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

Abstract

INTRODUCTION: Influenza infection is a significant threat to public health, and identifying dynamic biomarkers that influence disease progression is crucial for effective intervention. METHODS: We 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. RESULTS: Our 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, kynurenine, L-glutamine, and adipoyl-carnitine. Additionally, we developed a serum-based influenza disease progression scoring system. DISCUSSION: This 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.