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Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small
Casey P Shannon1,2, Travis M Blimkie3, Rym Ben-Othman4,5
1Prevention of Organ Failure (PROOF) Centre of Excellence and Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, BC, Canada.
Frontiers in Immunology
|December 17, 2020
Summary
Understanding individual immune system factors before vaccination can predict vaccine effectiveness. This study reveals key molecular patterns influencing hepatitis B vaccine response, aiding future vaccine development.
Area of Science:
- Immunology
- Systems Biology
- Genomics
Background:
- Vaccination is crucial for global infectious disease control.
- Understanding molecular mechanisms of vaccine response is vital for future vaccine development.
Purpose of the Study:
- To characterize temporal molecular responses after hepatitis B virus (HBV) vaccination.
- To identify baseline molecular patterns associated with effective HBV vaccine responses.
Main Methods:
- Applied multi-omics approaches including epigenomic, transcriptomic, proteomic, and fecal microbiome profiling.
- Integrated data using NetworkAnalyst and DIABLO for network analysis.
- Correlated molecular profiles with HBV antibody titers.
Main Results:
- Uncovered baseline molecular patterns and pathways linked to HBV vaccine response.
- Identified key pre-vaccination modulators including JAK-STAT, interleukin signaling, Toll-like receptor cascades, interferon signaling, and Th17 cell differentiation.
- Demonstrated associations between molecular data and vaccine efficacy.
Conclusions:
- Individual baseline immune system characteristics significantly influence vaccine responses.
- Integrating multi-omics data provides valuable insights into vaccine immunogenicity.
- Highlights the utility of systems biology approaches for predicting vaccine success.
