# DATA MANAGEMENT AND ANALYSIS RESEARCH CORE

> **NIH NIH U19** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2021 · $71,209

## Abstract

CORE C ABSTRACT - Data Management and Analysis Research Core
 The purpose of this core is to manage and support the resources to address fundamental questions
about the role of respiratory syncytial virus (RSV) on childhood respiratory morbidity and asthma. This data
management and analysis core will serve to manage the data from the two human study populations for
Project 1 and 2: Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure (INSPIRE)
and Childhood Allergy and the Neonatal Environment (CANOE), the experimental data, and the proposed
animal studies in Project 2. It will also serve to oversee the analyses for this proposal. The combination of data
management and analysis centered within one core allows for the oversight of the complex human, biosample
and experimental data to be used in this proposal, and the integrated collaboration of the biostatistical team in
the proposed analyses, and thus builds synergy for the projects 1 and 2 that this core serves. The research
team has a successful track record of working with the types of complex data generated in these projects and
conducting the proposed biostatistical analyses. This core assembles a complementary research team of
biostatisticians, geneticists, systems biologists, bioinformatics and database management staff along with the
data management and state of the art analytical skills necessary to successfully conduct the proposed studies.
 The two major functions of this core, data management and data analysis are outlined in two
separate aims or functions of this core: 1) Management and integration of clinical, physiological,
immunologic, microbiome, airway epithelial cell, genetic and epigenetic data from collaborating sites with
a central infrastructure that facilitates the proposed research. This includes ensuring subject-level data
quality control of primary clinical data collection, the pre-analytical variables and biospecimen processing
and performance of assays with validated standard protocols that minimize errors in reproducibility, and
efficient organization of samples and data among all research centers. 2) Integration of analytic support
for the conduct of the proposed rigorous biostatistical analyses that address research questions across
projects 1 and 2. This includes ensuring integration of the biostatistical team with the scientific cores,
creating derived and imputed variables, developing shared analytic datasets for specific projects to be
disseminated to the biostatistical leads on each aim, and conducting and implementing the proposed
rigorous statistical methodology. This is a natural extension of the work of our experienced biostatistical
team who have been integrated into each of the projects, and who will oversee the proposed analyses.

## Key facts

- **NIH application ID:** 10262869
- **Project number:** 2U19AI095227-12
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Tebeb Gebretsadik
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $71,209
- **Award type:** 2
- **Project period:** 2011-08-04 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10262869

## Citation

> US National Institutes of Health, RePORTER application 10262869, DATA MANAGEMENT AND ANALYSIS RESEARCH CORE (2U19AI095227-12). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10262869. Licensed CC0.

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