Evaluation of serum and urine biomarkers for severe COVID-19 - Shansky, Yaroslav D.; Yanushevich, Oleg O.; Gospodarik, Alina V.; Maev, Igor V.; Krikheli, Natella I.; Levchenko, Oleg V.; Zaborovsky, Andrew V.; Evdokimov, Vladimir V.; Solodov, Alexander A.; Bely, Petr A.; Andreev, Dmitry N.; Serkina, Anna N.; et al. (Frontiers in Medicine, 2024)
Introduction: The new coronavirus disease, COVID-19, poses complex challenges exacerbated by several factors, with respiratory tissue lesions being notably significant among them. Consequently, there is a pressing need to identify informative biological markers that can indicate the severity of the disease. Several studies have highlighted the involvement of proteins such as APOA1, XPNPEP2, ORP150, CUBN, HCII, and CREB3L3 in these respiratory tissue lesions. However, there's a lack of information regarding antibodies to these proteins in the human body, which could potentially serve as valuable diagnostic markers for COVID-19. Simultaneously, it is relevant to select biological fluids that can be obtained without invasive procedures. Urine is one such fluid, but its effect on clinical laboratory analysis is not yet fully understood due to insufficient study of its composition. Methods: total serum protein analysis; ELISA on moderate and severe COVID-19 patients' serum and urine; bioinformatic methods: ROC analysis, PCA, SVM. Results and discussion: The levels of anti-APOA1, anti-XPNPEP2, anti-ORP150, anti-CUBN, anti-HCII, and anti-CREB3L3 exhibit gradual fluctuations ranging from moderate to severe in both the serum and urine of COVID-19 patients. However, the diagnostic value of individual anti-protein antibodies is low, in both blood serum and urine. On the contrary, joint detection of these antibodies in patients’ serum significantly increase the diagnostic value, as demonstrated by results of principal component analysis (PCA) and support vector machine (SVM). The non-linear regression model achieved an accuracy of 0.833. Furthermore, PCA aided in identifying serum protein markers that have the greatest impact on patient groups discrimination. The study revealed that serum serves as a superior analyte for describing protein quantification due to its consistent composition and lack of organic salts and drug residues, which can otherwise affect the protein stability.