COV50, a urinary proteomic classifier, predicts disease progression and death from SARS-CoV-2 at early stage, suggesting it might predict pre-established vulnerability. This study investigated the value of COV50 in predicting non-COVID-19 associated death. Urinary proteomic data were extracted from the Human Urinary Proteome Database. In the ICU group (n=1719), an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death (adj. HR 1.2 [95% CI 1.17-1.24]). The same increase in COV50 in non-ICU patients (n=7474) resulted in a higher relative risk of 61% (adj. HR 1.61 [95% CI 1.47-1.76]), in line with adjusted meta-analytic HR estimate of 1.55. A higher COV50 scoring was observed in frail patients (p<0.0001). The COV50 classifier is predictive of death, and is associated with frailty suggesting that it detects pre-existing vulnerability. These data may serve as basis for proteomics guided intervention, reducing the risk of death and frailty.

HM is the cofounder and co-owner of Mosaiques Diagnostics (Hannover, Germany) and AL, MM, and JS are employees of Mosaiques Diagnostics. PP is also employed by Delta4 GmbH. AM reports grants or contracts from 4TEEN4, Abbott, Roche and Sphyngotec, and consulting fees from Roche, Adrenomed, Corteria, Fire1 and payment or honoraria from Merc and Novartis. All other authors declare no competing interests.

This work was supported in part by funding through the European Union Horizon Europe Marie Skłodowska Curie Actions Doctoral Networks Industrial Doctorates Programme (HORIZON MSCA 2021 DNID, DisCoI, grant agreement No 101072828) to AL, AV, JPS and HM.

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