Abstract The COVID-19 disease led to an unprecedented health emergency, still ongoing worldwide. Given the lack of a vaccine or a clear therapeutic strategy to counteract the infection as well as its secondary effects, there is currently a pressing need to generate new insights into the SARS-CoV-2 induced host response. Biomedical data can help to investigate new aspects of the COVID-19 pathogenesis, but source heterogeneity represents a major drawback and limitation. In this work, we applied data integration methods to develop a Unified Knowledge Space (UKS) and used it to identify a new set of genes associated with SARS-CoV-2 host response, both in vitro and in vivo. Functional analysis of these genes reveals possible long-term systemic effects of the infection, such as vascular remodelling and fibrosis. Finally, we identified a set of potentially relevant drugs targeting proteins involved in multiple steps of the host response to the virus.
【저자키워드】 COVID-19, SARS-CoV-2, coronavirus, drug repositioning, Data integration, virus–host interaction, unified knowledge space, multi-layer network analysis, drug targeting, 【초록키워드】 Vaccine, Infection, fibrosis, host response, in vitro, virus, heterogeneity, COVID-19 disease, Protein, COVID-19 pathogenesis, in vivo, therapeutic strategy, Analysis, health emergency, Space, help, limitation, vascular remodelling, Effects, identify, lack, develop, involved, generate, applied, reveal, drugs targeting, systemic effect, the SARS-CoV-2, 【제목키워드】 Treatment, network analysis, Effect, reveal,