| Autor: |
Xiaohua Tang, Rui Sun, Weigang Ge, Tingting Mao, Liujia Qian, Chongquan Huang, Zhouyang Kang, Qi Xiao, Meng Luo, Qiushi Zhang, Sainan Li, Hao Chen, Wei Liu, Bingjie Wang, Shufei Li, Xiaoling Lin, Xueqin Xu, Huanzheng Li, Lianpeng Wu, Jianyi Dai, Huanhuan Gao, Lu Li, Tian Lu, Xiao Liang, Xue Cai, Guan Ruan, Fei Xu, Yan Li, Yi Zhu, Ziqing Kong, Jianping Huang, Tiannan Guo |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Cell Discovery, Vol 8, Iss 1, Pp 1-18 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2056-5968 |
| DOI: |
10.1038/s41421-022-00441-y |
| Popis: |
Abstract Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we found that patients with long viral RNA course (LC) exhibited prolonged high-level IgG antibodies and higher regulatory T (Treg) cell counts compared to those with short viral RNA course (SC) in terms of viral load. Longitudinal proteomics and metabolomics analyses of the patient sera uncovered that prolonged viral RNA shedding was associated with inhibition of the liver X receptor/retinoid X receptor (LXR/RXR) pathway, substantial suppression of diverse metabolites, activation of the complement system, suppressed cell migration, and enhanced viral replication. Furthermore, a ten-molecule learning model was established which could potentially predict viral RNA shedding period. In summary, this study uncovered enhanced inflammation and suppressed adaptive immunity in COVID-19 patients with prolonged viral RNA shedding, and proposed a multi-omic classifier for viral RNA shedding prediction. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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