{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T12:31:12Z","timestamp":1775910672227,"version":"3.50.1"},"reference-count":57,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T00:00:00Z","timestamp":1732752000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Proteomics Clinical Apps"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>Coronary artery disease (CAD) is a major cause of morbidity and mortality worldwide. This underlines the urgent need for effective biomarkers for early diagnosis, risk stratification, and therapeutic counseling. Proteomic signatures from plasma and urine have emerged as promising tools for these efforts, each offering unique advantages and challenges. This review provides a detailed comparison of urine and blood proteomic analyzes in the context of CAD and explores their respective advantages and limitations. Urine proteomics offers a minimally invasive, easily repeatable, and temporally stable sampling method, but faces challenges such as lower protein concentrations and potential contamination. Despite its invasive nature, blood proteomics captures high protein concentration and directly reflects systemic physiological changes, making it valuable for acute assessments. Advances in artificial intelligence (AI) have significantly improved the analysis and interpretation of proteomic data, enabling greater accuracy in diagnosis and predictive modeling. AI algorithms, particularly in pattern recognition and data integration, are helping to uncover subtle relationships between biomarkers and disease progression and supporting the discovery of plasma\u2010 and urine\u2010based CAD biomarkers. This review demonstrates the potential of combining urine and blood proteomic data using AI to advance personalized approaches in CAD diagnosis and treatment. Future research should focus on standardization of collection protocols, validation of biomarkers in different populations, and the complexity of integrating data from different sources to maximize the potential of proteomics in the treatment of CAD.<\/jats:p>","DOI":"10.1002\/prca.202400062","type":"journal-article","created":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T09:24:08Z","timestamp":1732785848000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Minimally Invasive Versus Invasive Proteomics: Urine and Blood Biomarkers in Coronary Artery Disease"],"prefix":"10.1002","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3636-5805","authenticated-orcid":false,"given":"Rui","family":"Vitorino","sequence":"first","affiliation":[{"name":"Department of Medical Sciences Institute of Biomedicine iBiMED University of Aveiro  Aveiro Portugal"},{"name":"Cardiovascular R&amp;D Centre \u2010 UnIC@RISE, Department of Surgery and Physiology Faculty of Medicine of the University of Porto  Porto Portugal"}]}],"member":"311","published-online":{"date-parts":[[2024,11,28]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.52711\/jnmr.2023.07"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcp.28350"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCRESAHA.115.306566"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.5551\/jat.25478"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.52547\/rbmb.10.2.302"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2018.01.007"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-2517-9_1"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.4330\/wjc.v8.i1.1"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpcardiol.2017.04.005"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.104992"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCIMAGING.115.003533"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/3429541"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep28042"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurjpc\/zwad087"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1074\/mcp.M700394-MCP200"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2018.12.033"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12933-018-0697-9"},{"key":"e_1_2_9_19_1","first-page":"130","article-title":"A Diagnostic Algorithm Combining Clinical and Molecular Data Distinguishes Kawasaki Disease From Other Febrile Illnesses","volume":"9","author":"Ling X. 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