatures associated with thrombosis development in COVID-19 intensive care unit (ICU) patients and evaluates their predictive potential. Methods: We performed whole blood transcriptional profiling of 57 mechanically ventilated COVID-19 patients, comparing those with thrombotic complications (TC, n=36) to those without (non-TC, n=21) using differential gene expression and machine learning approaches. Results: TC patients showed greater transcriptome disruption and 283 differentially expressed genes compared to non-TC patients. Key features included enhanced neutrophil activation, inflammatory responses, and monocyte activation alongside suppressed lymphocyte function. An OPLS-DA model achieved excellent classification performance (AUC=0.961, 95% CI: 0.905-0.997). The maltase-glucoamylase gene (MGAM) was the top discriminatory biomarker outperforming traditional clinical markers like D-dimer and C-reactive protein (AUC=0.94). Conclusions: Thrombotic complications in critically ill COVID-19 patients are characterized by distinct transcriptional signatures reflecting heightened neutrophil activation and inflammatory dysregulation. MGAM represents a novel potential biomarker that outperforms traditional clinical markers for identifying patients at high thrombotic risk, offering new opportunities for personalized risk stratification and management in severe COVID-19.
2025-06-18 | GSE300129 | GEO
Project description:Sepsis patients experience a complex interplay of host pro- and anti-inflammatory processes which can compromise outcome. Even taking the latest clinical and scientific research data into account, the immunosuppressive events occurring during a septic episode are incompletely understood. Moreover, there is a lack of data on the way epigenetics can modulate immunosuppression, which in turn affects patient survival. To advance current understanding of the mechanisms underlying immunosuppression, in this study we explored DNA methylation changes using the Infinium MethylationEPIC v1.0 BeadChip Kit in leukocytes from patients suffering from sepsis, septic shock, and critically ill patients as controls, within the first 24 h after admission in the Intensive Care Unit of a tertiary hospital. The top 100 differentially methylated positions (DMPs) between septic shock and critically ill patients enabled us to clearly distinguish between the 3 groups of patients. Interestingly, the top 6,657 DMPs were associated with organ dysfunction and lactate levels. Two different analysis approaches (based on the use of DMRcate and mCSEA) comparing septic shock and critically ill patients revealed a total of 1,256 differentially methylated regions (DMRs) involved in critical immune system-related pathways. Among the individual genes exhibiting significant differential methylation, IL10, TREM1, IL1B, and TNFAIP8 showed the largest methylation differences among the different groups when analyzing their methylation levels by DNA bisulfite pyrosequencing. Our findings indicate that DNA methylation profile undergoes the most substantial changes in patients with septic shock, and that these changes are linked to disease severity. Importantly, IL10 and S100A8, which are closely related to immunosuppression, were hypomethylated in septic shock patients.
2023-12-18 | GSE247524 | GEO
Project description:Sepsis is a frequent complication in critically ill patients and highly heterogeneous that is associated with high morbidity and mortality rates, especially in the elderly population. Utilizing RNA-Sequencing (RNA-Seq) to analysis biological pathways is widely used in clinical and molecular genetics studies, but in elderly patients with sepsis are still lacking. Hence, we aim to investigate the mortality-relevant biological features and transcriptomic features in elderly patients who were admitted to intensive care unit (ICU) for sepsis.
2022-11-03 | GSE216902 | GEO
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress