Universität zu Köln

Myall, Ashleigh C., Perkins, Simon, Rushton, David, David, Jonathan, Spencer, Phillippa, Jones, Andrew R. and Antczak, Philipp ORCID: 0000-0001-9600-7757 (2021). An OMICs-based meta-analysis to support infection state stratification. Bioinformatics, 37 (16). S. 2347 - 2356. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2059

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Abstract

Motivation: A fundamental problem for disease treatment is that while antibiotics are a powerful counter to bacteria, they are ineffective against viruses. Often, bacterial and viral infections are confused due to their similar symptoms and lack of rapid diagnostics. With many clinicians relying primarily on symptoms for diagnosis, overuse and misuse of modern antibiotics are rife, contributing to the growing pool of antibiotic resistance. To ensure an individual receives optimal treatment given their disease state and to reduce over-prescription of antibiotics, the host response can in theory be measured quickly to distinguish between the two states. To establish a predictive biomarker panel of disease state (viral/bacterial/no-infection), we conducted a meta-analysis of human blood infection studies using machine learning. Results: We focused on publicly available gene expression data from two widely used platforms, Affymetrix and Illumina microarrays as they represented a significant proportion of the available data. We were able to develop multi-class models with high accuracies with our best model predicting 93% of bacterial and 89% viral samples correctly. To compare the selected features in each of the different technologies, we reverse-engineered the underlying molecular regulatory network and explored the neighbourhood of the selected features. The networks highlighted that although on the gene-level the models differed, they contained genes from the same areas of the network. Specifically, this convergence was to pathways including the Type I interferon Signalling Pathway, Chemotaxis, Apoptotic Processes and Inflammatory/Innate Response.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Myall, Ashleigh C. UNSPECIFIED UNSPECIFIED UNSPECIFIED Perkins, Simon UNSPECIFIED UNSPECIFIED UNSPECIFIED Rushton, David UNSPECIFIED UNSPECIFIED UNSPECIFIED David, Jonathan UNSPECIFIED UNSPECIFIED UNSPECIFIED Spencer, Phillippa UNSPECIFIED UNSPECIFIED UNSPECIFIED Jones, Andrew R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Antczak, Philipp UNSPECIFIED orcid.org/0000-0001-9600-7757 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-586865
DOI:	10.1093/bioinformatics/btab089
Journal or Publication Title:	Bioinformatics
Volume:	37
Number:	16
Page Range:	S. 2347 - 2356
Date:	2021
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2059
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language MHC CLASS-I; GENE-EXPRESSION; COMMUNITY STRUCTURE; INTERFERON; SELECTION; MICROARRAY; MODELS; FAMILY Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/58686