Evidence map›Paper›PMID 40775517›Full record

ArticleCommunications biology2025

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

Hyojung Ryu, Kyungwhan An, Yoonsung Kwon, Yeonsu Jeon, Sungwon Jeon, Hansol Choi, Yeo Jin Kim, Sunhwa Kim, Ok Joo Sul, SangJoon Lee and 4 more

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Hyojung Ryu *Clinomics, Inc., Ulsan, Republic of Korea.
Kyungwhan An *GenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Yoonsung KwonGenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Yeonsu JeonClinomics, Inc., Ulsan, Republic of Korea.ORCID http://orcid.org/0000-0003-4560-4142
Sungwon JeonClinomics, Inc., Ulsan, Republic of Korea.ORCID http://orcid.org/0000-0002-2729-9087
Hansol ChoiGenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Yeo Jin KimClinomics, Inc., Ulsan, Republic of Korea.
Sunhwa KimDivision of Pulmonology, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea.
Ok Joo SulBiomedical Research Center, Ulsan University Hospital, School of Medicine, University of Ulsan, Ulsan, Republic of Korea.
SangJoon LeeDepartment of Biological Science, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID http://orcid.org/0000-0001-7500-782X
Asaph Young ChunInstitute for Pandemic Sciences AI.celerator, Seoul National University, Seoul, Republic of Korea.
Eun-Seok ShinDepartment of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea. sesim1989@gmail.com.ORCID http://orcid.org/0000-0002-9169-6968
Seung Won RaDivision of Pulmonology, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea. docra@uuh.ulsan.kr.ORCID http://orcid.org/0000-0002-2458-8414
Jong BhakGenomeLab, Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea. jongbhak@genomics.org.ORCID http://orcid.org/0000-0002-4228-1299

Funding

National Research Foundation of Korea (NRF) 2022R1F1A1062753, RS-2023-00227944
6 · The paper itself

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.

Indexed as

COVID-19CpG IslandsDNA MethylationSARS-CoV-2Epigenesis, GeneticFemaleGene Expression ProfilingHumansMaleMiddle AgedSeverity of Illness IndexTranscriptome

Identifiers

PMID40775517
PMCPMC12331940

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.