Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery

Abstract Multi-omics analyses of severe COVID-19 cases are crucial in deciphering the complex interplay between genetic and epigenetic factors. Here, we present an analysis of Expression Quantitative Trait Methylation (eQTM) to investigate the complex interplay of methylation and gene expression pat...

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Main Authors: Hyojung Ryu, Kyungwhan An, Yoonsung Kwon, Yeonsu Jeon, Sungwon Jeon, Hansol Choi, Yeo Jin Kim, Sunhwa Kim, Ok Joo Sul, SangJoon Lee, Asaph Young Chun, Eun-Seok Shin, Seung Won Ra, Jong Bhak
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-025-08609-4
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author Hyojung Ryu
Kyungwhan An
Yoonsung Kwon
Yeonsu Jeon
Sungwon Jeon
Hansol Choi
Yeo Jin Kim
Sunhwa Kim
Ok Joo Sul
SangJoon Lee
Asaph Young Chun
Eun-Seok Shin
Seung Won Ra
Jong Bhak
author_facet Hyojung Ryu
Kyungwhan An
Yoonsung Kwon
Yeonsu Jeon
Sungwon Jeon
Hansol Choi
Yeo Jin Kim
Sunhwa Kim
Ok Joo Sul
SangJoon Lee
Asaph Young Chun
Eun-Seok Shin
Seung Won Ra
Jong Bhak
author_sort Hyojung Ryu
collection DOAJ
description Abstract Multi-omics analyses of severe COVID-19 cases are crucial in deciphering the complex interplay between genetic and epigenetic factors. Here, we present an analysis of Expression Quantitative Trait Methylation (eQTM) to investigate the complex interplay of methylation and gene expression pattern during the acute phase of severe COVID-19. We identified 16 differentially expressed genes and 30 nearby differentially methylated CpG sites. Six key genes—SRXN1, FURIN, IL18RAP, FOXO3, GCNT4, and FKBP5—were either up-regulated or down-regulated near hypomethylated CpG sites. These genes are associated with viral infiltration, immune activation, lung damage, and oxidative stress-related multi-organ failure, which are the hallmarks of severe COVID-19. Interestingly, during the recovery phase, methylation and gene expression levels returned to baseline, underscoring the rapid and reversible nature of these molecular changes. These findings provide insight into the dynamics of epigenetic and transcriptomic shifts according to the infectious stage, supporting potential prognostic and therapeutic approaches for severe COVID-19.
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spelling doaj-art-b249cd2b5d7e49398347831e1bb41ad02025-08-20T03:42:56ZengNature PortfolioCommunications Biology2399-36422025-08-018111010.1038/s42003-025-08609-4Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recoveryHyojung Ryu0Kyungwhan An1Yoonsung Kwon2Yeonsu Jeon3Sungwon Jeon4Hansol Choi5Yeo Jin Kim6Sunhwa Kim7Ok Joo Sul8SangJoon Lee9Asaph Young Chun10Eun-Seok Shin11Seung Won Ra12Jong Bhak13Clinomics, Inc.GenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST)GenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST)Clinomics, Inc.Clinomics, Inc.GenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST)Clinomics, Inc.Division of Pulmonology, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of MedicineBiomedical Research Center, Ulsan University Hospital, School of Medicine, University of UlsanDepartment of Biological Science, Ulsan National Institute of Science and Technology (UNIST)Institute for Pandemic Sciences AI.celerator, Seoul National UniversityDepartment of Cardiology, Ulsan University Hospital, University of Ulsan College of MedicineDivision of Pulmonology, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of MedicineGenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST)Abstract Multi-omics analyses of severe COVID-19 cases are crucial in deciphering the complex interplay between genetic and epigenetic factors. Here, we present an analysis of Expression Quantitative Trait Methylation (eQTM) to investigate the complex interplay of methylation and gene expression pattern during the acute phase of severe COVID-19. We identified 16 differentially expressed genes and 30 nearby differentially methylated CpG sites. Six key genes—SRXN1, FURIN, IL18RAP, FOXO3, GCNT4, and FKBP5—were either up-regulated or down-regulated near hypomethylated CpG sites. These genes are associated with viral infiltration, immune activation, lung damage, and oxidative stress-related multi-organ failure, which are the hallmarks of severe COVID-19. Interestingly, during the recovery phase, methylation and gene expression levels returned to baseline, underscoring the rapid and reversible nature of these molecular changes. These findings provide insight into the dynamics of epigenetic and transcriptomic shifts according to the infectious stage, supporting potential prognostic and therapeutic approaches for severe COVID-19.https://doi.org/10.1038/s42003-025-08609-4
spellingShingle Hyojung Ryu
Kyungwhan An
Yoonsung Kwon
Yeonsu Jeon
Sungwon Jeon
Hansol Choi
Yeo Jin Kim
Sunhwa Kim
Ok Joo Sul
SangJoon Lee
Asaph Young Chun
Eun-Seok Shin
Seung Won Ra
Jong Bhak
Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
Communications Biology
title Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
title_full Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
title_fullStr Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
title_full_unstemmed Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
title_short Identification of reactive CpGs and RNA expression in early COVID-19 through cis-eQTM analysis reflecting disease severity and recovery
title_sort identification of reactive cpgs and rna expression in early covid 19 through cis eqtm analysis reflecting disease severity and recovery
url https://doi.org/10.1038/s42003-025-08609-4
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