Evidence map›Paper›PMID 40416973›Full record

ArticleFrontiers in immunology2025

Reduced immune response to SARS-CoV-2 infection in the elderly after 6 months.

Qin Luo, Qinqin Song, Yan Li, Kexin Zong, Ti Liu, Junming He, Guoyong Mei, Haijun Du, Zhiqiang Xia, Mi Liu and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

19 authors.

Qin Luo *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qinqin Song *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yan Li *Shandong Center for Disease Control and Prevention, Shandong Provincial Key Laboratory of Intelligent Monitoring, Early Warning, and Prevention and Control of Infectious Diseases, Shandong Institute of Preventive Medicine, Jinan, China.
Kexin ZongDepartment of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Ti LiuShandong Center for Disease Control and Prevention, Shandong Provincial Key Laboratory of Intelligent Monitoring, Early Warning, and Prevention and Control of Infectious Diseases, Shandong Institute of Preventive Medicine, Jinan, China.
Junming HeBeijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Guoyong MeiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Haijun DuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhiqiang XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Mi LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Juan SongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Chen GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dong XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Guangyu XueNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Wenyan TianNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yinli QuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zengqiang KouShandong Center for Disease Control and Prevention, Shandong Provincial Key Laboratory of Intelligent Monitoring, Early Warning, and Prevention and Control of Infectious Diseases, Shandong Institute of Preventive Medicine, Jinan, China.
Zhongjun DongThe First Affiliated Hospital of Anhui Medical University and Institute of Clinical Immunology, Anhui Medical University, Hefei, China.
Jun HanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To evaluate the immune persistence and cross-immune response of elderly individuals after Omicron BA.5 infections. Method: The neutralizing antibodies against WT, BA.5, XBB.1 and EG.5 strains were analyzed. The T/B-cell subsets' responses were tested through intracellular cytokine staining and flow cytometry. Results: The neutralizing antibodies titers against WT and BA.5 strain, remaining high level for at least 6 months, were higher than that of both XBB.1 and EG.5 variants. The neutralizing antibodies of WT, BA.5, XBB.1, and EG.5 strains in the elderly were slightly lower than those in middle-age. The memory B cells decreased rapidly in the elderly, and Tfh, Th17 cells of the elderly continued to increase for only 3 months, while Tfh and Th17 cells increased in the middle-aged for over 6 months. For the elderly, after peptide stimulation, unswitched/switched memory B cells decreased, while double negative B cells displayed higher proliferation. The proportions of both naïve and Temra cells in CD4 Conclusions: Omicron BA.5 infection induced lower neutralizing antibodies against XBB.1 and EG.5 variant. The decrease of memory B cells, CD69

Indexed as

Antibodies, NeutralizingAntibodies, ViralCOVID-19SARS-CoV-2AgedAged, 80 and overB-LymphocytesFemaleHumansImmunologic MemoryMaleMemory B CellsMiddle AgedTh17 CellsAntibodies, NeutralizingAntibodies, Viraladaptive immunityelderlyneutralizing antibodyomicron BA.5T cell

Identifiers

PMID40416973
PMCPMC12098630

What OpenQuestion holds

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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.