Gene expression patterns in blood leukocytes discriminate patients with acute infections - GSE6269 - GPL96

Each infectious agent represents a unique combination of pathogen-associated molecular patterns that interact with specific pattern-recognition receptors expressed on immune cells. Therefore, we surmised that the blood immune cells of individuals with different infections might bear discriminative transcriptional signatures. Gene expression profiles were obtained for 131 peripheral blood samples from pediatric patients with acute infections caused by influenza A virus, Gram-negative (Escherichia coli) or Gram-positive (Staphylococcus aureus and Streptococcus pneumoniae) bacteria. Thirty-five genes were identified that best discriminate patients with influenza A virus infection from patients with either E coli or S pneumoniae infection. These genes classified with 95% accuracy (35 of 37 samples) an independent set of patients with either influenza A, E coli, or S pneumoniae infection. A different signature discriminated patients with E coli versus S aureus infections with 85% accuracy (34 of 40). Furthermore, distinctive gene expression patterns were observed in patients presenting with respiratory infections of different etiologies. Thus, microarray analyses of patient peripheral blood leukocytes might assist in the differential diagnosis of infectious diseases.

Entire study included 144 samples. Only 143 are included in this series because the CHP/CEL file was not available for sample PBMC_Healthy_INF295.

Blood infection due to Influenza A virus (2021 ICD-10-CM code* = J10)

Escherichia coli (2021 ICD-10-CM code* = B96.20)

Staphylococcus aureus (2021 ICD-10-CM code* = B95.8)

Streptococcus pneumoniae (2021 ICD-10-CM code* = B95.3)

Sepsis (2021 ICD-10-CM code* = A41)

The data were analyzed with Microarray Suite version 5.0 (MAS 5.0) using Affymetrix default analysis settings and global scaling as normalization method. The trimmed mean target intensity of each array was arbitrarily set to 500.

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6269