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Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients

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...

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Autores principales: Cheng, Jie, Zhou, Xiang, Feng, Weijun, Jia, Min, Zhang, Xinlu, An, Taixue, Luan, Minyuan, Pan, Yi, Zhang, Shu, Zhou, Zhaoming, Wen, Lei, Sun, Yun, Zhou, Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107096/
https://www.ncbi.nlm.nih.gov/pubmed/33759345
http://dx.doi.org/10.1111/jcmm.16444
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author Cheng, Jie
Zhou, Xiang
Feng, Weijun
Jia, Min
Zhang, Xinlu
An, Taixue
Luan, Minyuan
Pan, Yi
Zhang, Shu
Zhou, Zhaoming
Wen, Lei
Sun, Yun
Zhou, Cheng
author_facet Cheng, Jie
Zhou, Xiang
Feng, Weijun
Jia, Min
Zhang, Xinlu
An, Taixue
Luan, Minyuan
Pan, Yi
Zhang, Shu
Zhou, Zhaoming
Wen, Lei
Sun, Yun
Zhou, Cheng
author_sort Cheng, Jie
collection PubMed
description 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.
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spelling pubmed-81070962021-05-10 Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients Cheng, Jie Zhou, Xiang Feng, Weijun Jia, Min Zhang, Xinlu An, Taixue Luan, Minyuan Pan, Yi Zhang, Shu Zhou, Zhaoming Wen, Lei Sun, Yun Zhou, Cheng J Cell Mol Med Original Articles 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. John Wiley and Sons Inc. 2021-03-23 2021-05 /pmc/articles/PMC8107096/ /pubmed/33759345 http://dx.doi.org/10.1111/jcmm.16444 Text en © 2021 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Cheng, Jie
Zhou, Xiang
Feng, Weijun
Jia, Min
Zhang, Xinlu
An, Taixue
Luan, Minyuan
Pan, Yi
Zhang, Shu
Zhou, Zhaoming
Wen, Lei
Sun, Yun
Zhou, Cheng
Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title_full Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title_fullStr Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title_full_unstemmed Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title_short Risk stratification by long non‐coding RNAs profiling in COVID‐19 patients
title_sort risk stratification by long non‐coding rnas profiling in covid‐19 patients
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107096/
https://www.ncbi.nlm.nih.gov/pubmed/33759345
http://dx.doi.org/10.1111/jcmm.16444
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