Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MNGS of Pulmonary Fluid in Immunocompromised Children

ABSTRACT:

Despite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. In this study, we performed RNA and DNA-based metagenomic next generation sequencing (mNGS) on 41 lower respiratory samples collected from 34 children. We identified a rich cross-domain pulmonary microbiome containing bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Potential pathogens were detected in half of samples previously negative by clinical diagnostics. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease. Metatranscriptomic (RNA) sequencing libraries are reported in the manuscript and are included for this release.

PROVIDER: phs001684 | dbGaP |

REPOSITORIES: dbGaP

ACCESS DATA

Json Xml

Similar Datasets

Leveraging the pulmonary immune response and microbiome for improved lower respiratory tract infection diagnosis in critically ill children

Project description:BACKGROUND. Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging since non-infectious respiratory illnesses appear clinically similar and existing microbiologic tests are often falsely negative or detect incidentally-carried microbes common in children. These challenges result in antimicrobial overuse and adverse patient outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and precision treatment remains unclear. METHODS. We used tracheal aspirate RNA-sequencing to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a random forest gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n=117) or of non-infectious respiratory failure (n=50). We then developed a classifier that integrates the: i) host LRTI probability, ii) abundance of respiratory viruses, and iii) dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm. RESULTS. The host classifier achieved a median AUC of 0.967 by 5-fold cross-validation, driven by activation markers of T cells, alveolar macrophages and the interferon response. The integrated classifier achieved a median AUC of 0.986 and significantly increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n=94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those. CONCLUSIONS. Lower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.

2022-12-06 | GSE212532 | GEO

Elucidating the etiology and molecular pathogenicity of infectious diarrhea by high throughput RNA sequencing

Project description:Diarrhea remains a major cause of death in children. Current diagnostic methods largely rely on stool culture and suffer from low sensitivity and inadequate specificity, often leading to inappropriate treatment. The objective of the present study was to use RNA sequencing (RNAseq) analysis to determine blood transcriptional profiles specific for several common pathogenic bacteria and viruses that cause diarrhea in children. We collected whole blood samples from children in Mexico having diarrhea associated with a single pathogen and without systemic complications. Our RNAseq data suggested that the blood signatures can differentiate children with diarrhea from healthy children either with or without bacterial colonization. Moreover, we detected different expression profiles from bacterial and viral infection, demonstrating for the first time the use of RNAseq to identify the etiology of infectious diarrhea. Whole blood from 207 children including children with diarrhea caused by rotavirus (n=55), E.coli (n=55), Salmonella (n=36), Shigella (n=37) and control children (n=24).

2015-06-04 | E-GEOD-69529 | biostudies-arrayexpress

Elucidating the etiology and molecular pathogenicity of infectious diarrhea by high throughput RNA sequencing

2015-06-04 | GSE69529 | GEO

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities, dataset 1

Project description:This study includes the whole-genome screening of unbalanced chromosomal rearrangements (copy-number variants; CNV) in children with ID/DD, ASD and MCA. We identified a broad range of pathogenic/likely pathogenic CNVs as well as variants of unclear significance and likely benign variants. Our results confirm the benefit of array-CGH in the current clinical genetic diagnostics through the identification of genetic cause of ID/DD in the high proportion of affected children.

2019-04-30 | E-MTAB-6685 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities, dataset 3

2019-04-30 | E-MTAB-6731 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities, dataset 2

2019-04-30 | E-MTAB-6733 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities, dataset 4

2019-04-30 | E-MTAB-6735 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities, dataset 5

2019-04-30 | E-MTAB-6734 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities

2019-08-31 | E-MTAB-7696 | biostudies-arrayexpress

Array-CGH in children with intellectual disabilities, developmental delays, autism spectrum disorders and multiple congenital abnormalities