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Integrative multi-omics analysis of different patient cohorts stratified by COVID-19 Severity : a statistical and network approach
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Integrative multi-omics analysis of different patient cohorts stratified by COVID-19 Severity : a statistical and network approach

Keabetswe Setlogomi
Master of Science (MSc), University of Johannesburg
2023
Handle:
https://hdl.handle.net/10210/511612

Abstract

Emerging infectious diseases Virus diseases COVID-19 (Disease) -- Chemotherapy -- Research
n December 2019, a novel human infecting Coronavirus was detected in Wuhan China, leading to the beginning of the Coronavirus disease pandemic. The exponential spread of Severe Acute Respiratory Syndrome Coronavirus 2 led to increased infection and high mortality rates, which propelled a rapid scientific response towards understanding the disease. In recent years, data from multiple assays has been integrated to attain a holistic understanding of any disease or condition. However, despite the extensive analysis conducted on SAR-CoV-2 infection, replication mechanisms, clinical manifestations, and the categorisation of various disease groups based on symptomologies; gene alterations occurring at a cellular and molecular level and epigenomic factors affecting those changes, need to be fully uncovered to provide a bridge between the infection and symptom stages. Therefore, a comprehensive analysis of the alterations that occur at a cellular level, in response to SARS-CoV-2 infection provides an opportunity to thoroughly understand and unpack the factors that support disease progression or alterations thereof, which ultimately result in the phenotypic consequences of SARS-CoV-2 infection. We aimed to explore the integration of transcriptomic and epigenomic data, to uncover potential biomarkers and biological pathways significantly contributing to COVID-19 disease progression and in doing so highlight the benefit of joint analysis in generating biological insights from the wealth of scientific knowledge that is generated and made publicly available by researchers. This was achieved through the use of statistical and network approaches, which enabled us to represent relevant interactions between significant biomarkers and highlight potential regulatory relationships in response to SARS-CoV-2 infection. Our study identified various disease severity-associated gene transcripts, microRNA IDs and CpG sites. The analysis of the gene expression data revealed alterations in the cellular components and biological processes of infected patients, particularly those involving changes in mitochondrial function and the detrimental effects of an over-stimulated immune system in response to SARS-CoV-2 progression. The analysis of the microRNA data uncovered miR-21-5p, miR-26a-5p and miR-30d-5p as role players in the pathogenesis of COVID-19, whereby miR-21-5p plays a crucial role in contributing towards the over-activation of inflammatory responses. The analysis of the DNA methylation data uncovered that host responses against viral infection are potentially dysregulated through the alteration of gene expression to favour disease progression. The enrichment of various biological processes in response to SARS-CoV-2 infection was a direct consequence of the dysregulation of various processes by viral mechanisms, the detrimental overstimulation of the host immune system or inhibitory effects on various biological processes, which ultimately contribute to the evasion of host immunity and establishment of xii viral progression and severity. Not only did these findings highlight the dynamicity of SARS-CoV-2, but also underscored the importance of key regulators in viral progression and potential therapeutic targets to combat COVID-19.
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