Enterovirus-associated changes in blood transcriptomic profiles of children with genetic susceptibility to type 1 diabetes
|Author:||Lietzen, Niina1; An, Le T. T.1; Jaakkola, Maria K.1,2;|
1Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Tykistökatu 6, FI-20520 Turku, Finland
2Department of Mathematics and Statistics, University of Turku, Turku, Finland
3Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
4Fimlab Laboratories, Pirkanmaa Hospital District, Tampere, Finland
5Department of Pediatrics, Turku University Hospital, Turku, Finland
6Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
7Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
8Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
9Folkhälsan Research Center, Helsinki, Finland
10Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
11Department of Pediatrics, PEDEGO Research Unit, University of Oulu, Oulu, Finland
12Department of Children and Adolescents, Medical Research Center, Oulu University Hospital, Oulu, Finland
13Immunogenetics Laboratory, Institute of Biomedicine, University of Turku, Turku, Finland
14Department of Clinical Microbiology, Turku University Hospital, Turku, Finland
15Department of Physiology, Institute of Biomedicine, University of Turku, Turku, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201803236138
|Publish Date:|| 2018-03-23
Aims/hypothesis: Enterovirus infections have been associated with the development of type 1 diabetes in multiple studies, but little is known about enterovirus-induced responses in children at risk for developing type 1 diabetes. Our aim was to use genome-wide transcriptomics data to characterise enterovirus-associated changes in whole-blood samples from children with genetic susceptibility to type 1 diabetes.
Methods: Longitudinal whole-blood samples (356 samples in total) collected from 28 pairs of children at increased risk for developing type 1 diabetes were screened for the presence of enterovirus RNA. Seven of these samples were detected as enterovirus-positive, each of them collected from a different child, and transcriptomics data from these children were analysed to understand the individual-level responses associated with enterovirus infections. Transcript clusters with peaking or dropping expression at the time of enterovirus positivity were selected as the enterovirus-associated signals.
Results: Strong signs of activation of an interferon response were detected in four children at enterovirus positivity, while transcriptomic changes in the other three children indicated activation of adaptive immune responses. Additionally, a large proportion of the enterovirus-associated changes were specific to individuals. An enterovirus-induced signature was built using 339 genes peaking at enterovirus positivity in four of the children, and 77 of these genes were also upregulated in human peripheral blood mononuclear cells infected in vitro with different enteroviruses. These genes separated the four enterovirus-positive samples clearly from the remaining 352 blood samples analysed.
Conclusions/interpretation: We have, for the first time, identified enterovirus-associated transcriptomic profiles in whole-blood samples from children with genetic susceptibility to type 1 diabetes. Our results provide a starting point for understanding the individual responses to enterovirus infections in blood and their potential connection to the development of type 1 diabetes.
Data availability: The datasets analysed during the current study are included in this published article and its supplementary information files (www.btk.fi/research/computational-biomedicine/1234-2) or are available from the Gene Expression Omnibus (GEO) repository (accession GSE30211).
|Pages:||381 - 388|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3121 General medicine, internal medicine and other clinical medicine
This work was financially supported by the European Research Council (ERC) (decision number 677943), JDRF (grants 17-2013-533 and 2-2013-32), the Academy of Finland (Centre of Excellence in Molecular Systems Immunology and Physiology Research, 2012–2017, decision number 250114 and grants 287423, 288671, 292482, 292335, 294337, 296801 and 304995), the European Union’s Horizon 2020 research and innovation programme (decision number 675395), Tekes, the Finnish Funding Agency for Innovation (1877/31/2016), the Sigrid Jusélius Foundation, the Yrjö Johansson Foundation, the Finnish Diabetes Research Foundation, the Reino Lahtikari Foundation, the European Commission (Persistent Virus Infection in Diabetes Network [PEVNET] Frame Programme 7, contract number 261441) and the Paulo Foundation.
The datasets analysed during the current study are included in this published article and its supplementary information files (www.btk.fi/research/computational-biomedicine/1234-2) or are available from the GEO repository (accession GSE30211).
© The Author(s) 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.