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Infection is the most common cause of death in early life, especially for newborns and can be reduced by immunization but insufficient knowledge of how vaccines protect the very young limits their optimal use. To gain insight into how vaccines induce protection of the most vulnerable, this National Institutes of Health (NIH)/National Institute of Allergy & Infectious Diseases (NIAID)-funded Human Immunology Project Consortium (HIPC) study, based at Boston Children's Hospital and conducted by the Expanded Program on Immunization Consortium (EPIC), employs two novel approaches studying newborn responses to hepatitis B vaccine (HBV): (a) systems biology that uses technologies which comprehensively measure global changes in molecules such as transcriptomics (RNA) and proteomics (proteins), as well as cell composition of the blood and (b) use of human newborn blood components, collected prior to immunization, to model vaccine responses in vitro (outside the body). Characterizing vaccine-induced molecular patterns ("signatures") that correspond to vaccine-mediated protection will accelerate development and optimization of vaccines against early life infections of major global health importance.
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While the greatest number of vaccines is administered to the very young, vaccine preventable infections remain a major cause of morbidity and mortality, especially for the newborn. To improve vaccine-mediated protection early in life, the investigators will identify biomarkers that predict protective efficacy and garner insight into the underlying mechanisms of vaccine-mediated protection. Systems biology approaches ("OMICs") applied to vaccinology, i.e., systems vaccinology, has revolutionized the field with an unbiased identification of pathways relevant to vaccine-induced immune responses. However, thus far systems vaccinology has focused primarily on adults, with few studies conducted in children and infants, and none in newborns. This study will bridge this gap by conducting a comprehensive systems vaccinology study in newborns. Specifically, the investigators will determine the molecular pathways that are associated with successful neonatal immunization with hepatitis B virus vaccine (HBV). HBV is the ideal model because i) it is highly (>90%) effective; ii) it has a well-established correlate of protection (CoP; anti-hepatitis surface antigen antibody (anti-HBs)); iii) there is substantial variation in anti-HBs titers and quantifiable inter-subject variability is essential for systems biological approaches; iv) it is highly relevant as HBV is given at birth in the U.S. and most developing countries; v) it is amenable to in vivo manipulation with another regularly administered neonatal vaccine, Bacille Calmette-Guérin (BCG), which will greatly enhance detection of relevant signatures. As complex networks of functional interactions among genes and proteins drive the response to immunization, the investigators will integrate transcriptomic, proteomic and immune phenotyping approaches. Importantly, the investigators have successfully adapted these experimental platforms to be fully operational within the small blood volumes obtainable in newborns. The investigators have also developed in vitro systems amenable to experimental manipulation on the cellular and molecular level to identify cause-effect relationships. Pilot data prove feasibility of collecting the relevant high-quality samples according to stringent standard operating procedures, processing them and delivering cogent OMIC data suggesting vaccine-specific 'signatures' in the human newborn. This HIPC will identify biomarkers of neonatal HBV immunogenicity by pursuing the following Overall Specific Aims:
Overall, these integrated studies will identify vaccine-induced molecular pathways correlating with protective immune responses in newborns and will generate and test new mechanistic hypotheses regarding vaccine action in vivo and in vitro. This study will ultimately inform, accelerate and optimize early life immunization resulting in major public health benefit.
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911 participants in 4 patient groups
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Data sourced from clinicaltrials.gov
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