Evidence map›Paper›PMID 41361427›Full record

ArticleBMC medical genomics2025

Systematic annotation and analysis of susceptibility genes associated with vaccine adverse events.

Qingyun Song, Jun Su, Chenchen Pan, Xue Zhang, Bingjian Yang, Yongqun He, Jiangan Xie

Abstract read
In one paragraph

Article in BMC medical genomics, 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

7 authors.

Qingyun Song *School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China.
Jun Su *School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China.
Chenchen PanSchool of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China.
Xue ZhangSchool of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China.
Bingjian YangDepartment of Computational Medicine and Bioinformatics, University of Michigan Medical School, Room A317A, MSRB III, 1150 W., Ann Arbor, MI, 48109, USA.
Yongqun HeDepartment of Computational Medicine and Bioinformatics, University of Michigan Medical School, Room A317A, MSRB III, 1150 W., Ann Arbor, MI, 48109, USA. yongqunh@med.umich.edu.
Jiangan XieSchool of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China. xjahardy@hotmail.com.

Funding

National Natural Science Foundation of China 61801067Natural Science Foundation of Chongqing of China CSTC2018JCYJAX0243STI 2030-Major Projects 2022ZD0211400
6 · The paper itself

Abstract

Susceptibility genes, including single-nucleotide polymorphisms (SNPs) in the DNA sequences, genetically predispose certain individuals to developing adverse events (AEs) following vaccination. Such AEs are often undetected in initial clinical safety trials during vaccine licensing evaluations. Therefore, a comprehensive understanding of susceptibility genes is crucial for vaccine development, safety monitoring, and precision immunization. VaegenDB is a web-based centralized database and analysis system designed for managing, storing, and analyzing susceptibility genes associated with vaccine AEs. Basic information on these genes and supporting evidence are curated from peer-reviewed literature, while more detailed gene, AE, and vaccine data are automatically extracted from existing databases such as RefSeq and VIOLIN using in-house scripts. Currently, VaegenDB contains information on 160 susceptibility genes linked to 151 AEs and 86 vaccines. The system offers a user-friendly web interface that enables interactive querying and visualization of susceptibility genes. Bioinformatics analyses using VaegenDB reveal that a single susceptibility gene may harbor multiple genetic variations, one vaccine can be associated with several AEs, and a single AE may be influenced by multiple genes or SNPs. In addition, KEGG and GO enrichment analyses were employed to identify gene signatures-including functional annotations, mutation types, and expression patterns-associated with adverse reactions. The construction of this database and subsequent bioinformatics analyses help clarify enriched gene profiles and underlying mechanisms of vaccine-related AEs, thereby supporting rational vaccine design and advances in precision medicine.

Indexed as

Genetic Predisposition to DiseaseMolecular Sequence AnnotationVaccinesComputational BiologyDatabases, GeneticHumansInternetPolymorphism, Single NucleotideVaccinesAdverse eventBioinformatics analysisDatabaseOntologyPrecision medicineSusceptibility geneVaccine

Identifiers

PMID41361427
PMCPMC12817545

What Socratic 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 Socratic graph.