Article ; Online: Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status.
2023 Volume 24, Issue 1, Page(s) 319
Abstract: Background: There is still more to learn about the pathobiology of COVID-19. A multi-omic approach offers a holistic view to better understand the mechanisms of COVID-19. We used state-of-the-art statistical learning methods to integrate genomics, ... ...
Abstract | Background: There is still more to learn about the pathobiology of COVID-19. A multi-omic approach offers a holistic view to better understand the mechanisms of COVID-19. We used state-of-the-art statistical learning methods to integrate genomics, metabolomics, proteomics, and lipidomics data obtained from 123 patients experiencing COVID-19 or COVID-19-like symptoms for the purpose of identifying molecular signatures and corresponding pathways associated with the disease. Results: We constructed and validated molecular scores and evaluated their utility beyond clinical factors known to impact disease status and severity. We identified inflammation- and immune response-related pathways, and other pathways, providing insights into possible consequences of the disease. Conclusions: The molecular scores we derived were strongly associated with disease status and severity and can be used to identify individuals at a higher risk for developing severe disease. These findings have the potential to provide further, and needed, insights into why certain individuals develop worse outcomes. |
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MeSH term(s) | Humans ; Multiomics ; COVID-19 ; Metabolomics ; Genomics ; Inflammation |
Language | English |
Publishing date | 2023-06-12 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2041499-7 |
ISSN | 1471-2164 ; 1471-2164 |
ISSN (online) | 1471-2164 |
ISSN | 1471-2164 |
DOI | 10.1186/s12864-023-09410-5 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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