i.vacc

Individualized Vaccination

Paving the way towards individualized vaccination

Exploring multi-omics big data in the general population based on a digital mHealth cohort

Rationale
Novel vaccines for an increasing number of pathogens are becoming available. Yet, there is a natural limit to effectiveness, safety and acceptability with regard to combining vaccines and adding new ones to existing vaccination schedules. Therefore, vaccination schedules need to become more individualized to address this challenge and optimize their efficiency.

Objectives
The aim of the i.Vacc project is to identify new multi-omics profiles for susceptibility to respiratory infections that have a higher predictive value than existing stratifications for vaccination recommendations and that provide a conceptual basis for personalized vaccination strategies. The study is designed to target influenza infections with particular variability in host susceptibility, pathogen antigen profile and ranging vaccine effectiveness. The study will also include other respiratory viral infections and susceptibility to infections in general. We aim at complementing GNC data with genomics and proteomics to predict susceptibility to respiratory infections, using machine learning approaches, and at exploring the predictive potential of further molecular biomarkers, using sorted immune cell populations and high-resolution interaction proteomics. We expect that biomarkers identified in this project and validated in clinical studies will be instrumental in advancing personalized vaccine strategies. Furthermore, this study will support future translation of the PIA application from the research follow-up to extra-mural clinical patient monitoring (e.g. immunosuppressed patients).

Study Design
The project uses data from the German National Cohort (GNC) (see also our study center in Hannover), specifically from the subcohort ZIFCO (see also www.info-pia.de).

Principal Investigators

• Gerard Krause (Coordinator; Epidemiology, German National Cohort (NAKO), digital mHealth), Department of Epidemiology, HZI
• Alice McHardy (Bioinformatics), Department of Computational Biology for Infection Research, BRICS – Braunschweig Integrated Centre of Systems Biology
• Lothar Jänsch,( Proteomics), Research Group Cellular Proteome Research, HZI
• Thomas Illig (Genomics), Department of Human Genetics, Medical School Hannover
• Frank Klawonn (Biostatistics), Institute for Information Engineering, Ostfalia University of Applied Sciences

HZI-Project Partners        

• Carlos A. Guzmán (Vaccinology)
• Peggy Riese (Vaccinology)
• Stephanie Trittel (Vaccinology)
• Gisa Gerold (Functional proteomics)
• Andreas Bremges (Bioinformatics)
• Tobias Kerrinnes (NAKO)
• Yvonne Kemmling (NAKO)
• Stefanie Castell (Epidemiology, NAKO)

Funding
The project is funded by the Lower Saxony Ministry for Science and Culture within the framework of the call for proposals "Big Data in the Life Sciences of the Future" from funds of the Lower Saxony "Vorab".