Urinary peptides predict future death

Background There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, though the mechanisms that cause this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to already present vulnerabilities. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides. Methods Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated. Results In the ICU group, 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 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. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I(I). Conclusion The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. Prediction is based mainly on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as basis for proteomics guided intervention aiming towards manipulating/improving collagen turnover, thereby reducing the risk of death. ### Competing Interest Statement 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. ### Funding Statement This work was supported in part by funding through the European Union Horizon Europe Marie Sklodowska-Curie Actions Doctoral Networks - Industrial Doctorates Programme (HORIZON-MSCA-2021-DN-ID, DisCo-I, grant No 101072828) to AL, AV, JPS and HM, and in part by BMBF via the Propersis project, grant No 01DN21014 to HM. The funders had no role in the design of the study; collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All datasets were from previously published studies and fully anonymized. Ethical review and approval were waived for this study by the ethics committee of the Hannover Medical School, Germany (no. 3116-2016), due to all data being fully anonymized. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Anonymised data and code used in conducting the analyses will be made available upon request directed to the corresponding author. Proposals will be reviewed and approved by the authors with scientific merit and feasibility as the criteria. After approval of a proposal, data can be shared via a secure online platform after signing a data access and confidentiality agreement. Data will be made available for a maximum of 5 years after a data sharing agreement has been signed * CE-MS : capillary electrophoresis coupled to mass spectrometry ICU : intensive care unit BMI : body mass index eGFR : estimated glomerular filtration rate HR : hazard ratios