# Transcriptomics to define biomarkers of neonatal vaccine immunogenicity

> **NIH NIH U19** · BOSTON CHILDREN'S HOSPITAL · 2020 · $124,723

## Abstract

Project Summary
Here we propose to utilize Network Biology methods to identify transcriptomic signatures that correlate with
protective responses to immunization and characterize the pathways, hubs, and key mediators associated with
effective neonatal immunization. The immune system is complex and comprises 1,500 to 5,000 individual gene
products, as well as epigenetic events, miRNAs, posttranslational modifications, etc. Furthermore it is well
recognized that the immune system is integrated with multiple physiologic systems, and is influenced by
genetics, age, nutritional status, gender, environment and underlying diseases or health. Studying individual
genes, proteins, pathways and/or cell types to understand immune processes has provided us with an
incomplete picture of the intricacies of the cellular processes that take place in both health and disease. Thus
understanding how individuals respond to immune challenge, for example vaccination, requires a more holistic
systems-level approach. We have developed a substantial collection of skill sets and tools to enable
consideration of all gene expression events occurring in the blood of newborns/infants (and/or adults), and
ways of bioinformatically handing these data to enable network-oriented insights while considering all factors
(termed meta-data, and including demographics and differences in clinical assessments) that might act as
confounding variables. In particular we will use Network Biology to understand the impact of vaccination on
immune status and ultimately what factors determine the relative success of vaccination in individuals. Our
Transcriptomics Service Core (SC1) will develop transcriptomic data using the next generation sequencing
method of RNA-Seq. Downstream analyses will utilize our customized databases and analysis tools. InnateDB
is our popular (>6 million hits) open-source database and systems biology analysis platform of all the genes,
proteins, contains experimentally validated molecular interactions, and pathways in innate immune responses
of humans and other species. In addition we will apply our newest tool, the NetworkAnalyst platform, which
features statistical, visual and network-based approaches for meta-analysis and systems-level interpretation of
transcriptomic, and proteomic data. NetworkAnalyst delivers extremely fast network layouts, hub analysis and
visualization enabling unbiased examination of large transcriptomic datasets as protein-protein interaction
networks. Mining of the information for subnetworks, hubs and pathways permits unique insights into data and
value-added insights into differences due to experimental conditions and stimuli. Critically, we have already
de-risked all procedures for this project including sample collection, transport from remote locations, RNA-Seq
and downstream bioinformatic analysis and have already demonstrated our ability to develop new
insights/hypotheses into the potential mechanisms driving vaccine-induced neonatal r...

## Key facts

- **NIH application ID:** 9822173
- **Project number:** 5U19AI118608-04
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Robert Ernest William Hancock
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $124,723
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9822173

## Citation

> US National Institutes of Health, RePORTER application 9822173, Transcriptomics to define biomarkers of neonatal vaccine immunogenicity (5U19AI118608-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9822173. Licensed CC0.

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