Evidence map›Paper›PMID 35958562›Full record

ArticleFrontiers in immunology2022

Longitudinal Serum Proteome Characterization of COVID-19 Patients With Different Severities Revealed Potential Therapeutic Strategies.

Songfeng Wu, Yuan Xu, Jian Zhang, Xiaoju Ran, Xue Jia, Jing Wang, Longqin Sun, Huan Yang, Yulei Li, Bin Fu and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 15% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  8. Article
  9. The Impact of Serum/Plasma Proteomics on SARS-CoV-2 Diagnosis and Prognosis.International journal of molecular sciences · 2024
    Review
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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

13 authors at 5 institutions in 1 country.

Songfeng WuState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Yuan XuDepartment of Clinical Laboratory, Chongqing General Hospital, Chongqing, China.
Jian ZhangState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Xiaoju RanState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Xue JiaState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Jing WangDepartment of Clinical Laboratory, Chongqing Public Health Medical Center, Southwest University Public Health Hospital, Chongqing, China.
Longqin SunBeijing Qinglian Biotech Co., Ltd, Beijing, China.
Huan YangDepartment of Clinical Laboratory, Chongqing General Hospital, Chongqing, China.
Yulei LiSavaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
Bin FuState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Changwu HuangDepartment of Clinical Laboratory, Chongqing Fifth People's Hospital, Chongqing, China.
Pu LiaoDepartment of Clinical Laboratory, Chongqing General Hospital, Chongqing, China.
Wei SunState Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
Beijing Proteome Research Center · CNFirst People's Hospital of Chongqing · CNAffiliated Hospital of North Sichuan Medical College · CNSouthwest University · CNUniversity of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic caused by SARS-CoV-2 is exerting huge pressure on global healthcare. Understanding of the molecular pathophysiological alterations in COVID-19 patients with different severities during disease is important for effective treatment. In this study, we performed proteomic profiling of 181 serum samples collected at multiple time points from 79 COVID-19 patients with different severity levels (asymptomatic, mild, moderate, and severe/critical) and 27 serum samples from non-COVID-19 control individuals. Dysregulation of immune response and metabolic reprogramming was found in severe/critical COVID-19 patients compared with non-severe/critical patients, whereas asymptomatic patients presented an effective immune response compared with symptomatic COVID-19 patients. Interestingly, the moderate COVID-19 patients were mainly grouped into two distinct clusters using hierarchical cluster analysis, which demonstrates the molecular pathophysiological heterogeneity in COVID-19 patients. Analysis of protein-level alterations during disease progression revealed that proteins involved in complement activation, the coagulation cascade and cholesterol metabolism were restored at the convalescence stage, but the levels of some proteins, such as anti-angiogenesis protein PLGLB1, would not recovered. The higher serum level of PLGLB1 in COVID-19 patients than in control groups was further confirmed by parallel reaction monitoring (PRM). These findings expand our understanding of the pathogenesis and progression of COVID-19 and provide insight into the discovery of potential therapeutic targets and serum biomarkers worth further validation.

Indexed as

COVID-19HumansPandemicsProteomeProteomicsSARS-CoV-2ProteomeCOVID-19heterogeneityprogressionproteomicsserumseverity

Identifiers

PMID35958562
PMCPMC9361788
OpenAlexW4288039680

What OpenQuestion holds

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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.