A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1087273 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pneumonia stands as the primary cause of death among children under five, with its onset attributed to a broad spectrum of microorganisms. Diagnosis poses an ongoing challenge, relying on clinical or microbiological criteria, often resulting in delayed and inaccurate treatment and unnecessary therapy. Our research focuses on identifying host transcriptomic biomarkers in the blood of children affected by viral and bacterial pneumonia, alongside healthy controls. The main goal is to establish a gene-expression signature enhancing disease diagnosis and management. We conducted an analysis of a total of 192 whole blood samples, comprising 38 controls and 154 viral and bacterial pneumonia patients recruited through the EUCLIDS clinical network. Our investigation identified 5,486 differentially expressed genes (DEGs) when comparing blood RNA from pneumonia patients with healthy controls. Functional enrichment analysis highlighted pathways related to the immune system response, encompassing neutrophil degranulation, humoral immune response, and various inflammatory pathways. In the comparative analysis of gene expression between viral and bacterial pneumonia patients, we identified 272 DEGs. Gene set analysis revealed a significant difference in pathway enrichment for the immune response, contingent on the over-regulation of gene sets in viral or bacterial pneumonias. Furthermore, we identified a 5-transcript host signature specifically designed to distinguish between viral and bacterial pediatric pneumonia (FAM20A, BAG3, TDRD9, MXRA7 and KLF14; AUC: 0.95 [0.88–1.00]), pseudo-validated in a cohort including probable bacterial and viral patients (AUC: 0.87 [0.77–0.97]). This signature holds the potential to enhance the accuracy of previously described general transcript-based signatures for viral and bacterial infections.
2024-12-09 | GSE261482 | GEO
Project description:Pneumonia remains the leading cause of death in children under five, but existing diagnostic methods frequently lead to either insufficient or excessive treatments. Our study aims to bridge this gap by identifying host transcriptomic biomarkers in the blood of children with confirmed viral or bacterial pneumonia. Using RNA sequencing, we identified and validated in an independent cohort a 5-transcript signature that accurately differentiates bacterial from viral pneumonia. This signature has considerable potential to improve diagnostic accuracy for pediatric pneumonia, minimizing delays in diagnosis and avoiding unnecessary treatments, with the possibility of significantly impacting clinical practice. a strand specific library preparation was completed using NEBNext® Ultra™ II mRNA kit (NEB) and NEB rRNA/globin depletion probes following manufacturer’s recommendations. Individual libraries were normalized using Qubit, pooled together and diluted. The sequencing was performed using a 150 paired-end configuration in a Novaseq6000 platform. Quality control of raw data was carried out using FastQC, alignment and read counting were performed using STAR, alignment filtering was done with SAMtools and read counting was carried out using FeatureCounts. RNAseq data was processed for batch correction using control samples and COMBAT-Seq package.
2024-12-08 | E-MTAB-14564 | biostudies-arrayexpress
Project description:Blood transcriptome indicates different disease etiology in pediatric ANCA-associated vasculitis subtypes.
| PRJNA532630 | ENA
Project description:Pediatric sepsis is a leading cause of mortality in children across the world. Within pediatric sepsis, how developmental age-specific host immune response impact on the occurrence and development of pediatric sepsis is still unknown, especially between infants and toddlers, which were the major susceptible age groups in sepsis. Experimental design In this study, we applied a nested case-control study strategy and analyzed the plasma proteomes of pediatric sepsis patients between infants and toddlers in comparison to their age-matched controls respectively. Each age group consists of three subgroups with different outcomes. One hundred and ten plasma samples were pooled into 16 samples for quantitative identification by LC-MS/MS. Results It was totally quantified 677 proteins. In comparison to toddlers, infant sepsis patients were characteristic with dominant neutrophil-mediated defense, suppressed adaptive immunity and NK-mediated cytotoxicity. Besides, pentose phosphate pathway was more up-regulated in infants and associated with poor outcome. Moreover, combined Hp and Thbs1 with the AUC value of 0.958 (95%CI, 0.868, 1.000) was confirmed as potential infant-adapted prognostic marker of poor outcome in sepsis. Conclusion and clinical relevance Our proteomic analysis of age-associated pediatric sepsis combined with clinical laboratory data provided a comprehensive insight into the complex, multifactorial heterogeneous host response to pediatric sepsis and allowed identification of critical differences between infant and toddler sepsis. Moreover, we confirmed that combined Hp and Thbs1 is more infant-adapted and serves as a potential prognostic biomarker for poor outcome of infant sepsis, promoting the application of age-adapted precision medicine in pediatric sepsis.
