tetano
Editor, Senior Moderator
J Cell Mol Med
. 2021 Mar 23.
doi: 10.1111/jcmm.16444. Online ahead of print.
Risk stratification by long non-coding RNAs profiling in COVID-19 patients
Jie Cheng[SUP] 1 2 [/SUP], Xiang Zhou[SUP] 3 [/SUP], Weijun Feng[SUP] 4 [/SUP], Min Jia[SUP] 5 [/SUP], Xinlu Zhang[SUP] 6 [/SUP], Taixue An[SUP] 7 [/SUP], Minyuan Luan[SUP] 8 [/SUP], Yi Pan[SUP] 9 10 [/SUP], Shu Zhang[SUP] 11 [/SUP], Zhaoming Zhou[SUP] 12 [/SUP], Lei Wen[SUP] 13 [/SUP], Yun Sun[SUP] 1 2 [/SUP], Cheng Zhou[SUP] 14 [/SUP]
Affiliations
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic worldwide. Long non-coding RNAs (lncRNAs) are a subclass of endogenous, non-protein-coding RNA, which lacks an open reading frame and is more than 200 nucleotides in length. However, the functions for lncRNAs in COVID-19 have not been unravelled. The present study aimed at identifying the related lncRNAs based on RNA sequencing of peripheral blood mononuclear cells from patients with SARS-CoV-2 infection as well as health individuals. Overall, 17 severe, 12 non-severe patients and 10 healthy controls were enrolled in this study. Firstly, we reported some altered lncRNAs between severe, non-severe COVID-19 patients and healthy controls. Next, we developed a 7-lncRNA panel with a good differential ability between severe and non-severe COVID-19 patients using least absolute shrinkage and selection operator regression. Finally, we observed that COVID-19 is a heterogeneous disease among which severe COVID-19 patients have two subtypes with similar risk score and immune score based on lncRNA panel using iCluster algorithm. As the roles of lncRNAs in COVID-19 have not yet been fully identified and understood, our analysis should provide valuable resource and information for the future studies.
Keywords: COVID-19; RNA-seq; lncRNA; pulmonary injury; transcriptome.
. 2021 Mar 23.
doi: 10.1111/jcmm.16444. Online ahead of print.
Risk stratification by long non-coding RNAs profiling in COVID-19 patients
Jie Cheng[SUP] 1 2 [/SUP], Xiang Zhou[SUP] 3 [/SUP], Weijun Feng[SUP] 4 [/SUP], Min Jia[SUP] 5 [/SUP], Xinlu Zhang[SUP] 6 [/SUP], Taixue An[SUP] 7 [/SUP], Minyuan Luan[SUP] 8 [/SUP], Yi Pan[SUP] 9 10 [/SUP], Shu Zhang[SUP] 11 [/SUP], Zhaoming Zhou[SUP] 12 [/SUP], Lei Wen[SUP] 13 [/SUP], Yun Sun[SUP] 1 2 [/SUP], Cheng Zhou[SUP] 14 [/SUP]
Affiliations
- PMID: 33759345
- DOI: 10.1111/jcmm.16444
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic worldwide. Long non-coding RNAs (lncRNAs) are a subclass of endogenous, non-protein-coding RNA, which lacks an open reading frame and is more than 200 nucleotides in length. However, the functions for lncRNAs in COVID-19 have not been unravelled. The present study aimed at identifying the related lncRNAs based on RNA sequencing of peripheral blood mononuclear cells from patients with SARS-CoV-2 infection as well as health individuals. Overall, 17 severe, 12 non-severe patients and 10 healthy controls were enrolled in this study. Firstly, we reported some altered lncRNAs between severe, non-severe COVID-19 patients and healthy controls. Next, we developed a 7-lncRNA panel with a good differential ability between severe and non-severe COVID-19 patients using least absolute shrinkage and selection operator regression. Finally, we observed that COVID-19 is a heterogeneous disease among which severe COVID-19 patients have two subtypes with similar risk score and immune score based on lncRNA panel using iCluster algorithm. As the roles of lncRNAs in COVID-19 have not yet been fully identified and understood, our analysis should provide valuable resource and information for the future studies.
Keywords: COVID-19; RNA-seq; lncRNA; pulmonary injury; transcriptome.