{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T17:22:32Z","timestamp":1791566552879,"version":"4.3.4"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T00:00:00Z","timestamp":1762300800000},"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>Background<\/jats:title>\n                    <jats:p>Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne viral disease associated with high mortality. This study aimed to characterize serum proteomic signatures linked to adverse outcomes and to identify prognostic biomarkers with potential translational value for patient management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Serum samples from 55 survivors, 32 non-survivors, and 10 healthy controls were analyzed by data-independent acquisition\u2013based proteomics. Differential abundance analysis, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein\u2013protein interaction (PPI) network analyses with Markov clustering were conducted to characterize disease-associated proteins. XGBoost and Random Forest machine learning models were applied to prioritize candidate biomarkers, and discriminative performance was evaluated by the receiver operating characteristic (ROC) curve. Spearman correlation analyses were further used to examine associations between candidate proteins, clinical laboratory indicators, and viral load.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Non-survivors exhibited 642 differentially abundant proteins (DAPs) compared with survivors. Functional enrichment and PPI network analyses revealed a proteasome-centered module overrepresented in non-survivors. XGBoost and Random Forest consistently prioritized four candidate biomarkers (PSMD11, IL1RL1, PSMC4, and IFIH1) with areas under the ROC curve of 0.847, 0.847, 0.843, and 0.791, respectively. PSMD11 emerged as the strongest predictor of adverse outcome and showed strong correlations with markers of organ injury and dysfunction such as lactate dehydrogenase (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.77), thrombin time (\n                      <jats:italic>r<\/jats:italic>\n                      =\u00a00.76), aspartate aminotransferase (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.75), hydroxybutyrate dehydrogenase (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.74), viral load (\n                      <jats:italic>r<\/jats:italic>\n                      =\u00a00.63), and platelet count (\n                      <jats:italic>r<\/jats:italic>\n                      = \u22120.57) (all\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study identified a proteasome-centered signature associated with adverse outcomes in SFTS, with PSMD11 emerging as a key prognostic biomarker. Its strong correlations with viral load and multi-organ injury support potential utility for early risk stratification and prognostic prediction, while also providing mechanistic insights into disease progression and a foundation for future translational research and therapeutic development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1693946","type":"journal-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:25:37Z","timestamp":1762323937000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Serum proteomics and machine learning identify PSMD11 as a prognostic biomarker in severe fever with thrombocytopenia syndrome"],"prefix":"10.3389","volume":"16","author":[{"given":"Chenxi","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziruo","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ranran","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingyu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhouling","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,5]]},"reference":[{"key":"B1","unstructured":"Taxon Details | ICTV"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1010095","article-title":"Fever with thrombocytopenia associated with a novel bunyavirus in China","volume":"364","author":"Yu","year":"2011","journal-title":"N Engl J Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3201\/eid1911.130792","article-title":"Severe fever with thrombocytopenia syndrome, South Korea, 2012","volume":"19","author":"Kim","year":"2013","journal-title":"Emerg Infect Dis"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1093\/infdis\/jit603","article-title":"The first identification and retrospective study of severe fever with thrombocytopenia syndrome in Japan","volume":"209","author":"Takahashi","year":"2014","journal-title":"J Infect Dis"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.3201\/eid2505.181463","article-title":"Endemic severe fever with thrombocytopenia syndrome, Vietnam","volume":"25","author":"Tran","year":"2019","journal-title":"Emerg Infect Dis"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3201\/eid2812.221183","article-title":"Severe fever with thrombocytopenia syndrome virus infection, Thailand, 2019\u20132020","volume":"28","author":"Rattanakomol","year":"2022","journal-title":"Emerg Infect Dis"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.3201\/eid2607.190611","article-title":"Serologic evidence of severe fever with thrombocytopenia syndrome virus