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ORIGINAL RESEARCH article

Front. Microbiol.
Sec. Infectious Agents and Disease
Volume 16 - 2025 | doi: 10.3389/fmicb.2025.1514388
This article is part of the Research Topic Diagnosis and Treatment Strategies of Tick-borne Diseases View all 6 articles

Identification of Early Prediction Biomarkers of Severity in Patients With Severe Fever With Thrombocytopenia Syndrome Based on Plasma Proteomics

Provisionally accepted
Qian Zhang Qian Zhang 1,2Zhengyi Jiang Zhengyi Jiang 1*Nan Jiang Nan Jiang 1*Luchen Shi Luchen Shi 1*Jiaying Zhao Jiaying Zhao 1Jie Zhao Jie Zhao 1Ke Ouyang Ke Ouyang 1*Huaying Huang Huaying Huang 1*Yaqin Zhang Yaqin Zhang 1Yan Dai Yan Dai 1Nannan Hu Nannan Hu 1*Ping Shi Ping Shi 1*Yaping Han Yaping Han 1*Ke Jin Ke Jin 1*Jun Li Jun Li 1*
  • 1 First Affiliated Hospital, Nanjing Medical University, Nanjing, China
  • 2 Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, Shanghai, China

The final, formatted version of the article will be published soon.

    Background: Severe fever with thrombocytopenia syndrome (SFTS) is a newly emerging infectious disease. Given its rapid disease progression and high mortality rate, early warning is crucial in improving the outcomes, However, to date, relevant comprehensive predictors or an effective prediction model are still poorly explored.. Methods: A plasma proteomic profile was performed at early stages in patients with SFTS. Functional clustering analysis was used to select the candidate proteins and then validate their expression by ELISA. A cohort consisting of 190 patients with SFTS was used to develop the predictive model for severe illness and subsequently validate it in a new cohort consisting of 93 patients with SFTS.Results: A significant increase in plasma proteins associated with various functional clusters, such as the proteasomal protein catabolic process, phagocytosis, and humoral immune response, was observed in severe SFTS patients. High levels of four proteins including NID1, HSP90α, PSMA1, and VCAM1 were strongly correlated with mutiorgan damage and disease progression. A prediction model was developed at the early stage to accurately predict severe conditions with the area under the curve of 0.931 (95% CI, 0.885, 0.963).The proteomic signatures identified in this study provide insights into the potential pathogenesis of SFTS. The predictive models have substantial clinical implications for the early identification of SFTS patients who may progress to severe conditions.

    Keywords: Severe fever with thrombocytopenia syndrome, Proteomics, biomarker, prediction, prognosis

    Received: 20 Oct 2024; Accepted: 14 Jan 2025.

    Copyright: © 2025 Zhang, Jiang, Jiang, Shi, Zhao, Zhao, Ouyang, Huang, Zhang, Dai, Hu, Shi, Han, Jin and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhengyi Jiang, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Nan Jiang, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Luchen Shi, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Ke Ouyang, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Huaying Huang, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Nannan Hu, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Ping Shi, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Yaping Han, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Ke Jin, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
    Jun Li, First Affiliated Hospital, Nanjing Medical University, Nanjing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.