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  5. A systems immunology approach to investigate cytokine responses to viruses and bacteria and their association with disease
 
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A systems immunology approach to investigate cytokine responses to viruses and bacteria and their association with disease
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A systems immunology approach to investigate cytokine responses to viruses and bacteria and their association with disease.pdf (7.34 MB)
Published version
Author(s)
Lin, Lijing
Curtin, John A
Regis, Eteri
Hirsman, Aurica
Howard, Rebecca
more
Type
Journal Article
Abstract
Patterns of human immune responses to viruses and bacteria and how this impacts risk of infections or onset/exacerbation of chronic respiratory diseases are poorly understood. In a population-based birth cohort, we measured peripheral blood mononuclear cell responses (28 cytokines) to respiratory viruses and bacteria, Toll-like receptor ligands and phytohemagglutinin, in 307 children. Cytokine responses were highly variable with > 1000-fold differences between children. Machine learning revealed clear distinction between virus-associated and bacteria-associated stimuli. Cytokines clustered into three functional groups (anti-viral, pro-inflammatory and T-cell derived). To investigate mechanisms potentially explaining such variable responses, we investigated cytokine Quantitative Trait Loci (cQTLs) of IL-6 responses to bacteria and identified nine (eight novel) loci. Our integrative approach describing stimuli, cytokines and children as variables revealed robust immunologically and microbiologically plausible clustering, providing a framework for a greater understanding of host-responses to infection, including novel genetic associations with respiratory disease.
Date Issued
2022-08-05
Date Acceptance
2022-07-11
Citation
Scientific Reports, 2022, 12 (1), pp.1-14
URI
http://hdl.handle.net/10044/1/103194
URL
https://www.nature.com/articles/s41598-022-16509-4
DOI
https://www.dx.doi.org/10.1038/s41598-022-16509-4
ISSN
2045-2322
Publisher
Nature Portfolio
Start Page
1
End Page
14
Journal / Book Title
Scientific Reports
Volume
12
Issue
1
Copyright Statement
© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
http://creativecommons.org/licenses/by/4.0/
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000836707300056&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
ASTHMA EXACERBATIONS
GENOME-WIDE ASSOCIATION
IMPUTATION
INFECTIONS
Multidisciplinary Sciences
RECEPTOR
RISK
Science & Technology
Science & Technology - Other Topics
Publication Status
Published
Article Number
ARTN 13463
Date Publish Online
2022-08-05
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