# Core C: Data Management and Statistical Core

> **NIH NIH P30** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $492,821

## Abstract

CORE C: DATA MANAGEMENT AND STATISTICAL CORE
Abstract
The Data Management and Statistical Core (DMSC) will play a critical role in the activities and productivity of
the Michigan ADCC. Supporting the ADCC’s central theme, which emphasizes the non-β amyloid factors
contributing to brain dysfunction and degeneration and seeks to understand early events in the progression
from normal cognition to dementia, the DMSC will ensure that the ADCC database effectively and efficiently
synthesizes data coming from multiple sources. These include genetic, neuropathologic, imaging (e.g.,
magnetic resonance imaging, magnetic resonance spectroscopy, positron emission tomography), and
lipidomics, as well as clinical and neuropsychological data. In collaboration with the other cores, the DMSC will
(1) provide integrated HIPAA- and IRB-compliant data for researchers, (2) review, ensure quality-control, and
upload error-free data to the NACC for broad sharing among the AD and dementia research community, (3)
develop, refine, and apply predictive Big Data analytic approaches in dementia research data, (4) perform
thoughtful and thorough statistical analyses and provide consultations at every stage of Center-wide and
collaborative projects, and (5) work closely with the Research Education Component (REC) to assist, train and
support junior faculty members in becoming independent investigators by providing an enriched learning
environment to increase their statistical and research skills. Corresponding to these areas of importance, the
DMSC proposes five Specific Aims: Aim 1: Provide an integrated, user friendly and secure data management
platform for ADCC and collaborating researchers; Aim 2: Collaborate with the National Alzheimer’s
Coordinating Center (NACC) and related centers; Aim 3: Emphasize research on predictive Big Data analytics;
Aim 4: Provide data analysis and consultation at every stage of research projects; and Aim 5: Provide an
enriched educational environment for ADCC investigators to expand their statistical knowledge. Our original
Longitudinal Cohort data was successfully transferred to a secure REDCap system in 2011 as our Center and
DMSC moved to new leadership, which allowed us to continue successfully uploading data to the NACC.
Communication and collaboration across the three universities comprising the Michigan ADCC will be
enhanced by a newly funded NSF initiative, Multi-Institutional Open Storage Research InfraStructure (MI-
OSiRIS), to develop a distributed, multi-institutional storage infrastructure linking the three universities. With
our highly experienced DMSC leadership team and associated bioinformatics investigators, the DMSC is
exceptionally well-equipped to ensure that the Michigan ADCC makes seminal contributions to innovative
research, outreach and training across the region and nationally.

## Key facts

- **NIH application ID:** 9980248
- **Project number:** 5P30AG053760-05
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** HIROKO Hayama DODGE
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $492,821
- **Award type:** 5
- **Project period:** — → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9980248

## Citation

> US National Institutes of Health, RePORTER application 9980248, Core C: Data Management and Statistical Core (5P30AG053760-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9980248. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*