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Towards precision medicine: Omics approach for COVID-19

The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19...

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Autores principales: Cen, Xiaoping, Wang, Fengao, Huang, Xinhe, Jovic, Dragomirka, Dubee, Fred, Yang, Huanming, Li, Yixue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chinese Medical Association Publishing House. Published by Elsevier BV. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9846903/
https://www.ncbi.nlm.nih.gov/pubmed/36687209
http://dx.doi.org/10.1016/j.bsheal.2023.01.002
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author Cen, Xiaoping
Wang, Fengao
Huang, Xinhe
Jovic, Dragomirka
Dubee, Fred
Yang, Huanming
Li, Yixue
author_facet Cen, Xiaoping
Wang, Fengao
Huang, Xinhe
Jovic, Dragomirka
Dubee, Fred
Yang, Huanming
Li, Yixue
author_sort Cen, Xiaoping
collection PubMed
description The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.
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spelling pubmed-98469032023-01-18 Towards precision medicine: Omics approach for COVID-19 Cen, Xiaoping Wang, Fengao Huang, Xinhe Jovic, Dragomirka Dubee, Fred Yang, Huanming Li, Yixue Biosaf Health Review Article The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time. Chinese Medical Association Publishing House. Published by Elsevier BV. 2023-04 2023-01-18 /pmc/articles/PMC9846903/ /pubmed/36687209 http://dx.doi.org/10.1016/j.bsheal.2023.01.002 Text en © 2023 Chinese Medical Association Publishing House. Published by Elsevier BV. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Review Article
Cen, Xiaoping
Wang, Fengao
Huang, Xinhe
Jovic, Dragomirka
Dubee, Fred
Yang, Huanming
Li, Yixue
Towards precision medicine: Omics approach for COVID-19
title Towards precision medicine: Omics approach for COVID-19
title_full Towards precision medicine: Omics approach for COVID-19
title_fullStr Towards precision medicine: Omics approach for COVID-19
title_full_unstemmed Towards precision medicine: Omics approach for COVID-19
title_short Towards precision medicine: Omics approach for COVID-19
title_sort towards precision medicine: omics approach for covid-19
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9846903/
https://www.ncbi.nlm.nih.gov/pubmed/36687209
http://dx.doi.org/10.1016/j.bsheal.2023.01.002
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