Evidence map›Paper›PMID 40788170›Full record

ArticleMicrobiology spectrum2025

Humoral response dynamics following inactivated SARS-CoV-2 vaccination and their association with subsequent infection and symptoms in individuals with and without prior SARS-CoV-2 infection: evidence from Sichuan Province, China.

Yunhan Yu, Mengmeng Jia, Jingchuan Zhong, Luzhao Feng, Xiaoman Jiang, Yanan Li, Qiangru Huang, Yuezhu Chen, Xinming Wang, Yong Yue and 4 more

Abstract read
In one paragraph

Article in Microbiology spectrum, 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

14 authors.

Yunhan Yu *Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Science, Chengdu, China.ORCID 0000-0002-6809-5929
Mengmeng Jia *National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-8175-7181
Jingchuan Zhong *NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Luzhao FengSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xiaoman JiangChengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Science, Chengdu, China.
Yanan LiNHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Qiangru HuangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yuezhu ChenChengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Science, Chengdu, China.
Xinming WangNHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yong YueChengdu High-Tech Zone Center for Disease Control and Prevention, Chengdu, China.
Li GuoKey Laboratory of Pathogen Infection Prevention and Control (Ministry of Education), State Key Laboratory of Respiratory Health and Multimorbidity, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xian LiangChengdu Center for Disease Control and Prevention, Chengdu, China.ORCID 0009-0001-6140-2180
Lili RenKey Laboratory of Pathogen Infection Prevention and Control (Ministry of Education), State Key Laboratory of Respiratory Health and Multimorbidity, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0003-0249-481X
Weizhong YangSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0009-0003-7240-0898

Funding

Chinese Academy of Medical Sciences 2022-12M-CoV19-004
6 · The paper itself

Abstract

This study integrated multisource longitudinal data with trajectory modeling to delineate the heterogeneity of humoral immune dynamics induced by inactivated SARS-CoV-2 vaccinations and their clinical implications for subsequent SARS-CoV-2 infection outcomes in 205 individuals from Sichuan Province, China. We found that preexisting infection status served as the dominant stratifier of antibody trajectory divergence across the cohort. Additionally, among individuals without prior infection before the vaccine cohort, we identified five distinct immune response patterns with clinical implications. An age-associated "minimal response" subtype was associated with an increased risk of prolonged recovery time, sore throat, and limb pain in subsequent infections. In contrast, a subtype characterized by a marked increase in S-Igs titers after the booster dose exhibited fewer symptoms, with a lower likelihood of experiencing fever and fatigue. What is more, for those with prior infection, clinical data-including viral shedding duration and total antibody levels 15 days after discharge from the initial infection-could provide valuable insights into the subsequent risk of reinfection. IMPORTANCE: To better identify vulnerable populations in epidemic surveillance and predict their clinical manifestations post-infection for accurate diagnosis and effective management, it is vital to understand the intrinsic dynamic immune patterns among individuals and how these trajectory patterns relate to future infections and associated symptoms. In the post-COVID-19 era, conducting nuanced analyses remains of great significance, especially as longer-term observational data become available. This is the first finding from China that illustrates the dynamic characteristics of the immune response following inactivated COVID-19 vaccination over an extended observation period, including information on following infection and symptoms. These data are particularly valuable as no participants experienced COVID-19 infection during the vaccine cohort follow-ups, meaning their antibody levels solely reflect the intrinsic dynamic immune patterns triggered by the inactivated COVID-19 vaccines.

Indexed as

COVID-19COVID-19 VaccinesImmunity, HumoralSARS-CoV-2AdolescentAdultAgedAntibodies, ViralChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedVaccinationVaccines, InactivatedAntibodies, ViralCOVID-19 VaccinesSARS-CoV-2 inactivated vaccinesVaccines, Inactivateddynamic immune patternshumoral immunityinactivated vaccinationreinfectiontrajectory analysis

Identifiers

PMID40788170
PMCPMC12502705

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.