Journal of immunology research · 2026
Integration of SFTSV Viral Load, Age, and Double-Negative B-Cells as Prognostic Biomarkers for Severe Fever With Thrombocytopenia Syndrome Outcomes.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wei Wei, Tai Qian, Liu Heng, Chen Rujia, Wang Yun, Wang Ting, Ouyang Renren, Wu Shiji, Wang Feng, Hou Hongyan
Аннотация
BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral illness with high mortality, yet early risk stratification remains challenging. Recent evidence suggests that B-cell dysregulation contributes to disease severity.
METHODS: A cohort of 168 patients with confirmed SFTS was retrospectively analyzed. Flow cytometry was used to quantify B-cell subsets in peripheral blood at admission. Laboratory markers, viral load, and B-cell phenotypes were evaluated for prognostic relevance using univariate and multivariate Cox regression analyses. Receiver operating characteristic (ROC) curves and nomogram models were employed to assess predictive value.
RESULTS: Deceased patients exhibited significantly higher viral loads, elevated proinflammatory cytokines (interleukin-6 (IL-6), IL-10, and tumor necrosis factor-alpha (TNF-α)), and markers of multiorgan dysfunction. Immunophenotyping revealed a reduction in naïve B-cells (IgD+CD27-), alongside expansion of double negative B-cells (DNBs) (IgD-CD27-) in fatal cases. Furthermore, viral load was positively correlated with inflammatory cytokines and dysfunctional B-cell subsets, suggesting that impaired humoral immunity contributes to persistent hyperinflammation in severe SFTS. Multivariate Cox regression analysis identified higher viral load (HR = 2.193, p < 0.001), older age (HR = 1.073, p < 0.001), and increased proportion of DNBs (HR = 1.024, p = 0.035) as independent predictors of 28-day mortality. A combined prognostic model integrating these variables achieved excellent performance (AUC = 0.906, 95% CI: 0.814-0.967), significantly surpassing individual markers and enabling early identification of high-risk SFTS patients.
CONCLUSION: This study demonstrates that integrating B-cell subset profiling with laboratory indicators significantly improves early prognostic assessment in SFTS. These findings provide insights into immune-pathological mechanisms and support timely risk stratification and intervention to reduce mortality.
METHODS: A cohort of 168 patients with confirmed SFTS was retrospectively analyzed. Flow cytometry was used to quantify B-cell subsets in peripheral blood at admission. Laboratory markers, viral load, and B-cell phenotypes were evaluated for prognostic relevance using univariate and multivariate Cox regression analyses. Receiver operating characteristic (ROC) curves and nomogram models were employed to assess predictive value.
RESULTS: Deceased patients exhibited significantly higher viral loads, elevated proinflammatory cytokines (interleukin-6 (IL-6), IL-10, and tumor necrosis factor-alpha (TNF-α)), and markers of multiorgan dysfunction. Immunophenotyping revealed a reduction in naïve B-cells (IgD+CD27-), alongside expansion of double negative B-cells (DNBs) (IgD-CD27-) in fatal cases. Furthermore, viral load was positively correlated with inflammatory cytokines and dysfunctional B-cell subsets, suggesting that impaired humoral immunity contributes to persistent hyperinflammation in severe SFTS. Multivariate Cox regression analysis identified higher viral load (HR = 2.193, p < 0.001), older age (HR = 1.073, p < 0.001), and increased proportion of DNBs (HR = 1.024, p = 0.035) as independent predictors of 28-day mortality. A combined prognostic model integrating these variables achieved excellent performance (AUC = 0.906, 95% CI: 0.814-0.967), significantly surpassing individual markers and enabling early identification of high-risk SFTS patients.
CONCLUSION: This study demonstrates that integrating B-cell subset profiling with laboratory indicators significantly improves early prognostic assessment in SFTS. These findings provide insights into immune-pathological mechanisms and support timely risk stratification and intervention to reduce mortality.