Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Yvonne M. Mueller, Thijs J. Schrama, Rik Ruijten, Marco W. J. Schreurs, Dwin G. B. Grashof, Harmen J. G. van de Werken, Giovanna Jona Lasinio, Daniel Álvarez-Sierra, Caoimhe H. Kiernan, Melisa D. Castro Eiro, Marjan van Meurs, Inge Brouwers-Haspels, Manzhi Zhao, Ling Li, Harm de Wit, Christos A. Ouzounis, Merel E. P. Wilmsen, Tessa M. Alofs, Danique A. Laport, Tamara van Wees, Geoffrey Kraker, Maria C. Jaimes, Sebastiaan Van Bockstael, Manuel Hernández-González, Casper Rokx, Bart J. A. Rijnders, Ricardo Pujol-Borrell and Peter D. Katsikis ()
Additional contact information
Yvonne M. Mueller: Erasmus University Medical Center
Thijs J. Schrama: Erasmus University Medical Center
Rik Ruijten: Erasmus University Medical Center
Marco W. J. Schreurs: Erasmus University Medical Center
Dwin G. B. Grashof: Erasmus University Medical Center
Harmen J. G. van de Werken: Erasmus University Medical Center
Giovanna Jona Lasinio: University of Rome “La Sapienza”
Daniel Álvarez-Sierra: Hospital Universitari Vall d’Hebron, Campus Vall d’Hebron
Caoimhe H. Kiernan: Erasmus University Medical Center
Melisa D. Castro Eiro: Erasmus University Medical Center
Marjan van Meurs: Erasmus University Medical Center
Inge Brouwers-Haspels: Erasmus University Medical Center
Manzhi Zhao: Erasmus University Medical Center
Ling Li: Erasmus University Medical Center
Harm de Wit: Erasmus University Medical Center
Christos A. Ouzounis: Aristotle University of Thessaloniki
Merel E. P. Wilmsen: Erasmus University Medical Center
Tessa M. Alofs: Erasmus University Medical Center
Danique A. Laport: Erasmus University Medical Center
Tamara van Wees: Erasmus University Medical Center
Geoffrey Kraker: Cytek Biosciences
Maria C. Jaimes: Cytek Biosciences
Sebastiaan Van Bockstael: Cytek Biosciences
Manuel Hernández-González: Hospital Universitari Vall d’Hebron, Campus Vall d’Hebron
Casper Rokx: Erasmus University Medical Center
Bart J. A. Rijnders: Erasmus University Medical Center
Ricardo Pujol-Borrell: Hospital Universitari Vall d’Hebron, Campus Vall d’Hebron
Peter D. Katsikis: Erasmus University Medical Center

Nature Communications, 2022, vol. 13, issue 1, 1-13

Abstract: Abstract Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient’s immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy.

Date: 2022
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DOI: 10.1038/s41467-022-28621-0

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