Ontology-supported Integrative Analysis and Visualization of Vaccine-induced Pathways and Networks

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Project Summary: Although vaccination has dramatically protected humans against various infectious diseases, there are still many deadly diseases that do not have corresponding vaccines. For rational vaccine development, it is crucial to identify the fundamental host immune mechanisms against infectious pathogens under different conditions. ImmPort is the world's largest repository for publicly de-identified clinical trial data related to immunology. The secondary analysis of the ImmPort vaccine research data across different studies to identify vaccine-induced immune effectors and related pathways given specific conditions would allow us to better understand molecular mechanisms of vaccine-host interactions and support rational vaccine design. As preliminary data, we have developed the first web-based vaccine immune effector database VaximmutorDB that has manually collected and annotated over 1,700 vaccine immune effector genes identified from peer- reviewed publications. We have also initiated the development of community-based Vaccine Ontology (VO) and Vaccine Investigation Ontology (VIO), which will facilitate vaccine-related data and metadata standardization, integration and analysis. In addition, together with other groups we have developed a pathway knowledge base called Reactome, containing many pathways related to infectious diseases and host immune responses, and pathway visualization tools that are being used in the Reactome website as well as a Cytoscape app. In this project, we aim to further develop the VO and VIO, apply ontology-based integrative approaches to systematically represent, standardize, process, and analyze vaccine-related gene expression data from different experimental studies, identify core and differential vaccine-induced immune effectors, pathways and networks under specific experimental conditions (e.g., vaccine type, host cell, vaccination route), establish an ontology-based vaccine immune effector knowledge base, and develop visualization tools to better query and analyze the secondarily analyzed vaccine immunological data. The influenza and yellow fever vaccine studies will be emphasized as driving use cases. New ontology-based statistical methods will be developed and applied. In addition to the scientific insights obtained from this study, the resulting ontology-based tools and methods will significantly support immunology data standardization, representation, visualization, and analysis.