Evidence map›Paper›PMID 40100292›Full record

ArticleArchives of virology2025

Humoral immune response characteristics of vulnerable populations against SARS-CoV-2 strains EG.5 and JN.1 after infection with strains BA.5 and XBB.

Huan Zhang, Shi Ouyang, Yunyun Qu, Zhuolin Li, Yushan Jiang, Tingting Peng, Guangyan Yang, Tao Chen, Baisheng Li, Chenguang Shen and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of virology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Huan Zhang *Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China.
Shi Ouyang *Department of Infectious Diseases, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Yunyun Qu *The Second Affiliated Hospital of Shandong, University of Traditional Chinese Medicine, Jinan, China.
Zhuolin LiBSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
Yushan JiangBSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
Tingting PengDepartment of Infectious Diseases, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Guangyan YangJinan Central People's Hospital, Jinan, Shandong, China.
Tao ChenThe Second Affiliated Hospital of Shandong, University of Traditional Chinese Medicine, Jinan, China. 13869187232@163.com.
Baisheng LiGuangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China. libsn@126.com.
Chenguang ShenBSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China. a124965468@smu.edu.cn.ORCID http://orcid.org/0000-0001-8607-3750
Wei ZhaoGuangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China. zhaowei@smu.edu.cn.

Funding

National Natural Science Foundation of China 32170939 and 82371846
6 · The paper itself

Abstract

In this study, we compared the humoral immune characteristics of children, elderly individuals, and pregnant women in Guangzhou, China, who had been infected with the SARS-CoV-2 strains BA.5 and XBB against the currently predominant strains EG.5 and JN.1. It was discovered that the neutralizing antibody titers in children, elderly individuals, and pregnant women against strains EG.5 and JN.1 were low in individuals who had been infected with strain BA.5, irrespective of their vaccination status. There was a significant positive correlation between the neutralization titers against JN.1 and EG.5 in both the acute and convalescent phases of BA.5 infection. For XBB-infected patients, the sera in the acute stage exhibited a low neutralizing titer against EG.5 and JN.1, whereas the convalescent sera demonstrated a significantly higher neutralizing titer against the two viruses, particularly in infected individuals who had been vaccinated. For XBB-infected patients, there was a strong positive correlation between the serum neutralizing antibody titers against EG.5 and JN.1 in both the acute and recovery phases. This finding provides crucial information for judging the epidemic trend of COVID-19 and the development of vaccines, especially for developing customized vaccines and immune strategies for different populations.

Indexed as

Antibodies, NeutralizingAntibodies, ViralCOVID-19Immunity, HumoralSARS-CoV-2AdolescentAdultAgedChildChild, PreschoolChinaCOVID-19 VaccinesFemaleHumansInfantMaleAntibodies, NeutralizingAntibodies, ViralCOVID-19 Vaccines

Identifiers

PMID40100292

What OpenQuestion holds

Textmetadata
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.