Related Experiment Video
Updated: May 2, 2026

Isolating Human Peripheral Blood Mononuclear Cells and CD4+ T cells from Sézary Syndrome Patients for Transcriptomic Profiling
Published on: October 14, 2021
Two-transcript signature for differentiation and clinical outcomes in severe fever with thrombocytopenia syndrome
Nannan Xu1, Sai Wen1, Yongyuan Yao2
1Department of Infectious Disease, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Abstract:
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with a high mortality rate that is often underdiagnosed due to the limitations of current laboratory testing. Timely diagnosis and early identification of severe cases are crucial to improving patient outcomes and overall survival rates. This study aimed to evaluate the efficacy of two transcripts, IFI44L and PI3, in the early differentiation between SFTS virus (SFTSV) infection and bacterial sepsis, as well as in the prompt identification of severe cases during epidemic seasons. In a prospective study conducted between 1 May 2021 and 30 September 2022, we enrolled 225 patients who presented with acute fever and thrombocytopenia at four hospitals in Shandong Province, China. The two-transcript signature provided a clear distinction between SFTS and bacterial infection, achieving an area under the receiver operating characteristic curve of 0.961 (95% confidence interval [95% CI] 0.916-0.986), outperforming C-reactive protein (0.810 [95% CI 0.738-0.870]) and procalcitonin (0.764 [95% CI 0.687-0.830]). Importantly, the relative expression of the IFI44L gene was significantly elevated in fatal SFTS cases, with an area under the curve (AUC) of 0.820 (95% CI 0.727-0.914), indicating its potential as an early prognostic marker. Additionally, IFI44L and PI3 were identified as potential biomarkers for distinguishing SFTS patients with and without invasive pulmonary aspergillosis, with AUC values of 0.817 and 0.753, respectively. Our findings demonstrate that the two-transcript signature effectively distinguishes SFTSV infection from bacterial sepsis and helps identify high-risk individuals, guiding appropriate treatment during SFTS outbreak.

