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.