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Quantitative test for COVID-19 in the cardiovascular process: in silico gene-target cluster evaluation
Journal article   Peer reviewed

Quantitative test for COVID-19 in the cardiovascular process: in silico gene-target cluster evaluation

Luiz Henrique Pontes dos Santos, Chad Eric Grueter and Vânia Marilande Ceccatto
Biotechnology Research and Innovation, Vol.8(2), e2024009
2024
DOI: 10.4322/biori.00092024

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Abstract

The relative lack of clinical knowledge revealed by the most recent pandemic caused by SARS-CoV-2 has highlighted the need for molecular knowledge in ‘omics disciplines and molecular databases, integrated with available and user-friendly virtual tools. The production of an RT-qPCR reaction cluster is a posteriori and must be planned based on the knowledge of several available sources: specialized literature and databases with laboratory medicine tools. However, the specificities of infection with the new virus would require the prior use and execution of techniques to obtain extensive expression profiles, such as next-generation sequencing (i.e., RNAseq). In this work, we cross-reference RT-qPCR and RNAseq resources from literature and the KEGG Disease Database (Kyoto Encyclopedia of Genes and Genomes) to provide comprehensive insights into COVID-19-related cardiovascular DEGs and gene-target relationships. Gene clusters were used to identify enriched pathways and compare the canonical metabolic pathways for COVID-19 cardiac quantitative evaluation. One hundred seventy-one genes were listed in 42 KEGG Disease entries, resulting in 194 enriched pathways, with seven annotated pathways showing statistically significant XD-scores. Some specific differentially expressed genes in transcriptional literature evaluations overlapped with the KEGG canonical cardiac processes. The KEGG Disease cardiovascular gene set showed six pathways linked to quantitative cardiac evaluation that are significantly enriched in COVID-19. Results indicated hypertrophic and dilated cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, and cardiac muscle contraction. The presence of specific sets of genes with links between gene clusters, overlaps of genes and processes, and subsets of compartmentalization represent different possibilities for metabolic pathways and gene targets related to cardiac damage pre- and post-COVID-19 infection.

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