and related viruses in Pakistan","volume":"26","author":"Zohaib","year":"2020","journal-title":"Emerg Infect Dis"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(18)30293-7","article-title":"Epidemiological and clinical features of laboratory-diagnosed severe fever with thrombocytopenia syndrome in China, 2011\u201317: a prospective observational study","volume":"18","author":"Li","year":"2018","journal-title":"Lancet Infect Dis"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1016\/j.lanwpc.2024.101133","article-title":"Global epidemiology of severe fever with thrombocytopenia syndrome virus in human and animals: a systematic review and meta-analysis","volume":"48","author":"Cui","year":"2024","journal-title":"Lancet Reg Health West Pac"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2025.1566719","article-title":"Case Report: Successful treatment of severe fever with thrombocytopenia syndrome associated with hemophagocytic lymphohistiocytosis by preemptively using favipiravir and methylprednisolone","volume":"12","author":"Qiao","year":"2025","journal-title":"Front Med"},{"key":"B11","doi-asserted-by":"publisher","first-page":"e0013279","DOI":"10.1371\/journal.pntd.0013279","article-title":"Re-evaluating a single-arm trial of favipiravir for severe fever with thrombocytopenia syndrome in Japan: A proposal to use real-world data as external controls","volume":"19","author":"Kubo","year":"2025","journal-title":"PloS Negl Trop Dis"},{"key":"B12","unstructured":"Pathogens prioritization: a scientific framework for epidemic and pandemic research preparedness"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmi.2024.01.009","article-title":"Severe fever with thrombocytopenia syndrome complicated by haemophagocytic lymphohistiocytosis: a retrospective cohort study","volume":"30","author":"Wang","year":"2024","journal-title":"Clin Microbiol Infect"},{"key":"B14","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1186\/s12985-024-02403-0","article-title":"Cytokines and lymphocyte subsets are associated with disease severity of severe fever with thrombocytopenia syndrome","volume":"21","author":"Song","year":"2024","journal-title":"Virol J"},{"key":"B15","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1093\/infdis\/jiae039","article-title":"Identification of CCL20 as a prognostic predictor for severe fever with thrombocytopenia syndrome based on plasma proteomics","volume":"230","author":"Zhang","year":"2024","journal-title":"J Infect Dis"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbadis.2024.167337","article-title":"Harnessing high-throughput OMICS in emerging zoonotic virus preparedness and response activities","volume":"1870","author":"Loeb","year":"2024","journal-title":"Biochim Biophys Acta Mol Basis Dis"},{"key":"B17","doi-asserted-by":"publisher","first-page":"e315","DOI":"10.1002\/mco2.315","article-title":"Applications of multi-omics analysis in human diseases","volume":"4","author":"Chen","year":"2023","journal-title":"MedComm"},{"key":"B18","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/j.cell.2021.01.004","article-title":"Multi-organ proteomic landscape of COVID-19 autopsies","volume":"184","author":"Nie","year":"2021","journal-title":"Cell"},{"key":"B19","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.cell.2020.05.032","article-title":"Proteomic and metabolomic characterization of COVID-19 patient sera","volume":"182","author":"Shen","year":"2020","journal-title":"Cell"},{"key":"B20","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.bsheal.2023.01.002","article-title":"Towards precision medicine: Omics approach for COVID-19","volume":"5","author":"Cen","year":"2023","journal-title":"Biosaf Health"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1016\/j.bioteChadv.2021.107739","article-title":"Using machine learning approaches for multi-omics data analysis: A review","volume":"49","author":"Reel","year":"2021","journal-title":"Biotechnol Adv"},{"key":"B22","doi-asserted-by":"publisher","first-page":"6236","DOI":"10.1038\/s41598-023-31850-y","article-title":"Circulating proteins to predict COVID-19 severity","volume":"13","author":"Su","year":"2023","journal-title":"Sci Rep"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.1012824","article-title":"Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection","volume":"13","author":"Boada","year":"2022","journal-title":"Front Immunol"},{"key":"B24","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1002\/rmv.1776","article-title":"Systematic review of severe fever with thrombocytopenia syndrome:virology, epidemiology, and clinical characteristics","volume":"24","author":"Liu","year":"2014","journal-title":"Rev Med Virol"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbab460","article-title":"Machine learning meets omics: applications and perspectives","volume":"23","author":"Li","year":"2022","journal-title":"Brief Bioinform"},{"key":"B26","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1186\/s12879-025-10900-y","article-title":"Clinical characteristics and outcomes of disseminated intravascular coagulation in patients with severe fever with thrombocytopenia