scholarly journals Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yuming Li ◽  
Guixue Hou ◽  
Haibo Zhou ◽  
Yanqun Wang ◽  
Hein Min Tun ◽  
...  

AbstractDisease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

2021 ◽  
Author(s):  
Phoebe C. Parrish ◽  
James D. Thomas ◽  
Shriya Kamlapurkar ◽  
Robert K. Bradley ◽  
Alice H. Berger

2014 ◽  
Vol 13 (1) ◽  
pp. 198-204 ◽  
Author(s):  
H.M. Zhang ◽  
Z.R. Nan ◽  
G.Q. Hui ◽  
X.H. Liu ◽  
Y. Sun

2011 ◽  
Vol 76 (0) ◽  
pp. 235-246 ◽  
Author(s):  
J. D. Rabinowitz ◽  
J. G. Purdy ◽  
L. Vastag ◽  
T. Shenk ◽  
E. Koyuncu

2019 ◽  
Vol 21 (6) ◽  
pp. 1937-1953 ◽  
Author(s):  
Jussi Paananen ◽  
Vittorio Fortino

Abstract The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.


2008 ◽  
Vol 4 (4) ◽  
pp. 186-193 ◽  
Author(s):  
Peter Williamson ◽  
Shirong Zhang ◽  
John Panepinto ◽  
Guowu Hu ◽  
Scott Waterman ◽  
...  

2019 ◽  
Vol 92 (1) ◽  
pp. 1363-1371 ◽  
Author(s):  
Xiaolei Zhang ◽  
Qi Wang ◽  
Yanan Li ◽  
Chengfei Ruan ◽  
Shuyue Wang ◽  
...  

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