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Updated: Jan 9, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Systematic annotation and analysis of susceptibility genes associated with vaccine adverse events
Qingyun Song1, Jun Su1, Chenchen Pan1
1School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Nanan District, Chongqing, 400065, China.
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.
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