Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning
| العنوان: | Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning |
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| المؤلفون: | Mueller, Yvonne M., Schrama, Thijs J., Ruijten, Rik, Schreurs, Marco W. J., Grashof, Dwin G. B., van de Werken, Harmen J. G., Lasinio, Giovanna Jona, Álvarez-Sierra, Daniel, Kiernan, Caoimhe H., Castro Eiro, Melisa D., van Meurs, Marjan, Brouwers-Haspels, Inge, Zhao, Manzhi, Li, Ling, de Wit, Harm, Ouzounis, Christos A., Wilmsen, Merel E. P., Alofs, Tessa M., Laport, Danique A., van Wees, Tamara, Kraker, Geoffrey, Jaimes, Maria C., Van Bockstael, Sebastiaan, Hernández-González, Manuel, Rokx, Casper, Rijnders, Bart J. A., Pujol-Borrell, Ricardo, Katsikis, Peter D., Universitat Autònoma de Barcelona |
| المساهمون: | Institut Català de la Salut, [Mueller YM, Schrama TJ, Ruijten R, Schreurs MWJ, Grashof DGB] Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands. [van de Werken HJG] Department of Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands. Cancer Computational Biology Center, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands. [Álvarez-Sierra D] Servei d’Immunologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Hernández-González M] Servei d’Immunologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Departament de Biologia Cel•lular, Fisiologia i Immunologia, Universitat Autònoma de Barcelona, Bellaterra, Spain. Grup de Recerca en Immunologia Translacional, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. [Pujol-Borrell R] Servei d’Immunologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Departament de Biologia Cel•lular, Fisiologia i Immunologia, Universitat Autònoma de Barcelona, Bellaterra, Spain. Grup de Recerca en Immunologia Translacional, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain, Vall d'Hebron Barcelona Hospital Campus, Immunology, Cell biology, Internal Medicine, Medical Microbiology & Infectious Diseases |
| المصدر: | Scientia Nature Communications, 13(1):915. Nature Publishing Group Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Male, machine learning, multinomial regression, immuno-type, covid-19, General Physics and Astronomy, Predictive markers, Antibodies, Viral, Severity of Illness Index, General Biochemistry, Genetics and Molecular Biology, Immunophenotyping, Machine Learning, Applied immunology, virosis::infecciones por virus ARN::infecciones por Nidovirales::infecciones por Coronaviridae::infecciones por Coronavirus [ENFERMEDADES], Coronavirus Nucleocapsid Proteins, Humans, Aged, COVID-19 (Malaltia) - Prognosi, Multidisciplinary, Hospitals - Pacients, SARS-CoV-2, COVID-19, Virus Diseases::RNA Virus Infections::Nidovirales Infections::Coronaviridae Infections::Coronavirus Infections [DISEASES], General Chemistry, Middle Aged, Phosphoproteins, Immunoglobulin A, Hospitalization, Immunoglobulin M, Viral infection, Immunoglobulin G, Computer modelling, Disease Progression, Cytokines, Female |
| الوصف: | Applied immunology; Predictive markers; Viral infection Immunologia aplicada; Marcadors predictius; Infecció viral Inmunología aplicada; Marcadores predictivos; Infección viral 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. This work was supported by Health Holland LSHM20056 grant (PDK), in part from the European Union’s Horizon 2020 research and innovation program under grant agreement No 779295 (PDK), in part supported by the Erasmus foundation (BJAR), grant PI20/00416 from the Instituto de Salud Carlos III (RPB) and the European Regional Development Fund (ERDF) (RPB). |
| وصف الملف: | application/pdf |
| تدمد: | 2041-1723 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76965598bb9dae66e2a700c93f634571Test https://pubmed.ncbi.nlm.nih.gov/35177626Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....76965598bb9dae66e2a700c93f634571 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20411723 |
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