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.

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.

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.

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.

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).