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Series GSE133378 Query DataSets for GSE133378
Status Public on Jun 27, 2019
Title Diagnosing enterovirus meningitis via blood transcriptomics: an alternative for lumbar puncture?
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Background: Meningitis can be caused by several viruses and bacteria. Identifying the causative pathogen as quickly as possible is crucial to initiate the most optimal therapy, as acute bacterial meningitis is associated with a significant morbidity and mortality. Bacterial meningitis requires antibiotics, as opposed to enteroviral meningitis, which only requires supportive therapy. Clinical presentation is usually not sufficient to differentiate between viral and bacterial meningitis, thereby necessitating cerebrospinal fluid (CSF) analysis by PCR and/or time-consuming bacterial cultures. However, collecting CSF in children is not always feasible and a rather invasive procedure.

Methods: In 12 Belgian hospitals, we obtained acute blood samples from children with signs of meningitis (49 viral and 7 bacterial cases). (aged between 3 months and 16 years). After pathogen confirmation on CSF, the patient was asked to give a convalescent sample after recovery. 3’mRNA sequencing was performed to determine differentially expressed genes (DEGs) to create a host transcriptomic profile.

Results: Enteroviral meningitis cases displayed the largest upregulated fold change enrichment in type I interferon production, response and signaling pathways. Patients with bacterial meningitis showed a significant upregulation of genes related to macrophage and neutrophil activation. We found several significantly DEGs between enteroviral and bacterial meningitis. Random forest classification showed that we were able to differentiate enteroviral from bacterial meningitis with an AUC of 0.982 on held-out samples.

Conclusions: Enteroviral meningitis has an innate immunity signature with type 1 interferons as key players. Our classifier, based on blood host transcriptomic profiles of different meningitis cases, is a possible strong alternative for diagnosing enteroviral meningitis.
 
Overall design Gene expression profiles of host blood can be used to differentiate between different types of meningitis. Libraries were sequenced in 4 lanes and each sequencing lane is represented as a column in the processed data files.
 
Contributor(s) Bartholomeus E, De Neuter N, Lemay A, Pattyn L, Tuerlinckx D, Weynants D, Van Lede K, van Berlaer G, Bulckaert D, Boi T, Vander Auwera A, Raes M, Van der Linden D, Verhelst H, Van Steijn S, Jonckheer T, Dehoorne J, Joos R, Jansens H, Suls A, Van Damme P, Laukens K, Mortier G, Meysman P, Ogunjimi B
Citation(s) 31443725
Submission date Jun 26, 2019
Last update date Sep 26, 2019
Contact name Nicolas De Neuter
Organization name University of Antwerp
Street address Middelheimlaan 1
City Antwerpen
ZIP/Postal code 2020
Country Belgium
 
Platforms (1)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (476)
GSM3906536 AZT11C_S34_L001
GSM3906537 AZT11C_S34_L002
GSM3906538 AZT11C_S34_L003
Relations
BioProject PRJNA551288
SRA SRP212148

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE133378_180214_NB501809_0255_AHJFNMBGX5_readcounts.txt.gz 4.6 Mb (ftp)(http) TXT
GSE133378_180302_NB501809_0264_AHJGHCBGX5_readcounts.txt.gz 3.8 Mb (ftp)(http) TXT
GSE133378_180321_NB501809_0276_AHJJ3LBGX5_readcounts.txt.gz 3.7 Mb (ftp)(http) TXT
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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