Evidence map›Paper›PMID 34667241›Full record

ArticleScientific reports2021

Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach.

Yayoi Kimura, Yusuke Nakai, Jihye Shin, Miyui Hara, Yuriko Takeda, Sousuke Kubo, Sundararaj Stanleyraj Jeremiah, Yoko Ino, Tomoko Akiyama, Kayano Moriyama and 14 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% of its field
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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 64 citations in OpenAlex.

  1. Pooled it
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  12. The Impact of Serum/Plasma Proteomics on SARS-CoV-2 Diagnosis and Prognosis.International journal of molecular sciences · 2024
    Review
  13. Review
  14. Plasma Proteins Associated with COVID-19 Severity in Puerto Rico.International journal of molecular sciences · 2024
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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

24 authors at 3 institutions in 1 country.

Yayoi KimuraAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Yusuke NakaiAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Jihye ShinAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Miyui HaraDepartment of Biostatistics, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Yuriko TakedaDepartment of Biostatistics, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Sousuke KuboDepartment of Microbiology, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Sundararaj Stanleyraj JeremiahDepartment of Microbiology, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Yoko InoAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Tomoko AkiyamaAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Kayano MoriyamaAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan.
Kazuya SakaiSchool of Medicine Medical Course Emergency Medicine, Yokohama City University, Yokohama, 236-0004, Japan.
Ryo SajiSchool of Medicine Medical Course Emergency Medicine, Yokohama City University, Yokohama, 236-0004, Japan.
Mototsugu NishiiSchool of Medicine Medical Course Emergency Medicine, Yokohama City University, Yokohama, 236-0004, Japan.
Hideya KitamuraDepartment of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, 236-0051, Japan.
Kota MurohashiDepartment of Pulmonology, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Kouji YamamotoDepartment of Biostatistics, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Takeshi KanekoDepartment of Pulmonology, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Ichiro TakeuchiSchool of Medicine Medical Course Emergency Medicine, Yokohama City University, Yokohama, 236-0004, Japan.
Eri HagiwaraDepartment of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, 236-0051, Japan.
Takashi OguraDepartment of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Yokohama, 236-0051, Japan.
Hideki HasegawaInfluenza Research Center, National Institute of Infectious Diseases, Musashimurayama, Tokyo, 208-0011, Japan.
Tomohiko TamuraDepartment of Immunology, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Takeharu YamanakaDepartment of Biostatistics, Yokohama City University School of Medicine, Yokohama, 236-0004, Japan.
Akihide RyoAdvanced Medical Research Center, Yokohama City University, Yokohama, 236-0004, Japan. aryo@yokohama-cu.ac.jp.
Yokohama City University · JPKanagawa Cardiovascular and Respiratory Center · JPNational Institute of Infectious Diseases · JP

Funding

the Japan Agency for Medical Research and Development JP19fk0108110the Japan Agency for Medical Research and Development JP19fk0108169
6 · The paper itself

Abstract

The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass spectrometry (DIA-MS) to identify the serum proteins that are closely associated with COVID-19 prognosis. Twenty-seven proteins were differentially expressed between severely ill COVID-19 patients with an adverse or favorable prognosis. Ingenuity Pathway Analysis revealed that 15 of the 27 proteins might be regulated by cytokine signaling relevant to interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF), and their differential expression was implicated in the systemic inflammatory response and in cardiovascular disorders. We further evaluated practical predictors of the clinical prognosis of severe COVID-19 patients. Subsequent ELISA assays revealed that CHI3L1 and IGFALS may serve as highly sensitive prognostic markers. Our findings can help formulate a diagnostic approach for accurately identifying COVID-19 patients with severe disease and for providing appropriate treatment based on their predicted prognosis.

Indexed as

Gene Expression ProfilingBiomarkersChitinase-3-Like Protein 1COVID-19COVID-19 Serological TestingEnzyme-Linked Immunosorbent AssayGas Chromatography-Mass SpectrometryGene Expression RegulationHumansInflammationInterleukin-1betaInterleukin-6PrognosisProteomicsSARS-CoV-2Tumor Necrosis Factor-alphaBiomarkersCHI3L1 protein, humanChitinase-3-Like Protein 1IL1B protein, humanIL6 protein, humanInterleukin-1betaInterleukin-6Tumor Necrosis Factor-alpha

Identifiers

PMID34667241
PMCPMC8526747
OpenAlexW3126361432

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LicenceCC BY
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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.