Evidence map›Paper›PMID 33763078›Full record

ArticleFrontiers in immunology2021

The Characterization of Disease Severity Associated IgG Subclasses Response in COVID-19 Patients.

Huanle Luo, Tingting Jia, Jiamin Chen, Shike Zeng, Zengzhao Qiu, Shu Wu, Xu Li, Yuxuan Lei, Xin Wang, Weihua Wu and 10 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

66 citing papers in PubMed, 106 citations in OpenAlex.

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6 more citing papers are in PubMed but not listed here.

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

20 authors at 4 institutions in 2 countries.

Huanle LuoSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Tingting JiaSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Jiamin ChenSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Shike ZengSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Zengzhao QiuSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Shu WuSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Xu LiSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Yuxuan LeiSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Xin WangShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Weihua WuShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Renli ZhangShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Xuan ZouShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Tiejian FengShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Ruxia DingDivision of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, China.
Yue ZhangDivision of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, China.
Yao-Qing ChenSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Caijun SunSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Tian WangDepartment of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, United States.
Shisong FangShenzhen Center for Disease Control and Prevention, Shenzhen, China.
Yuelong ShuSchool of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
Sun Yat-sen University · CNShenzhen Center for Disease Control and Prevention · CNNational Institutes for Food and Drug Control · CNThe University of Texas Medical Branch at Galveston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing evidence suggests that dysregulated immune responses are associated with the clinical outcome of coronavirus disease 2019 (COVID-19). Nucleocapsid protein (NP)-, spike (S)-, receptor binding domain (RBD)- specific immunoglobulin (Ig) isotypes, IgG subclasses and neutralizing antibody (NAb) were analyzed in 123 serum from 63 hospitalized patients with severe, moderate, mild or asymptomatic COVID-19. Mild to modest correlations were found between disease severity and antigen specific IgG subclasses in serum, of which IgG1 and IgG3 were negatively associated with viral load in nasopharyngeal swab. Multiple cytokines were significantly related with antigen-specific Ig isotypes and IgG subclasses, and IL-1β was positively correlated with most antibodies. Furthermore, the old patients (≥ 60 years old) had higher levels of chemokines, increased NAb activities and SARS-CoV-2 specific IgG1, and IgG3 responses and compromised T cell responses compared to the young patients (≤ 18 years old), which are related with more severe cases. Higher IgG1 and IgG3 were found in COVID-19 patients with comorbidities while biological sex had no effect on IgG subclasses. Overall, we have identified diseases severity was related to higher antibodies, of which IgG subclasses had weakly negative correlation with viral load, and cytokines were significantly associated with antibody response. Further, advancing age and comorbidities had obvious effect on IgG1 and IgG3.

Indexed as

AdolescentAdultAntibodies, ViralChildChinaCOVID-19CytokinesFemaleHumansImmunoglobulin AImmunoglobulin GImmunoglobulin MMaleMiddle AgedSARS-CoV-2Severity of Illness IndexAntibodies, ViralCytokinesImmunoglobulin AImmunoglobulin GImmunoglobulin Mantibody responseCOVID-19cytokine productiondisease severityhost immune responseIgG subclassesSARS-CoV-2

Identifiers

PMID33763078
PMCPMC7982848
OpenAlexW3134324254

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.