Abstract
Background
To understand the transcriptomic response to SARS-CoV-2 infection, is of the utmost importance to design diagnostic tools predicting the severity of the infection.
Methods
We have performed a deep sampling analysis of the viral transcriptomic data oriented towards drug repositioning. Using different samplers, the basic principle of this methodology the biological invariance, which means that the pathways altered by the disease, should be independent on the algorithm used to unravel them.
Results
The transcriptomic analysis of the altered pathways, reveals a distinctive inflammatory response and potential side effects of infection. The virus replication causes, in some cases, acute respiratory distress syndrome in the lungs, and affects other organs such as heart, brain, and kidneys. Therefore, the repositioned drugs to fight COVID-19 should, not only target the interferon signalling pathway and the control of the inflammation, but also the altered genetic pathways related to the side effects of infection. We also show via Principal Component Analysis that the transcriptome signatures are different from influenza and RSV. The gene COL1A1, which controls collagen production, seems to play a key/vital role in the regulation of the immune system. Additionally, other small-scale signature genes appear to be involved in the development of other COVID-19 comorbidities.
Conclusions
Transcriptome-based drug repositioning offers possible fast-track antiviral therapy for COVID-19 patients. It calls for additional clinical studies using FDA approved drugs for patients with increased susceptibility to infection and with serious medical complications.
【저자키워드】 SARS-CoV-2, coronavirus, machine learning, drug repositioning, Side effects, Small scale genetic signature, 【초록키워드】 COVID-19, Transcriptome, Inflammation, antiviral therapy, Influenza, SARS-COV-2 infection, susceptibility, severity, Genetic, Infection, Comorbidities, diagnostic, drug, immune system, Brain, FDA approved drug, RSV, Lungs, Algorithm, Patient, Control, pathway, complications, virus replication, transcriptomic analysis, collagen, transcriptomic data, methodology, COVID-19 patients, acute respiratory distress, clinical study, Inflammatory response, Analysis, Pathways, Side effect, Regulation, causes, syndrome, kidneys, component, offer, Affect, transcriptomic, principal, independent, Col1a1, Result, performed, involved, the disease, the interferon, reveal, other organ, 【제목키워드】 COVID-19, susceptibility, Infection, drug, response, pathway, Complication, help, transcriptomic, responsible, develop, reveal,