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Evaluating COVID-19 severity prediction and immune dynamics with NULISAseq: Insights from the IMPACC study
Journal article   Open access   Peer reviewed

Evaluating COVID-19 severity prediction and immune dynamics with NULISAseq: Insights from the IMPACC study

Koji Abe, Tyson H Holmes, Tran T Nguyen, Seunghee Kim-Schulze, Ofer Levy, Lindsey R Baden, Esther Melamed, Lauren I R Ehrlich, Grace A McComsey, Rafick P Sekaly, …
The Journal of immunology (1950), Forthcoming
30 Oct 2025
PMID: 41166719
url
https://doi.org/10.1093/jimmun/vkaf263View
Published, Version of Record (VoR) Open

Abstract

viral human Molecular Biology Cytokines Inflammation
The National Institutes of Health-funded IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) evaluated longitudinal clinical and immunological features of human patients hospitalized for COVID-19. This study focuses on comparing the novel NULISAseq assay with the Olink platform using a subset of participants to assess their efficacy in predicting COVID-19 severity and understanding immune response dynamics. Our findings reveal that NULISAseq could provide superior detectability and dynamic range across various targets. Elastic net analysis demonstrated that specific proteins, including amphiregulin, effectively predict COVID-19 severity from sera at admission (samples drawn within 96 h of admission), with a test area under the curve of 0.84. Longitudinal analysis identified significant differences in multiple targets, including IL-5 and interferons, between low- and high-severity groups over time. Additionally, association rule mining suggested potential early markers predictive of later immune cell changes. These findings emphasize the potential of NULISAseq for comprehensive profiling, early prediction, and identification of targeted therapeutic interventions in COVID-19.

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Collaboration types
Domestic collaboration
Web of Science research areas
Immunology
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