Open Access
CC BY 4.0 · TH Open 2020; 04(04): e403-e412
DOI: 10.1055/s-0040-1721706
Original Article

Host–Viral Interactions Revealed among Shared Transcriptomics Signatures of ARDS and Thrombosis: A Clue into COVID-19 Pathogenesis

Aastha Mishra
1   Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
,
Shankar Chanchal
1   Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
,
Mohammad Z. Ashraf
1   Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
› Institutsangaben

Funding This work was supported by the research project sponsored under Inspire faculty scheme of Department of Science and Technology and NBS funded project under Department of Biotechnology. S.C. is a senior research fellow of Council of Scientific and Industrial Research (CSIR).
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Abstract

Severe novel corona virus disease 2019 (COVID-19) infection is associated with a considerable activation of coagulation pathways, endothelial damage, and subsequent thrombotic microvascular injuries. These consistent observations may have serious implications for the treatment and management of this highly pathogenic disease. As a consequence, the anticoagulant therapeutic strategies, such as low molecular weight heparin, have shown some encouraging results. Cytokine burst leading to sepsis which is one of the primary reasons for acute respiratory distress syndrome (ARDS) drive that could be worsened with the accumulation of coagulation factors in the lungs of COVID-19 patients. However, the obscurity of this syndrome remains a hurdle in making decisive treatment choices. Therefore, an attempt to characterize shared biological mechanisms between ARDS and thrombosis using comprehensive transcriptomics meta-analysis is made. We conducted an integrated gene expression meta-analysis of two independently publicly available datasets of ARDS and venous thromboembolism (VTE). Datasets GSE76293 and GSE19151 derived from National Centre for Biotechnology Information–Gene Expression Omnibus (NCBI-GEO) database were used for ARDS and VTE, respectively. Integrative meta-analysis of expression data (INMEX) tool preprocessed the datasets and effect size combination with random effect modeling was used for obtaining differentially expressed genes (DEGs). Network construction was done for hub genes and pathway enrichment analysis. Our meta-analysis identified a total of 1,878 significant DEGs among the datasets, which when subjected to enrichment analysis suggested inflammation–coagulation–hypoxemia convolutions in COVID-19 pathogenesis. The top hub genes of our study such as tumor protein 53 (TP53), lysine acetyltransferase 2B (KAT2B), DExH-box helicase 9 (DHX9), REL-associated protein (RELA), RING-box protein 1 (RBX1), and proteasome 20S subunit beta 2 (PSMB2) gave insights into the genes known to be participating in the host–virus interactions that could pave the way to understand the various strategies deployed by the virus to improve its replication and spreading.

Author's Contributions

A.M. and M.Z.A. wrote the manuscript and designed the study. S.C. participated in data analysis and interpretation and all authors edited and approved the final version of the manuscript.


Supplementary Material



Publikationsverlauf

Eingereicht: 03. Juni 2020

Angenommen: 02. November 2020

Artikel online veröffentlicht:
17. Dezember 2020

© 2020. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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