Plasma cell-free RNA characteristics in COVID-19 patients

作者：Yanqun Wang, Jie Li, Lu Zhang, Hai‐Xi Sun, Zhaoyong Zhang, Jinjin Xu, Yonghao Xu, Yu Lin, Airu Zhu, Yuxue Luo, Haibo Zhou, Yan Wu, Shanwen Lin, Yuzhe Sun, Fei Xiao, Ruiying Chen, Liyan Wen, Wei Chen, Fang Li, Rijing Ou, Yanjun Zhang, Tingyou Kuo, Yuming Li, Lingguo Li, Jing Sun, Kun Sun, Zhen Zhuang, Haorong Lu, Chen Zhao, Guoqiang Mai, Jianfen Zhuo, Puyi Qian, Jiayu Chen, Huanming Yang, Jian Wang, Xun Xu, Nanshan Zhong, Jingxian Zhao, Junhua Li, Jincun Zhao, Xin Jin · 发表于：Genome Research · 年份：2022 · DOI：10.1101/gr.276175.121 · 被引用次数：70 · 研究领域：RNA modifications and cancer、MicroRNA in disease regulation、Cancer-related molecular mechanisms research

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral ( NFKB1A , IFITM3 , and IFI27 ) and neutrophil activation ( S100A8 , CD68 , and CD63 )–related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs ( GJA9 - MYCBP ) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-C...