TY - JOUR
T1 - A serum proteome signature to predict mortality in severe COVID-19 patients
AU - Völlmy, Franziska
AU - van den Toorn, Henk
AU - Zenezini Chiozzi, Riccardo
AU - Zucchetti, Ottavio
AU - Papi, Alberto
AU - Volta, Carlo Alberto
AU - Marracino, Luisa
AU - Vieceli Dalla Sega, Francesco
AU - Fortini, Francesca
AU - Demichev, Vadim
AU - Tober-Lau, Pinkus
AU - Campo, Gianluca
AU - Contoli, Marco
AU - Ralser, Markus
AU - Kurth, Florian
AU - Spadaro, Savino
AU - Rizzo, Paola
AU - Heck, Albert Jr
N1 - Funding Information:
We acknowledge support from the Dutch Research Council (NWO) funding the Netherlands Proteomics Centre through the X-omics Road Map program (project 184.034.019) and the EU Horizon 2020 program INFRAIA project Epic-XS (Project 823839).
Publisher Copyright:
© 2021 Vollmy et al.
PY - 2021/9
Y1 - 2021/9
N2 - Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.
AB - Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.
UR - http://www.scopus.com/inward/record.url?scp=85110871838&partnerID=8YFLogxK
U2 - 10.26508/LSA.202101099
DO - 10.26508/LSA.202101099
M3 - Article
C2 - 34226277
SN - 2575-1077
VL - 4
SP - 1
EP - 12
JO - Life Science Alliance
JF - Life Science Alliance
IS - 9
M1 - e202101099
ER -