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

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.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2025-12-01
DOI
https://doi.org/10.1093/jimmun/vkaf263
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Grace A. McComsey, Joann Diray‐Arce, David A. Hafler, Tyson H. Holmes et al.
PubMed
COVID-19 Clinical Research Studies
article

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

Grace A. McComsey, Joann Diray‐Arce, David A. Hafler, Tyson H. Holmes, Lauren I. R. Ehrlich, David J. Erle, Chris Bime, Ruth R. Montgomery, William B. Messer, Esther Melamed, Albert C. Shaw, Bjoern Peters, Kari Christine Nadeau, Andy Nguyễn, Jordan P. Metcalf, Bali Pulendran, Rafick‐Pierre Sékaly, Charles B. Cairns, Nadine Rouphael, Mark Davis, Farrah Kheradmand, Catherine L. Hough, Seunghee Kim‐Schulze, Elaine F. Reed, Mark A. Atkinson, Joanna Schaenman, Carolyn S. Calfee, Monica Kraft, Steven H. Kleinstein, Ofer Levy, Patrice M. Becker, David B. Corry, Ana Fernández-Sesma, Nelson Iván Agudelo Higuita, Al Ozonoff, Scott C. Brakenridge, Alison D. Augustine, Lindsey Robert Baden, Viviana Simon, Elias K. Haddad, Koji Abe
article en

Abstract

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.

PubMedVol. 214(12)
Brigham and Women's Hospital (US), Boston Children's Hospital (US), National Institutes of Health (US), La Jolla Institute for Immunology (US), Harvard University (US), University of Arizona (US), Emory University (US), University of California, Los Angeles (US), Oregon Health & Science University (US), Palo Alto University (US), University of California, San Francisco (US), Baylor College of Medicine (US), University Hospitals of Cleveland (US), Yale University (US), University of Florida (US), National Institute of Allergy and Infectious Diseases (US), OU Health, University of Oklahoma Health Sciences Center (US), Drexel University (US), The University of Texas at Austin (US), Stanford University (US), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 63%
COVID-19 Clinical Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.