IFI27 is a gene-expression biomarker that identifies influenza-specific immune response in symptomatic patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE82050 | GEO | 2017/05/11
SECONDARY ACCESSION(S): PRJNA323822
REPOSITORIES: GEO
Similar Datasets
Project description:IFI27 is a gene-expression biomarker that identifies influenza-specific immune response in symptomatic patients
| PRJNA323822 | ENA
Project description:Recent findings have challenged the prevailing histology- or imaging-based definition of the “vulnerable plaque”. To investigate molecular characteristics associated with “clinical instability” of atherosclerosis, we performed a proteomics comparison of the vascular extracellular matrix and associated molecules in human carotid endarterectomy specimens from symptomatic versus asymptomatic patients. The proteomics data were integrated with gene expression profiling and an analysis of protein secretion by lipid-loaded human vascular smooth muscle cells. The molecular signature of plaques from symptomatic patients identified by proteomics and at least one of the other two approaches comprised matrix metalloproteinase-9, chitinase-3-like protein 1, S100A8/S100A9, cathepsin B, fibronectin and galectin-3-binding protein. These biomarker candidates were measured in 685 subjects of the Bruneck Study and found to significantly predict the progression to advanced atherosclerosis (as assessed by repeated carotid ultrasound) and the incidence of cardiovascular disease over a 10-year follow-up period, highlighting the strength of tissue-based proteomics for biomarker discovery.
2017-04-20 | PXD005130 | Pride
Project description:Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign “symptomatic” and “asymptomatic” phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24, and 48 hours post-challenge. Variation in symptomatic scoring was found among those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed flu that show differential gene expression in 1,103 probes 48 hours post-challenge compared to the remaining subjects. We have further reduced this profile to 6 genes that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge. Twenty two healthy volunteers were enrolled for an influenza challenge study. Eleven were vaccinated thirty days before challenge with H3N2 influenza. Whole blood was collected in PAXgene tubes prior to influenza challenge and then at three further timepoints (12, 24 and 48 hours post-challenge).
2014-11-06 | E-GEOD-61754 | biostudies-arrayexpress
Project description:Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign “symptomatic” and “asymptomatic” phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24, and 48 hours post-challenge. Variation in symptomatic scoring was found among those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed flu that show differential gene expression in 1,103 probes 48 hours post-challenge compared to the remaining subjects. We have further reduced this profile to 6 genes that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge.
2014-11-06 | GSE61754 | GEO
Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.
2009-08-06 | E-GEOD-17156 | biostudies-arrayexpress
Project description:Single Cell Transcriptomics identifies Focal Segmental Glomerulosclerosis Remission Endothelial Biomarker
| PRJNA591621 | ENA
Project description:Diagnosis of acute respiratory viral infection is currentlybased on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals.
2009-08-06 | GSE17156 | GEO
Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130174 | GEO
Project description:The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify macrophages to have elevated expression of IFI27 in areas of infection.
2024-01-28 | GSE253474 | GEO
Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130175 | GEO