Evidence map›Paper›PMID 34250342›Full record

ArticleACS omega2021

SOD1 is a Possible Predictor of COVID-19 Progression as Revealed by Plasma Proteomics.

Benhong Xu, Yuxuan Lei, Xiaohu Ren, Feng Yin, Weihua Wu, Ying Sun, Xiaohui Wang, Qian Sun, Xifei Yang, Xin Wang and 4 more

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Hepatic Anti-Oxidative GenesAntioxidants (Basel, Switzerland) · 2023
    Article
  5. Article
  6. Article
  7. Article
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 at 3 institutions in 1 country.

Benhong XuShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Yuxuan LeiShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Xiaohu RenShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Feng YinState Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
Weihua WuShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Ying SunShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Xiaohui WangShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Qian SunShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Xifei YangShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.ORCID https://orcid.org/0000-0002-9000-7016
Xin WangShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Renli ZhangShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Zigang LiState Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, China.ORCID https://orcid.org/0000-0002-3630-8520
Shisong FangShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.
Jianjun LiuShenzhen Center for Disease Control and Prevention, Shenzhen 518055, China.ORCID https://orcid.org/0000-0002-9662-8294
Shenzhen Center for Disease Control and Prevention · CNPeking University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a worldwide health emergency. Patients infected with SARS-CoV-2 present with diverse symptoms related to the severity of the disease. Determining the proteomic changes associated with these diverse symptoms and in different stages of infection is beneficial for clinical diagnosis and management. Here, we performed a tandem mass tag-labeling proteomic study on the plasma of healthy controls and COVID-19 patients, including those with asymptomatic infection (NS), mild syndrome, and severe syndrome in the early phase and the later phase. Although the number of patients included in each group is low, our comparative proteomic analysis revealed that complement and coagulation cascades, cholesterol metabolism, and glycolysis-related proteins were affected after infection with SARS-CoV-2. Compared to healthy controls, ELISA analysis confirmed that SOD1, PRDX2, and LDHA levels were increased in the patients with severe symptoms. Both gene set enrichment analysis and receiver operator characteristic analysis indicated that SOD1 could be a pivotal indicator for the severity of COVID-19. Our results indicated that plasma proteome changes differed based on the symptoms and disease stages and SOD1 could be a predictor protein for indicating COVID-19 progression. These results may also provide a new understanding for COVID-19 diagnosis and treatment.

Identifiers

PMID34250342
PMCPMC8247781
OpenAlexW3173271658

What OpenQuestion 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 OpenQuestion graph.