Park Heewon, Wang Qingbo S, Hasegawa Takanori, Namkoong Ho, Tanaka Hiroko, Koike Ryuji, Kitagawa Yuko, Kimura Akinori, Imoto Seiya, Kanai Takanori, Fukunaga Koichi, Ogawa Seishi, Okada Yukinori, Miyano Satoru
School of Mathematics Statistics and Data Science, Sungshin Women's University, Seoul 02844, Republic of Korea.
M&D Data Science Center, Institute of Science Tokyo, Tokyo 113-8510, Japan.
Int J Mol Sci. 2025 May 6;26(9):4412. doi: 10.3390/ijms26094412.
The 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' 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-receptor 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.
由严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)引起的 2019 冠状病毒病(COVID-19)在全球迅速传播,导致了严重的缺氧、急性呼吸窘迫综合征、多器官衰竭,最终导致死亡。通过聚焦几个基因/单个基因对小规模分子相互作用进行了分析,提供了重要见解;然而,除了显示遗传风险的全基因组关联研究(GWAS)和表达定量性状位点(eQTLm)之外,尚未对全基因组多组学综合分子相互作用进行充分研究。从 2020 年 4 月至今,我们建立了一个全日本范围的系统,最初名为日本 COVID-19 特别工作组。该系统从 120 多家医院的网络中收集了 6500 多名 COVID-19 患者的外周血以及尽可能多的相关临床信息。DNA、RNA、血清和血浆被提取并储存在这个库中。本研究利用来自日本 COVID-19 特别工作组的多组学数据,揭示了诱导不同 COVID-19 严重程度水平(轻度、中度、重度和危重症)的炎症基因网络之间的相互作用。我们分析 RNA 和蛋白质表达,以估计特定严重程度的炎症网络,该网络通过配体-受体对揭示 RNA 和蛋白质网络之间的相互作用。我们的大规模 RNA/蛋白质表达数据分析表明,非典型趋化因子受体 2(ACKR2)作为连接 RNA 和蛋白质炎症网络以诱导 COVID-19 危重症的关键中介。ACKR2 出现在 RNA 和蛋白质炎症网络中,在高严重程度病例中显示出活跃的相互作用,而在轻度病例中相互作用较弱。结果还显示了白细胞介素(IL)、细胞因子受体活性、细胞粘附以及涉及 CC 趋化因子配体(CCL)基因家族和 ACKR2 的相互作用之间特定严重程度的分子相互作用。