Soroosh Najafi, Maryam Jojani, Kianoosh Najafi, Giovanni N Roviello
Hantaviruses are zoonotic RNA viruses responsible for two severe human diseases: hemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS). Worldwide case fatality rates vary from 1% to 40%. Although single-layer genomics, transcriptomics, proteomics, and metabolomics studies have advanced our understanding of hantavirus biology, true multi-omics integration remains scarce, leaving systems-level mechanisms of disease severity and host-pathogen interactions unresolved. High-throughput omics technologies have greatly advanced the study of hantavirus-host interactions. This review summarizes genomic, transcriptomic, proteomic, metabolomic, and AI-enabled approaches in hantavirus research. Genomic studies have clarified viral diversity, evolution, and reassortment, while transcriptomics has identified regulatory networks governing endothelial and innate immune responses. Proteomics has revealed host proteins involved in immune regulation, endothelial dysfunction, and potential therapeutic targeting, whereas metabolomics indicates substantial metabolic reprogramming during infection, although dedicated studies remain limited. AI-based approaches are increasingly applied to outbreak prediction, surveillance, and risk modeling. Drawing on successful multi-omics frameworks developed for other viral infections, we discuss opportunities to improve biomarker discovery, surveillance, therapeutic development, and future precision medicine strategies for hantavirus infections.