Evidence map›Paper›PMID 40796616›Full record

ArticleScientific reports2025

Severity-specific immune landscape of COVID-19 revealed by single-cell sequencing.

Hongying Zhao, Meiting Fei, Wentong Yu, Zhichao Geng, Jing Bai, Li Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

6 authors.

Hongying Zhao *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. zhaohongying@hrbmu.edu.cn.
Meiting Fei *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Wentong YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Zhichao GengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Jing BaiGeneplus-Beijing Institute, Peking University Medical Industrial Park, Zhongguancun Life Science Park, Life Park Road NO.8, Beijing, 102205, China.
Li WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. wangli@hrbmu.edu.cn.

Funding

the National Natural Science Foundation of China 62372144the Outstanding Youth Foundation of Heilongjiang Province of China YQ2023F004
6 · The paper itself

Abstract

The Coronavirus disease 2019 (COVID-19) has rapidly become the worst pandemic since the 1918 influenza pandemic. Studies have shown that severe COVID-19 patients have immune dysfunction. To characterize the dysregulated immune response to SARS-CoV-2 infection, we performed a comprehensive analysis of scRNA-seq and scV(D)J-seq in peripheral blood mononuclear cells from mild, moderate, and severe patients. We observed that as the severity of the disease increased, several CD8 + T cell subsets and Treg cells continued to decrease, while CD4 + T subsets, natural killer cells and plasma cells continued to increase. Several aberrantly expressed biomarkers associated with SARS-CoV-2 severity were identified. For example, RPS26 was down-regulated, while the ZFP36, IL-32, and IgM genes were up-regulated with increasing disease severity. Functional analysis showed multiple immune-related pathways, such as interleukin-2 and interleukin-10 production pathways, were dysregulated. As the disease severity increased, intercellular interactions fluctuated. Particularly, naive CD8 + T cells regulated memory and activated CD8 + T cells, and the weakening in Treg cells' regulation of other immune cells was especially obvious. The expression of the MIF signaling pathway, mediated by CD74 + CXCR4, was higher throughout SARS-CoV-2 infection and the intensity of immune cell-cell interactions mediated by TGF-β was enhanced from mild to severe. Subsequently, scV(D)J-seq analysis showed a decreasing trend in the number of clonotypes, repertoire diversity and clonotypes overlap of monoclonal B cell receptor (BCR) and T cell receptor (TCR) as the SARS-CoV-2 progresses. The CDR3 sequence length in COVID-19-specific clonotypes showed a bias towards being longer as the severity of COVID-19 increases. Our findings may provide new clues for understanding COVID-19 immunopathogenesis and help identify optimal biomarkers for new therapeutic strategies.

Indexed as

COVID-19SARS-CoV-2Single-Cell AnalysisAdultAgedBiomarkersCD8-Positive T-LymphocytesFemaleHumansLeukocytes, MononuclearMaleMiddle AgedSeverity of Illness IndexT-Lymphocytes, RegulatoryBiomarkersCOVID-19Disease progression stage specificImmune landscapeScRNA-seqScV(D)J-seq

Identifiers

PMID40796616
PMCPMC12343939

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.