Multiomics analysis unveils key biomarkers during dynamic progress of IAV infection in mice

IntroductionInfluenza infection is a significant threat to public health, and identifying dynamic biomarkers that influence disease progression is crucial for effective intervention.MethodsWe conducted a comprehensive evaluation of physiological and pathological parameters in Balb/c mice infected wi...

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Main Authors: Huan Lei, Yixi Xu, Hao Zhang, Bin Zhang, Wenjun Luo, Xiao Liu, Haijun Zhang, Jinming Yang, Wen Wen, Ping Wang, Shijun Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Immunology
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Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1566690/full
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Summary:IntroductionInfluenza infection is a significant threat to public health, and identifying dynamic biomarkers that influence disease progression is crucial for effective intervention.MethodsWe conducted a comprehensive evaluation of physiological and pathological parameters in Balb/c mice infected with H1N1 influenza over a 14-day period. We employed the DIABLO multi-omics integration method to analyze dynamic changes in the lung transcriptome, metabolome, and serum metabolome from mild to severe stages of infection.ResultsOur analysis highlighted the critical importance of intervention within the first 6 days post-infection to prevent severe disease. We identified several novel biomarkers associated with disease progression, including Ccl8, Pdcd1, Gzmk, kynurenine, L-glutamine, and adipoyl-carnitine. Additionally, we developed a serum-based influenza disease progression scoring system.DiscussionThis study provides new insights into the molecular mechanisms underlying influenza progression and identifies potential targets for therapeutic intervention. The developed scoring system serves as a valuable tool for early diagnosis and prognosis of severe influenza.
ISSN:1664-3224