{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T04:58:58Z","timestamp":1781240338242,"version":"3.54.1"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Renal transplant patients (RTPs) receiving immunomodulatory therapy are at increased risk of severe complications from COVID-19 and other infections. This study aimed to identify immune and proteomic biomarkers associated with COVID-19 in RTPs to improve disease characterization and support future diagnostic and therapeutic strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Peripheral blood samples from RTPs with COVID-19 infection, uninfected RTPs, and healthy controls were analyzed using cytokine gene expression profiling and label-free global quantitative proteomics. Differential cytokine expression and proteomic alterations were evaluated across study groups and according to disease severity and recovery status.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Cytokine levels differed significantly between healthy controls and COVID-19-affected RTPs (p = 0.04), whereas no significant difference was observed between healthy controls and uninfected RTPs (p = 0.92). Within the RTP-COVID group, cytokine expression varied according to disease severity (p = 0.04) but not between acute and recovery phases (p = 0.39). Proteomic profiling identified eighteen altered protein targets. Eight proteins (SERPINF2, SAA1, HP, PLG, SERPINA3, CFHR1, HRG, and C4A) were associated with RTP-COVID and may represent candidate biomarkers of COVID-19 risk in RTPs. Ten proteins (PLXNA2, CP, A2M, KNG1, CLU, SERPINA5, APOA4, ITIH2, ITIH1, and VTN) were uniquely differentially expressed between RTPs and healthy controls but not between RTP-COVID patients and controls.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These findings provide preliminary insights into immune and proteomic dysregulation associated with COVID-19 in RTPs and identify potential biomarker candidates for disease risk and severity assessment. However, the small sample size and inclusion of only surviving patients limit the generalizability of the findings. Validation in larger and more diverse cohorts is warranted.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1687147","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T04:45:24Z","timestamp":1781239524000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive biomarkers of COVID-19 impact in renal transplant patients: an exploratory proteomic and cytokine analysis"],"prefix":"10.3389","volume":"17","author":[{"given":"Ayodele","family":"Alaiya","sequence":"first","affiliation":[{"name":"Biomarker Innovation for Clinical Applications, Research Laboratories Department","place":["Riyadh, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maha","family":"Al-Mozaini","sequence":"additional","affiliation":[{"name":"Research Laboratories Department","place":["Riyadh, Saudi 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