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rapid worldwide transmission of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to severe cases of hypoxia, acute respiratory distress syndrome, multi-organ failure, and ultimately death. Small-scale molecular interactions have been analyzed by focusing on several genes\/single genes, providing important insights; however, genome-wide multi-omics comprehensive molecular interactions have not yet been well investigated with the exception of GWAS and eQTLm, both of which show genetic risks. From April of 2020 until now, we have created a Japan-wide system, initially named the Japan COVID-19 Task Force. This system has collected more than 6500 COVID-19 patients\u2019 peripheral blood and as much associated clinical information as possible from a network of more than 120 hospitals. DNA, RNA, serum, and plasma were extracted and stored in this bank. This study unravels the interplay of inflammatory gene networks that induce different COVID-19 severity levels (mild, moderate, severe, and critical) by using multi-omics data from the Japan COVID-19 Task Force. We analyze RNA and protein expressions to estimate severity-specific inflammation networks that uncover the interplay between RNA and protein networks via ligand\u2013receptor pairs. Our large-scale RNA\/protein expression data analysis reveals that the atypical chemokine receptor 2 (ACKR2) acts as a key broker linking RNA and protein inflammation networks to induce COVID-19 critical severity. ACKR2 emerges in RNA and protein inflammation networks, showing active interplay in high-severity cases and weak interactions in mild cases. The results also show severity-specific molecular interactions between interleukin (IL), cytokine receptor activity, cell adhesion, and interactions involving the CC chemokine ligand (CCL) gene family and ACKR2.<\/jats:p>","DOI":"10.3390\/ijms26094412","type":"journal-article","created":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T09:08:56Z","timestamp":1746522536000},"page":"4412","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unraveling the COVID-19 Severity Hubs and Interplays in Inflammatory-Related RNA\u2013Protein Networks"],"prefix":"10.3390","volume":"26","author":[{"given":"Heewon","family":"Park","sequence":"first","affiliation":[{"name":"School of Mathematics Statistics and Data Science, Sungshin Women\u2019s University, Seoul 02844, Republic of Korea"},{"name":"M&D Data Science Center, Institute of Science Tokyo, Tokyo 113-8510, Japan"},{"name":"Human Genome Center, Institute of Medical 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