Diagnosis of childhood bacterial and viral infection using host RNA expression- Discovery set and Inflammatory validation cohort - GSE72829-GPL10558 - Also, deposited as SubSeries (GSE72809 and GSE80412)

Genome-wide analysis of transcriptional profiles in children <17 years of age with bacterial or viral infections or with clinical features suggestive of infection. This is also deposited as SubSeries (GSE72809 and GSE80412)

Overall design [Discovery set]

Patients were recruited at or after presentation to hospital. Main inclusion criteria were presence of illness of sufficient severity to warrant blood tests for clinical reasons, in child aged <17 years. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 v4 Beadchips (Discovery set) or Illumina Human HT-12 V3 Beadchips (Validation set). Numbers of arrays analysed were as follows: Definite Bacterial infection (n=52), Definite Viral infection (n=92), Probable Bacterial infection (n=42), Probable Viral infection (n=5), infections of uncertain bacterial or viral aetiology (n=49), Healthy controls (n=52).

Overall design [Inflammatory validation cohort]

Patients were recruited at or after presentation to hospital. Main inclusion criteria were presence of illness of sufficient severity to warrant blood tests for clinical reasons, in child aged <17 years. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 v4 Beadchips. Numbers of arrays analysed were as follows: HSP (n=18), JIA (n=30)

Bacterial infection (2021 ICD-10-CM code* = A49.9)

Viral infection (2021 ICD-10-CM code* = B99.9)

Henoch-Schonlein purpura (2021 ICD-10-CM code* = D69.0)

Juvenile idiopathic arthritis (2021 ICD-10-CM code* = M08.90)

Overall design [Discovery set]

The data were normalised using RSN, after background subtraction and filtering for transcripts common to Illumina HT12-V3 The software used for data normalization was 'R' Language and Environment for Statistical Computing (R) 3.1.2

Overall design [Inflammatory validation cohort]

The data were normalised using RSN, after background subtraction and filtering for transcripts common to Illumina HT12-V3

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72829

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72809 [Discovery set]

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80412 [Inflammatory validation cohort]