Increasing the Generalization Capability of Biomarkers Through Systems Biology Malaria Vaccines Case Study
Finding biomarker combinations is a difficult task. As a problem with a large number of solutions, they usually lack generalization power. One example is the fact that a surrogate biomarker of immunity has been difficult to achieve for malaria and other complex diseases through classical immunological assays. Within the context of SysMalVac, a project partially funded by the European Seventh Framework Programme (FP7) [1], Anaxomics proposed to use Systems Biology in order to analyse two malaria vaccination models (the RTS,S vaccine and the CPS immunization strategy) in order to identify combinatorial biomarkers of protection. The aim of the project is to design a tool able to predict whether a person will be protected from malaria after vaccination. The prediction is achieved through the development of mathematical models including newly generated cellular transcriptome profiles, immunological read-outs and transcriptomic results from both trials, and experimental data obtained from non-human primates. This analytical tool will not also predict each individual’s protection, but will also allow identifying a biomarker signature indicative of protection to malaria.
[1] The SysMalVac Consortium. SysMalVac. 2013 [cited 2014 11 July 2014]; Available from: http://www.sysmalvac.eu/
[1] The SysMalVac Consortium. SysMalVac. 2013 [cited 2014 11 July 2014]; Available from: http://www.sysmalvac.eu/