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J Infect Dis. 2019 Oct 17. pii: jiz531. doi: 10.1093/infdis/jiz531. [Epub ahead of print]

Immune predictors of mortality following RNA virus infection.

Author information

1
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
2
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.
3
Department of Microbiology and Immunology, University of Texas Medical Center, Galveston, TX.
4
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC.
5
Center for Innate Immunity and Immune Disease, Department of Immunology, University of Washington School of Medicine, Seattle, WA.
6
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR.
7
OHSU Knight Cancer Institute, Oregon Health & Science University, Portland, O.
8
Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, O.
9
Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC.
10
Department of Global Health, University of Washington, Seattle, WA.

Abstract

BACKGROUND:

Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines, as well as the early identification of individuals with the highest risk that may require supportive treatment.

METHODS:

We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, SARS-coronavirus, and West Nile virus.

RESULTS:

CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality following infection and strains exhibiting no mortality. We then used comprehensive pre-infection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection.

CONCLUSIONS:

These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design.

KEYWORDS:

Collaborative cross; RNA virus infection; immune correlates of mortality

PMID:
31621854
DOI:
10.1093/infdis/jiz531

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