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Correlates of disease severity in bluetongue as a model of acute arbovirus infection.

Authors :
Herder V
Caporale M
MacLean OA
Pintus D
Huang X
Nomikou K
Palmalux N
Nichols J
Scivoli R
Boutell C
Taggart A
Allan J
Malik H
Ilia G
Gu Q
Ronchi GF
Furnon W
Zientara S
Bréard E
Antonucci D
Capista S
Giansante D
Cocco A
Mercante MT
Di Ventura M
Da Silva Filipe A
Puggioni G
Sevilla N
Stewart ME
Ligios C
Palmarini M
Source :
PLoS pathogens [PLoS Pathog] 2024 Aug 16; Vol. 20 (8), pp. e1012466. Date of Electronic Publication: 2024 Aug 16 (Print Publication: 2024).
Publication Year :
2024

Abstract

Most viral diseases display a variable clinical outcome due to differences in virus strain virulence and/or individual host susceptibility to infection. Understanding the biological mechanisms differentiating a viral infection displaying severe clinical manifestations from its milder forms can provide the intellectual framework toward therapies and early prognostic markers. This is especially true in arbovirus infections, where most clinical cases are present as mild febrile illness. Here, we used a naturally occurring vector-borne viral disease of ruminants, bluetongue, as an experimental system to uncover the fundamental mechanisms of virus-host interactions resulting in distinct clinical outcomes. As with most viral diseases, clinical symptoms in bluetongue can vary dramatically. We reproduced experimentally distinct clinical forms of bluetongue infection in sheep using three bluetongue virus (BTV) strains (BTV-1IT2006, BTV-1IT2013 and BTV-8FRA2017). Infected animals displayed clinical signs varying from clinically unapparent, to mild and severe disease. We collected and integrated clinical, haematological, virological, and histopathological data resulting in the analyses of 332 individual parameters from each infected and uninfected control animal. We subsequently used machine learning to select the key viral and host processes associated with disease pathogenesis. We identified and experimentally validated five different fundamental processes affecting the severity of bluetongue: (i) virus load and replication in target organs, (ii) modulation of the host type-I IFN response, (iii) pro-inflammatory responses, (iv) vascular damage, and (v) immunosuppression. Overall, we showed that an agnostic machine learning approach can be used to prioritise the different pathogenetic mechanisms affecting the disease outcome of an arbovirus infection.<br />Competing Interests: The authors have declared that no competing interests exist.<br /> (Copyright: © 2024 Herder et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Details

Language :
English
ISSN :
1553-7374
Volume :
20
Issue :
8
Database :
MEDLINE
Journal :
PLoS pathogens
Publication Type :
Academic Journal
Accession number :
39150989
Full Text :
https://doi.org/10.1371/journal.ppat.1012466