2021-11-01 | PXD026656 | Pride
Project description:Clinical diagnosis and etiology of C. psittaci pneumonia patients based on metagenomic next-generation sequencing
| PRJEB55126 | ENA
Project description:Genome-wide CpG-island methylation profiling on pediatric AML samples was performed to identify specific methylation patterns discriminating particular AML subgroups from the rest of AML samples based on the methylation profile.
2017-06-22 | GSE100284 | GEO
Project description:Purpose: The goal of this study was to compare gene expression profiles from whole blood RNA-Seq data from pediatric ANCA-associated vasculitis patients to identify mechanistic endotypes. Methods: Whole blood mRNA profiles were generated from pediatric and adult vasculitis patients using Illumina GAIIx or Hi Seq 2500 RNA-Seq. Fastq files were alinged to human genome version GRC38.91 using STAR v2.6 and count data was generated with HTSEQ v0.61p1. Counts that passed quality and minimum expression filteres were anlayzed by hierarchical clustering based on Euclidean distance, and then for differential expression with DESeq2. Results: Our workflow identified 14,156 transcripts consistently expressed in vasculitis patients. Distance hierarchcial clustering identified three groups within these pediatric samples, and two groups plus one outlier in the adult samples. The two largest pediatric clusters were used as groups for differential expression analysis with the DESeq2 package for R. DE analysis identified 3,809 differentially expressed genes between clusters. Between the two adult groups, 1,682 genes were differentially expressed. DE genes were anlayzed for enrichment using ReatomePA as the reference database. This analysis revealed that genes involved in T-cell mediated immunity are more highly expressed in pediatric patients that fell into one endotype and those involved in neutrophil and Toll-like receptor mediated inflammation are more highly expressed in pediatric patients that fell into the other endotype group. Similar results were also seen in adults. Conclusions: This study utilizes RNA-Seq data to investigate the etiologies of ANCA-associated vasculitis. Using this approach we have identified T-cell mediated immunity and Toll-like receptor mediated inflammation as potentially differing inflammatory mechanisms in both pediatric and adult vasculitis patients that do not fall along normal diagnostic criteria.
2021-01-01 | GSE129752 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE32105: Expression data from mouse livers lacking STAT3 and RelA during pneumonia GSE35513: Expression data from mouse livers lacking NF-kappaB RelA (p65) during pneumonia GSE35514: Expression data from mouse livers lacking STAT3 during pneumonia GSE35515: Expression data from mouse livers expressing or lacking Cre recombinase during pneumonia Refer to individual Series
2012-02-16 | E-GEOD-35516 | biostudies-arrayexpress
Project description:There is evidence that small extracellular vesicles (sEV) play a vital role in immune responses to viral and bacterial infection. Characteristics of urinary sEV, however, from pediatric patients with pneumonia remain to be ill-defined. In this study, we isolated sEV from urines of children with viral pneumonia or Mycoplasma pneumoniae pneumonia and healthy children and performed label-free proteomic analysis of these vesicles and identified viral-specific differentially expressed proteins compared with healthy children. Results of functional enrichment analysis suggest that the proteomic profiles of urinary sEV serve as the basis for understanding the fundamental biology of infection in children with viral pneumonia.
2023-01-13 | PXD036472 | Pride
Project description:Despite tremendous advances in diagnostic laboratory technology, identifying the pathogen(s) causing pneumonia remains challenging because the infected lung tissue cannot usually be sampled for testing. Consequently, to obtain information about pneumonia etiology, clinicians and researchers test specimens distant to the site of infection. These tests may lack sensitivity (eg, blood culture, which is only positive in a small proportion of children with pneumonia) and/or specificity (eg, detection of pathogens in upper respiratory tract specimens, which may indicate asymptomatic carriage or a less severe syndrome, such as upper respiratory infection). While highly sensitive nucleic acid detection methods and testing of multiple specimens improve sensitivity, multiple pathogens are often detected and this adds complexity to the interpretation as the etiologic significance of results may be unclear (ie, the pneumonia may be caused by none, one, some, or all of the pathogens detected). Some of these challenges can be addressed by adjusting positivity rates to account for poor sensitivity or incorporating test results from controls without pneumonia to account for poor specificity. However, no classical analytic methods can account for measurement error (ie, sensitivity and specificity) for multiple specimen types and integrate the results of measurements for multiple pathogens to produce an accurate understanding of etiology. We describe the major analytic challenges in determining pneumonia etiology and review how the common analytical approaches (eg, descriptive, case-control, attributable fraction, latent class analysis) address some but not all challenges. We demonstrate how these limitations necessitate a new, integrated analytical approach to pneumonia etiology data.
| S-EPMC5447845 | biostudies-literature