Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution

Wang, Guoliang; Xiong, Zhuang; Yang, Fei; Zheng, Xinchang; Zong, Wenting; Li, Rujiao; Bào, Yīmíng

doi:10.3390/genes13071109

Cited by 10 publications

(2 citation statements)

References 50 publications

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“…The tumor necrosis factor receptor-related factor 3 (TRAF3) interacting protein 3 (TRAF3IP3) plays an essential role in both the innate and adaptive immunity. Several genomic and methylation studies on COVID-19 have found that TRAF3IP3 can serve as a potential epigenetic biomarker for COVID-19 and is a key mutated region in severe patients, compared with non-severe COVID-19 patients [ 49 , 50 ]. The protein encoded by CD48 is present on the surface of many immune cells and endothelial cells, and is involved in the activation and differentiation of these cells.…”

Section: Discussionmentioning

confidence: 99%

Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods

Zhou

Ding

et al. 2022

Biomolecules

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The rapid spread of COVID-19 has become a major concern for people’s lives and health all around the world. COVID-19 patients in various phases and severity require individualized treatment given that different patients may develop different symptoms. We employed machine learning methods to discover biomarkers that may accurately classify COVID-19 in various disease states and severities in this study. The blood gene expression profiles from 50 COVID-19 patients without intensive care, 50 COVID-19 patients with intensive care, 10 non-COVID-19 individuals without intensive care, and 16 non-COVID-19 individuals with intensive care were analyzed. Boruta was first used to remove irrelevant gene features in the expression profiles, and then, the minimum redundancy maximum relevance was applied to sort the remaining features. The generated feature-ranked list was fed into the incremental feature selection method to discover the essential genes and build powerful classifiers. The molecular mechanism of some biomarker genes was addressed using recent studies, and biological functions enriched by essential genes were examined. Our findings imply that genes including UBE2C, PCLAF, CDK1, CCNB1, MND1, APOBEC3G, TRAF3IP3, CD48, and GZMA play key roles in defining the different states and severity of COVID-19. Thus, a new point of reference is provided for understanding the disease’s etiology and facilitating a precise therapy.

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Section: Discussionmentioning

confidence: 99%

Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods

Zhou

Ding

et al. 2022

Biomolecules

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“…Significant cell-type specific DNA hypermethylation lowering the expression of gamma-delta T cells immune and virus-related signaling pathways genes ) S100A9, AHNAK, CX3CR1, TRAF3IP3 , and LFNG ) in COVID-19 patients (Wang et al, 2022).…”

Section: Genome-wide Dna Methylation Alterations Associated With Covi...mentioning

confidence: 96%

Host’s DNA methylation alterations accompanying COVID-19 infection: a review article

Fouad Ali,

Mohammed Lafta,

Khashman

2023

MSA

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The latest global pandemic of severe acute respiratory syndrome (SARS-CoV-2) is triggered by a highly pathogenic RNA virus initiating coronavirus disease 2019 . Epigenetic modifications (mainly DNA methylation and histone modification) are key regulators of the transcriptome. Such epigenetic marks have the ability to switch on/off gene expression. Additionally, the epigenetic marks are known to be dynamic, reversible, and more vulnerable, than the genome, in response to environmental insults including pathogenic invaders such as viruses and bacteria. During the period of COVID-19 pandemic, much more efforts have been concentrated on characterizing the SARS-CoV-2 virus, determining how it enters the cells, and revealing the associated health complications. Interestingly, the SARS-CoV-2 RNA virus is believed to have the potential of hijacking the host immune cells' epigenome to avoid antiviral defense. However, a very little scientific understanding of how the host epigenome responds to COVID-19 infection. This review summarizes the existing knowledge and provides an overview of a considerable amount of literature published on this topic, especially the contribution of DNA methylation alterations in triggering the cytokine storm in pulmonary tissues mainly by the hyper-activation of the immune system and uncontrolled influx of cytokines in response to COVID-19 infection.

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Single-cell RNA sequencing reveals the transcriptional heterogeneity of Tbx18-positive cardiac cells during heart development

Long,

Wei,

Fang

et al. 2024

Funct Integr Genomics

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Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution

Cited by 10 publications

References 50 publications

Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods

Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods

Host’s DNA methylation alterations accompanying COVID-19 infection: a review article

Single-cell RNA sequencing reveals the transcriptional heterogeneity of Tbx18-positive cardiac cells during heart development

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