{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:42:35Z","timestamp":1760146955496,"version":"build-2065373602"},"reference-count":68,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,22]],"date-time":"2024-12-22T00:00:00Z","timestamp":1734825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Generalitat Valenciana","award":["ACIF\/2021\/298"],"award-info":[{"award-number":["ACIF\/2021\/298"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has spurred an extraordinary scientific effort to better understand the disease\u2019s pathophysiology and develop diagnostic and prognostic tools to guide more precise and effective clinical management. Among the biological samples analyzed for biomarker identification, urine stands out due to its low risk of infection, non-invasive collection, and suitability for frequent, large-volume sampling. Integrating data from omics studies with standard biochemical analyses offers a deeper and more comprehensive understanding of COVID-19. This review aims to provide a detailed summary of studies published to date that have applied omics and clinical analyses on urine samples to identify potential biomarkers for COVID-19. In July 2024, an advanced search was conducted in Web of Science using the query: \u201ccovid* (Topic) AND urine (Topic) AND metabol* (Topic)\u201d. The search included results published up to 14 October 2024. The studies retrieved from this digital search were evaluated through a two-step screening process: first by reviewing titles and abstracts for eligibility, and then by retrieving and assessing the full texts of articles that met the specific criteria. The initial search retrieved 913 studies, of which 45 articles were ultimately included in this review. The most robust biomarkers identified include kynurenine, neopterin, total proteins, red blood cells, ACE2, citric acid, ketone bodies, hypoxanthine, amino acids, and glucose. The biological causes underlying these alterations reflect the multisystemic impact of COVID-19, highlighting key processes such as systemic inflammation, renal dysfunction, critical hypoxia, and metabolic stress.<\/jats:p>","DOI":"10.3390\/metabo14120724","type":"journal-article","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T10:58:55Z","timestamp":1734951535000},"page":"724","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Diagnosis, Severity, and Prognosis from Potential Biomarkers of COVID-19 in Urine: A Review of Clinical and Omics Results"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0160-8312","authenticated-orcid":false,"given":"Jennifer","family":"Narro-Serrano","sequence":"first","affiliation":[{"name":"Department of Physical Chemistry, University of Alicante, 03690 Alicante, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0402-9770","authenticated-orcid":false,"given":"Frutos Carlos","family":"Marhuenda-Egea","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology and Soil Science and Agricultural Chemistry, University of Alicante, 03690 Alicante, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"m1328","DOI":"10.1136\/bmj.m1328","article-title":"Prediction models for diagnosis and prognosis of COVID-19: Systematic review and critical appraisal","volume":"369","author":"Wynants","year":"2020","journal-title":"BMJ"},{"key":"ref_2","first-page":"20","article-title":"COVID-19 pandemic: From origins to outcomes. 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