Back

Identification of potential biomarkers and inhibitors for SARS-CoV-2 infection

Gu, H.; Yuan, G.

2020-09-18 epidemiology
10.1101/2020.09.15.20195487 medRxiv
Show abstract

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has overwhelmed many health systems globally. Here, we aim to identify biological markers and associated biological processes of COVID-19 using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profile of the GSE152418 dataset was originally produced by using the high-throughput Illumina NovaSeq 6000. Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and Gene Ontology (GO) enrichment analyses were applied to identify functional categories and biochemical pathways. KEGG and GO results suggested that biological pathways such as "Cancer pathways" and "Insulin pathways" were mostly affected in the development of COVID-19. Moreover, we identified several genes including EP300, CREBBP, and POLR2A were involved in the virus activities in COVID-19 patients. We further predicted that some inhibitors may have the potential to block the SARS-CoV-2 infection based on the L1000FWD analysis. Therefore, our study provides further insights into the underlying pathogenesis of COVID-19.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Science China Life Sciences
26 papers in training set
Top 0.1%
26.8%
2
The Innovation
12 papers in training set
Top 0.1%
5.0%
3
Emerging Microbes & Infections
74 papers in training set
Top 0.2%
4.5%
4
PLOS ONE
4510 papers in training set
Top 35%
4.1%
5
Frontiers in Medicine
113 papers in training set
Top 1%
4.1%
6
Scientific Reports
3102 papers in training set
Top 33%
3.7%
7
Frontiers in Public Health
140 papers in training set
Top 2%
3.2%
50% of probability mass above
8
Journal of Medical Virology
137 papers in training set
Top 1%
3.0%
9
Quantitative Biology
11 papers in training set
Top 0.1%
2.7%
10
Journal of Advanced Research
15 papers in training set
Top 0.1%
2.7%
11
eLife
5422 papers in training set
Top 34%
2.2%
12
Journal of Infection
71 papers in training set
Top 1.0%
2.0%
13
Heliyon
146 papers in training set
Top 1%
2.0%
14
Genomics, Proteomics & Bioinformatics
171 papers in training set
Top 3%
1.8%
15
Frontiers in Microbiology
375 papers in training set
Top 6%
1.5%
16
Frontiers in Pharmacology
100 papers in training set
Top 3%
1.3%
17
National Science Review
22 papers in training set
Top 2%
0.9%
18
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 7%
0.9%
19
Medicine
30 papers in training set
Top 2%
0.8%
20
Journal of Cellular Physiology
21 papers in training set
Top 0.8%
0.7%
21
International Journal of Infectious Diseases
126 papers in training set
Top 4%
0.7%
22
Journal of Medical Internet Research
85 papers in training set
Top 5%
0.7%
23
International Journal of Epidemiology
74 papers in training set
Top 3%
0.7%
24
Computers in Biology and Medicine
120 papers in training set
Top 5%
0.7%
25
Journal of Translational Medicine
46 papers in training set
Top 3%
0.7%
26
Molecular & Cellular Proteomics
158 papers in training set
Top 2%
0.7%
27
Journal of Cellular and Molecular Medicine
18 papers in training set
Top 1%
0.7%
28
British Journal of Cancer
42 papers in training set
Top 2%
0.7%
29
Virus Research
36 papers in training set
Top 1%
0.7%
30
Microbial Genomics
204 papers in training set
Top 2%
0.7%