South Texas Alzheimer's Disease Center Data and Statistical Management Core

The Data Management and Statistics Core (DMSC) will support the South Texas Alzheimer disease Center (STAC) with an integrated analytic information system. It has two core leads in this resubmission, a Chair of Clinical Informatics with experience in multisite collaborations, Meredith Zozus, PhD and a biostatistician, Chen Pin Wang, PhD. It includes faculty and staff who are clinical informaticians, biostatisticians, genetic statisticians, bioinformaticians, machine learning experts. The DMSC will provide comprehensive expertise, infrastructure and services for data collection, use, analysis and sharing. It provides an information highway between the STAC Cores through advanced infrastructure for daily acquisition of data and real-time exchange and use of that data. This is accomplished through decentralized data collection, centralized data integration and storage, and decentralized data use across sites and STAC cores. This information highway is built on the Informatics Data Exchange and Acquisition System (IDEAS) platform that has supported diverse multicenter studies for 16 years and is integrated with systems in use by STAC cores such as REDCap - used by all cores, especially the clinical, outreach and population neuroscience cores (CC, OREC and PNC), Freezerworks - used by the Biomarker and Neuropathology Cores (BC and NPC) and the Extensible Neuroimaging Archive Toolkit (XNAT) - managed by the imaging core (IC). IDEAS was specifically designed to integrate disparate data from multiple sources, collection points, including maintaining associations with multi-omics platforms (GMC). Cutting-edge informatics support extends to data exchange with Electronic Health Records (EHRs) such as extraction of data and facilitating referrals to the CC and NPC. Thus, information collected in one core is available to another when needed and will be used across STAC to trigger automated processes controlling data quality and process fidelity across STAC. Statistical methods will leverage extensive faculty expertise in heterogeneity characterization, outcome prediction, bioinformatics and multi-omics approaches. DMSC will support the PNC in harmonization of data from high-value Hispanic population studies, and will support STAC with curated data, sample tracking, maintaining and updating data dictionaries to support submission of data, images or samples to NACC, NCRAD and NIGADS. The aims of the DMSC are: AIM 1: Leverage Data to Optimize Key STAC Processes: Provide advanced system connectivity, automation and decision support to optimize and align focus on recruitment, retention and completeness of data and sample collection. AIM 2: Collect and Share Quality Data: Apply rigorous collection and management methods across cores and projects to ensure that data meet NACC requirements and support study conclusions and reuse. AIM 3: Provide State-of-the-Art Statistical Methods and Support: Support STAC Cores and projects with deep expertise in study design, statistical monitoring, data analyses, and result reporting. AIM 4: Educate the Next Generation of Data Savvy ADRD Researchers: Provide training and mentoring in ADRD relevant informatics and data science for STAC trainees, investigators.