Whole blood gene expression profiling of neonates with confirmed bacterial sepsis

Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction...

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Main Authors: Paul Dickinson, Claire L. Smith, Thorsten Forster, Marie Craigon, Alan J. Ross, Mizan R. Khondoker, Alasdair Ivens, David J. Lynn, Judith Orme, Allan Jackson, Paul Lacaze, Katie L. Flanagan, Benjamin J. Stenson, Peter Ghazal
Format: Article
Language:English
Published: Elsevier 2015-03-01
Series:Genomics Data
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2213596014001160
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spelling doaj-d54f889f318f4447bd703971eee188f32020-11-25T02:08:01ZengElsevierGenomics Data2213-59602015-03-013C414810.1016/j.gdata.2014.11.003Whole blood gene expression profiling of neonates with confirmed bacterial sepsisPaul Dickinson0Claire L. Smith1Thorsten Forster2Marie Craigon3Alan J. Ross4Mizan R. Khondoker5Alasdair Ivens6David J. Lynn7Judith Orme8Allan Jackson9Paul Lacaze10Katie L. Flanagan11Benjamin J. Stenson12Peter Ghazal13Division of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKNeonatal Unit, Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKFios Genomics Ltd., Edinburgh BioQuater, Edinburgh EH16 4SB, UKAnimal & Bioscience Research Department, AGRIC, Teagasc, Grange, Dunsany, Co. Meath, IrelandNeonatal Unit, Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UKNeonatal Unit, Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKMRC Research Laboratories, Atlantic Boulevard, PO Box 273, Fajara, GambiaNeonatal Unit, Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UKDivision of Infection and Pathway Medicine, Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh EH16 4SB, UKNeonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.http://www.sciencedirect.com/science/article/pii/S2213596014001160Neonatal sepsisWhole bloodGene expression profilingMicroarray
collection DOAJ
language English
format Article
sources DOAJ
author Paul Dickinson
Claire L. Smith
Thorsten Forster
Marie Craigon
Alan J. Ross
Mizan R. Khondoker
Alasdair Ivens
David J. Lynn
Judith Orme
Allan Jackson
Paul Lacaze
Katie L. Flanagan
Benjamin J. Stenson
Peter Ghazal
spellingShingle Paul Dickinson
Claire L. Smith
Thorsten Forster
Marie Craigon
Alan J. Ross
Mizan R. Khondoker
Alasdair Ivens
David J. Lynn
Judith Orme
Allan Jackson
Paul Lacaze
Katie L. Flanagan
Benjamin J. Stenson
Peter Ghazal
Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
Genomics Data
Neonatal sepsis
Whole blood
Gene expression profiling
Microarray
author_facet Paul Dickinson
Claire L. Smith
Thorsten Forster
Marie Craigon
Alan J. Ross
Mizan R. Khondoker
Alasdair Ivens
David J. Lynn
Judith Orme
Allan Jackson
Paul Lacaze
Katie L. Flanagan
Benjamin J. Stenson
Peter Ghazal
author_sort Paul Dickinson
title Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
title_short Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
title_full Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
title_fullStr Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
title_full_unstemmed Whole blood gene expression profiling of neonates with confirmed bacterial sepsis
title_sort whole blood gene expression profiling of neonates with confirmed bacterial sepsis
publisher Elsevier
series Genomics Data
issn 2213-5960
publishDate 2015-03-01
description Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.
topic Neonatal sepsis
Whole blood
Gene expression profiling
Microarray
url http://www.sciencedirect.com/science/article/pii/S2213596014001160
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