syndrome","volume":"25","author":"Zhang","year":"2025","journal-title":"BMC Infect Dis"},{"key":"B27","doi-asserted-by":"publisher","first-page":"e0010489","DOI":"10.1371\/journal.pntd.0010489","article-title":"Clinical laboratory parameters and fatality of Severe fever with thrombocytopenia syndrome patients: A systematic review and meta-analysis","volume":"16","author":"Wang","year":"2022","journal-title":"PloS Negl Trop Dis"},{"key":"B28","doi-asserted-by":"publisher","first-page":"1509","DOI":"10.1097\/CCM.0000000000006367","article-title":"The association between elevated myocardial injury-related biomarker (TnI) and increased mortality in patients with severe fever with thrombocytopenia syndrome*","volume":"52","author":"Liang","year":"2024","journal-title":"Crit Care Med"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.3390\/tropicalmed10070193","article-title":"Prediction of mortality by clinical laboratory parameters in severe fever with thrombocytopenia syndrome: A meta-analysis","volume":"10","author":"Yan","year":"2025","journal-title":"Trop Med Infect Dis"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1080\/21505594.2025.2520343","article-title":"Bandavirus dabieense: A review of epidemiology, clinical characteristics, pathophysiology, treatment and prevention","volume":"16","author":"Peng","year":"2025","journal-title":"Virulence"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1522332112","article-title":"cAMP-induced phosphorylation of 26S proteasomes on Rpn6\/PSMD11 enhances their activity and the degradation of misfolded proteins","volume":"112","author":"Lokireddy","year":"2015","journal-title":"Proc Natl Acad Sci U.S.A"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1038\/nature11468","article-title":"Increased proteasome activity determines human embryonic stem cell identity","volume":"489","author":"Vilchez","year":"2012","journal-title":"Nature"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1016\/j.molmed.2024.10.006","article-title":"Promoting proteostasis by cAMP\/PKA and cGMP\/PKG","volume":"31","author":"Ahammed","year":"2025","journal-title":"Trends Mol Med"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2024.05.016","article-title":"PSMD11 loss-of-function variants correlate with a neurobehavioral phenotype, obesity, and increased interferon response","volume":"111","author":"Deb","year":"2024","journal-title":"Am J Hum Genet"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1042\/BSR20191455","article-title":"MicroRNA-451 inhibits inflammation and proliferation of glomerular mesangial cells through down-regulating PSMD11 and NF-\u03baB p65","volume":"39","author":"Wei","year":"2019","journal-title":"Biosci Rep"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms11730","article-title":"Long noncoding RNA NRON contributes to HIV-1 latency by specifically inducing tat protein degradation","volume":"7","author":"Li","year":"2016","journal-title":"Nat Commun"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1355","DOI":"10.1002\/mc.23568","article-title":"An integrative analysis reveals the prognostic value and potential functions of PSMD11 in hepatocellular carcinoma","volume":"62","author":"Zhang","year":"2023","journal-title":"Mol Carcinog"},{"key":"B38","doi-asserted-by":"publisher","first-page":"e7379","DOI":"10.1002\/cam4.7379","article-title":"Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression","volume":"13","author":"Huang","year":"2024","journal-title":"Cancer Med"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2025.1555649","article-title":"PSMD11 and PSMD14 may serve as novel biomarkers for the prognosis of pancreatic ductal adenocarcinoma","volume":"15","author":"Yang","year":"2025","journal-title":"Front Oncol"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1080\/08941939.2020.1863527","article-title":"Prognostic value and molecular mechanisms of proteasome 26S subunit, non-ATPase family genes for pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy","volume":"35","author":"Zhou","year":"2022","journal-title":"J Investig Surg Off J Acad Surg Res"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.3892\/mmr.2019.10314","article-title":"Identification of key candidate genes involved in melanoma metastasis","volume":"20","author":"Chen","year":"2019","journal-title":"Mol Med Rep"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1016\/j.lfs.2024.123125","article-title":"Bortezomib in cancer therapy: Mechanisms, side effects, and future proteasome inhibitors","volume":"358","author":"Sogbein","year":"2024","journal-title":"Life Sci"}],"container-title":["Frontiers in Immunology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1693946\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:25:38Z","timestamp":1762323938000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1693946\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,5]]},"references-count":42,"alternative-id":["10.3389\/fimmu.2025.1693946"],"URL":"https:\/\/doi.org\/10.3389\/fimmu.2025.1693946","relation":{},"ISSN":["1664-3224"],"issn-type":[{"value":"1664-3224","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,5]]},"article-number":"1693946"}}