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Analysis of transcriptomic responses to SARS-CoV-2 reveals plausible defective pathways responsible for increased susceptibility to infection and complications and helps to develop fast-track repositioning of drugs against COVID-19.
deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Álvarez-Machancoses, Óscar; Bea, Guillermina; Galmarini, Carlos M; Kloczkowski, Andrzej.
  • deAndrés-Galiana EJ; Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics, University of Oviedo, C. Federico García Lorca, 18, 33007, Oviedo, Spain; Department of Computer Science, University of Oviedo, C. Federico García Lorca, 18, 33007, Oviedo, Spain. Electronic address: andresenriq
  • Fernández-Martínez JL; Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics, University of Oviedo, C. Federico García Lorca, 18, 33007, Oviedo, Spain; DeepBioInsights, Spain. Electronic address: jlfm@uniovi.es.
  • Álvarez-Machancoses Ó; Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics, University of Oviedo, C. Federico García Lorca, 18, 33007, Oviedo, Spain. Electronic address: oscar.alvarez@deepbioinsights.com.
  • Bea G; Group of Inverse Problems, Optimization and Machine Learning. Department of Mathematics, University of Oviedo, C. Federico García Lorca, 18, 33007, Oviedo, Spain; DeepBioInsights, Spain. Electronic address: guillermina.bea@icloud.com.
  • Galmarini CM; Topazium Artificial Intelligence, Paseo de la Castellana 40, 28046, Madrid, Spain. Electronic address: cmgalmarini@topazium.com.
  • Kloczkowski A; Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, and Department of Pediatrics, The Ohio State University, Columbus, OH, USA. Electronic address: andrzej.kloczkowski@nationwidechildrens.org.
Comput Biol Med ; 149: 106029, 2022 10.
Article in English | MEDLINE | ID: covidwho-2003989
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article