Evidence map›Paper›PMID 40362649›Full record

ArticleInternational journal of molecular sciences2025

Unraveling the COVID-19 Severity Hubs and Interplays in Inflammatory-Related RNA-Protein Networks.

Heewon Park, Qingbo S Wang, Takanori Hasegawa, Ho Namkoong, Hiroko Tanaka, Ryuji Koike, Yuko Kitagawa, Akinori Kimura, Seiya Imoto, Takanori Kanai and 4 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 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.

Heewon ParkSchool of Mathematics Statistics and Data Science, Sungshin Women's University, Seoul 02844, Republic of Korea.
Qingbo S WangDepartment of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
Takanori HasegawaM&D Data Science Center, Institute of Science Tokyo, Tokyo 113-8510, Japan.ORCID 0000-0001-7251-9950
Ho NamkoongDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo 160-8582, Japan.
Hiroko TanakaM&D Data Science Center, Institute of Science Tokyo, Tokyo 113-8510, Japan.ORCID 0000-0001-9634-8922
Ryuji KoikeHealth Science Research and Development Center (HeRD), Tokyo Medical and Dental University, Tokyo 113-8510, Japan.ORCID 0000-0001-5647-8159
Yuko KitagawaDepartment of Surgery, Keio University School of Medicine, Tokyo 160-8582, Japan.
Akinori KimuraMedical Research Institute, Tokyo Medical and Dental University, Tokyo 113-8510, Japan.ORCID 0000-0002-4933-2132
Seiya ImotoHuman Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.ORCID 0000-0002-2989-308X
Takanori KanaiDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo 160-8582, Japan.
Koichi FukunagaDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan.
Seishi OgawaDepartment of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Tokyo 606-8507, Japan.
Yukinori OkadaDepartment of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
Satoru MiyanoM&D Data Science Center, Institute of Science Tokyo, Tokyo 113-8510, Japan.ORCID 0000-0002-1753-6616

Funding

Japan Agency for Medical Research and Development JP23tk0124003h0001, JP24tk0124003h0002, JP20fk0108452h0001, JP21fk0108553h0001, JP22fk0108510h0001, JP23kk0305022 , JP22ek0410075, JP23km0405211, JP23km0405217, JP23ek0109594, JP23ek0410113, JP223fa627002, JP223fa627010, JP233fa627011, JP23zf01270Japan Science and Technology Agency JP-MJCR20H2, JPMJFR225Y, JPMJPR21R7, JP-MJMS2021, JPMJMS2024Japan Society for the Promotion of Science 22H00476, 23K14233, JP24H00009Ministry of Health, Labour and Welfare 20CA2054National Research Foundation of Korea RS-2023-00276559
6 · The paper itself

Abstract

The rapid worldwide transmission of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to severe cases of hypoxia, acute respiratory distress syndrome, multi-organ failure, and ultimately death. Small-scale molecular interactions have been analyzed by focusing on several genes/single genes, providing important insights; however, genome-wide multi-omics comprehensive molecular interactions have not yet been well investigated with the exception of GWAS and eQTLm, both of which show genetic risks. From April of 2020 until now, we have created a Japan-wide system, initially named the Japan COVID-19 Task Force. This system has collected more than 6500 COVID-19 patients' peripheral blood and as much associated clinical information as possible from a network of more than 120 hospitals. DNA, RNA, serum, and plasma were extracted and stored in this bank. This study unravels the interplay of inflammatory gene networks that induce different COVID-19 severity levels (mild, moderate, severe, and critical) by using multi-omics data from the Japan COVID-19 Task Force. We analyze RNA and protein expressions to estimate severity-specific inflammation networks that uncover the interplay between RNA and protein networks via ligand-receptor pairs. Our large-scale RNA/protein expression data analysis reveals that the atypical chemokine receptor 2 (ACKR2) acts as a key broker linking RNA and protein inflammation networks to induce COVID-19 critical severity. ACKR2 emerges in RNA and protein inflammation networks, showing active interplay in high-severity cases and weak interactions in mild cases. The results also show severity-specific molecular interactions between interleukin (IL), cytokine receptor activity, cell adhesion, and interactions involving the CC chemokine ligand (CCL) gene family and ACKR2.

Indexed as

COVID-19Gene Regulatory NetworksInflammationHumansJapanProtein Interaction MapsSARS-CoV-2Severity of Illness IndexACKR2COVID-19immunogenesRNA–protein networksseverity

Identifiers

PMID40362649
PMCPMC12072413

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.