An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.
Author(s)
Type
Journal Article
Abstract
Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.
Date Issued
2022-11-02
Date Acceptance
2022-09-16
Citation
Science Translational Medicine, 2022, 14 (669), pp.1-15
ISSN
1946-6234
Publisher
American Association for the Advancement of Science
Start Page
1
End Page
15
Journal / Book Title
Science Translational Medicine
Volume
14
Issue
669
Copyright Statement
Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works https://www.sciencemag.org/about/science-licenses-journal-article-reuse
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/36322631
Subjects
Adult
Humans
Child
Influenza A Virus, H1N1 Subtype
Gene Expression Profiling
COVID-19
Sepsis
Transcriptome
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2022-11-02