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Publications

Journal Article Epublish

PubMed: 40278357 DOI: 10.3390/metabo15040228

Metabolic Profiling Reveals Potential Prognostic Biomarkers for SFTS: Insights into Disease Severity and Clinical Outcomes.

Metabolites 15(4)

Authors: Zhuo-Min Zhu, Huan-Yu Liu, Na An, An-Ling Li, Jia Li, Sai-Jun Wang, Gui Yang, Yong-Wei Duan, Ying Yang, Mei Zhang, Quan-Fei Zhu, Song-Mei Liu, Yu-Qi Feng

Affiliations

  • School of Bioengineering and Health, Wuhan Textile University, Wuhan 430200, China. School of Public Health, Wuhan University, Wuhan 430072, China.
  • Department of Clinical Laboratory, Center for Gene Diagnosis & Program of Clinical Laboratory, Zhongnan Hospital of Wuhan University, Wuhan 430071, China. Department of Obstetrics, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
  • Department of Clinical Laboratory, Center for Gene Diagnosis & Program of Clinical Laboratory, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
  • School of Public Health, Wuhan University, Wuhan 430072, China.
  • Department of Clinical Laboratory, Ezhou Hospital of Traditional Chinese Medicine, Ezhou 436000, China.
  • School of Bioengineering and Health, Wuhan Textile University, Wuhan 430200, China.
  • Hubei Province Key Laboratory of Allergy and Immunology, School of Basic Medical Sciences, Wuhan University, Wuhan 430071, China.
  • School of Bioengineering and Health, Wuhan Textile University, Wuhan 430200, China. School of Public Health, Wuhan University, Wuhan 430072, China. Frontier Science Center for Immunology and Metabolism, Wuhan University, Wuhan 430071, China.

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is a viral infection primarily found in Asia, with a case fatality rate of about 10%. Despite its increasing prevalence, the underlying pathogenic mechanisms remain poorly understood, limiting the development of effective therapeutic interventions. We employed an untargeted metabolomics approach using liquid chromatography-mass spectrometry (LC-MS) to analyze serum samples from 78 SFTS patients during the acute phase of their illness. Differential metabolic features between survival and fatal cases were identified through multivariate statistical analysis. Furthermore, we constructed a metabolic prognostic model based on these biomarkers to predict disease severity. Significant alterations were observed in four key metabolic pathways: sphingolipid metabolism, biosynthesis of phenylalanine, tyrosine, and tryptophan, primary bile acid biosynthesis, and phenylalanine metabolism. Elevated levels of phenyllactic acid and isocitric acid were strongly associated with adverse outcomes and demonstrated high discriminatory power in distinguishing fatal cases from survivors. The metabolic prognostic model incorporating these biomarkers achieved a sensitivity of 75% and a specificity of 90% in predicting disease severity. Our findings highlight the pivotal role of metabolic dysregulation in the pathogenesis of SFTS and suggest that targeting specific metabolic pathways could open new avenues for therapeutic development. The identification of prognostic biomarkers provides a valuable tool for early risk stratification and timely clinical intervention, potentially improving patient outcomes.

MeSH

Severe Fever With Thrombocytopenia Syndrome, Phenylalanine, Biomarkers, Metabolomics, Therapeutics