10779/crick.12739175.v1 Christoph B Messner Christoph B Messner Vadim Demichev Vadim Demichev Daniel Wendisch Daniel Wendisch Laura Michalick Laura Michalick Matthew White Matthew White Anja Freiwald Anja Freiwald Kathrin Textoris-Taube Kathrin Textoris-Taube Spyros I Vernardis Spyros I Vernardis Anna-Sophia Egger Anna-Sophia Egger Marco Kreidl Marco Kreidl Daniela Ludwig Daniela Ludwig Christiane Kilian Christiane Kilian Federica Agostini Federica Agostini Aleksej Zelezniak Aleksej Zelezniak Charlotte Thibeault Charlotte Thibeault Moritz Pfeiffer Moritz Pfeiffer Stefan Hippenstiel Stefan Hippenstiel Andreas Hocke Andreas Hocke Christof von Kalle Christof von Kalle Archie Campbell Archie Campbell Caroline Hayward Caroline Hayward David J Porteous David J Porteous Riccardo E Marioni Riccardo E Marioni Claudia Langenberg Claudia Langenberg Kathryn S Lilley Kathryn S Lilley Wolfgang M Kuebler Wolfgang M Kuebler Michael Mülleder Michael Mülleder Christian Drosten Christian Drosten Norbert Suttorp Norbert Suttorp Martin Witzenrath Martin Witzenrath Florian Kurth Florian Kurth Leif Erik Sander Leif Erik Sander Markus Ralser Markus Ralser Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection The Francis Crick Institute 2020 COVID-19 infection SWATH-MS antiviral immune response clinical classifiers high-throughput proteomics mass spectrometry Ralser FC001134 2020-07-30 13:14:00 Journal contribution https://crick.figshare.com/articles/journal_contribution/Ultra-high-throughput_clinical_proteomics_reveals_classifiers_of_COVID-19_infection/12739175 The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.