TY - JOUR T1 - A serum proteome signature to predict mortality in severe COVID-19 patients JF - Life Science Alliance JO - Life Sci. Alliance DO - 10.26508/lsa.202101099 VL - 4 IS - 9 SP - e202101099 AU - Franziska Völlmy AU - Henk van den Toorn AU - Riccardo Zenezini Chiozzi AU - Ottavio Zucchetti AU - Alberto Papi AU - Carlo Alberto Volta AU - Luisa Marracino AU - Francesco Vieceli Dalla Sega AU - Francesca Fortini AU - Vadim Demichev AU - Pinkus Tober-Lau AU - Gianluca Campo AU - Marco Contoli AU - Markus Ralser AU - Florian Kurth AU - Savino Spadaro AU - Paola Rizzo AU - Albert JR Heck Y1 - 2021/09/01 UR - https://www.life-science-alliance.org/content/4/9/e202101099.abstract 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. ER -