Analysis of transcriptomics data from COVID-19 patients: a pilot research.

Analysis of transcriptomics data from COVID-19 patients: a pilot research.

Publication date: Jan 19, 2024

During SARS-CoV-2 infection, the virus transforms the infected host cell into factories that produce new viral particles. As infection progresses, the infected cells undergo numerous changes in various pathways. One of these changes is the occurrence of a cytokine storm, which leads to severe symptoms. In this study, we examined the transcriptomic changes caused by COVID-19 by analyzing RNA-seq data obtained from COVID-19-positive patients as well as COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. We analyzed the first datasets, consisting of 96 samples to validate our methods. The objective of this publication is to report the pilot results. To explore potential biomarkers related to disease severity, we conducted a differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Given the large number of potential biomarkers we identified, we further performed pathway enrichment analysis with terms from Kyoto Encyclopedia of Genes and Genomics (KEGG) to obtain a more profound understanding of altered pathways. Our results indicate that pathways related to immune processes, response to infection, and multiple signaling pathways were affected. These findings align with several previous studies that also reported the influence of SARS-CoV-2 infection on these pathways.

Concepts Keywords
Pilot COVID-19
Storm Differentially expressed genes
Transcriptomics Enriched pathways
Viral Gene enrichment analysis
RNA-seq
SARS-CoV-2
Transcriptomics

Semantics

Type Source Name
disease MESH COVID-19
pathway REACTOME SARS-CoV-2 Infection
disease MESH infection
disease MESH cytokine storm
disease VO report
disease IDO symptom
disease MESH Long Covid
disease VO gene

Original Article

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