biomedical and healthCAre Data Discovery Index Ecosystem
biomedical and healthCAre Data Discovery Index Ecosystem
| Title: | Transcriptional Profiling is Superior to Procalcitonin to Discriminate Bacterial vs. Viral Lower Respiratory Tract Infections in Hospitalized Adults
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| dateReleased: |
09-14-2015
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| description: |
Background: Distinguishing between bacterial and viral lower respiratory tract infections (LRTI) in hospitalized patients remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods: We performed whole blood transcriptional analysis in a cohort of 118 adult patients (median [IQR] age, 61 [50-76] years) hospitalized with bacterial, viral or viral-bacterial LRTI, and 40 age-matched healthy controls (60 [46-70] years). We applied class comparisons, modular analysis and class prediction algorithms to identify distinct biosignatures for bacterial and viral LRTI, which were validated in an independent group of patients. Results: Patients were classified as bacterial (B, n=22), viral (V, n=71) and bacterial-viral LRTI (BV, n=25) based on comprehensive microbiologic testing. Compared with healthy controls statistical group comparisons (p<0.01; with multiple test corrections) identified 3,376 differentially expressed genes in patients with B-LRTI; 2,391 in V-LRTI, and 2,628 in BV-LRTI. Independent of etiologic pathogen, patients with LRTI demonstrated overexpression of innate immunity and underexpression of adaptive immunity genes. Patients with B-LRTI showed significant overexpression of inflammation (B>BV>V) and neutrophils (B>BV>V) while those with V-LRTI displayed significantly greater overexpression of interferon genes (V>BV>B). The K-Nearest Neighbors (K-NN) algorithm identified 10 classifier genes that discriminated patients with bacterial vs viral LRTI with 97% [95%CI: 84-100] sensitivity and 92% [77-98] specificity. In comparison, procalcitonin classified bacterial vs viral LRTI with 38% [18-62] sensitivity and 91% [76-98] specificity. Conclusions: Transcriptional profiling can be used as a helpful tool for the diagnosis of adults hospitalized with LRTI. 158 samples, no replicates; bacterial LRTI n=22, viral LRTI n=71, bacterial-viral coinfections n=25, and healthy controls n=40
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| privacy: |
not applicable
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| aggregation: |
instance of dataset
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| ID: |
E-GEOD-60244
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| refinement: |
raw
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| alternateIdentifiers: |
60244
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| keywords: |
functional genomics
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| dateModified: |
09-20-2015
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| availability: |
available
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| types: |
gene expression
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| name: |
Homo sapiens
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| ID: |
A-GEOD-10558
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| name: |
Illumina HumanHT-12 V4.0 expression beadchip
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| accessURL: | https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-60244/E-GEOD-60244.raw.1.zip |
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ArrayExpress
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| qualifier: |
gzip compressed
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TXT
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| accessType: |
download
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| authentication: |
none
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| authorization: |
none
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| accessURL: | https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-60244/E-GEOD-60244.processed.1.zip |
| storedIn: |
ArrayExpress
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| qualifier: |
gzip compressed
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| format: |
TXT
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| accessType: |
download
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| authentication: |
none
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| authorization: |
none
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| accessURL: | https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60244 |
| storedIn: |
Gene Expression Omnibus
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| qualifier: |
not compressed
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| format: |
HTML
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| accessType: |
landing page
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| primary: |
true
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| authentication: |
none
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| authorization: |
none
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| abbreviation: |
EBI
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| homePage: | http://www.ebi.ac.uk/ |
| ID: |
SCR:004727
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| name: |
European Bioinformatics Institute
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| homePage: | https://www.ebi.ac.uk/arrayexpress/ |
| ID: |
SCR:002964
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| name: |
ArrayExpress
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