PI: Helena Chui
Institution: University of Southern California


The USC Alzheimer’s Disease Research Center (ADRC) has three overarching goals: 1) to elucidate vascular contributions to Alzheimer’s disease (AD); 2) to catalyze local research, including clinical trials in AD at USC; and 3) to contribute expertise in vascular disease and imaging to national collaborative initiatives. To this end, the ADRC is recruiting and new longitudinal vascular cohort, who will undergo lumbar puncture, blood draws, cognitive assessments and brain scans to assess brain structure, function, connectivity, and blood brain barrier integrity. In this collaboration between the LONI P42 and ADRC projects, we will develop novel image analysis and data management techniques, including automated quality control tools that will improve statistical power to detect effects in this longitudinal study. These tools will advance the discovery of vascular and metabolic contributions to AD, and will facilitate re-use of these data in complementary future studies of AD risk. The ADRC grant includes funding of 2-3 pilot projects per year and a brain donation program/Neuropathology Core, which characterizes and shares biospecimen and provides a comprehensive panel of CSF biomarkers. It also includes the outreach and recruitment of a new vascular cohort, which will undergo brain scanning by the ADRC Imaging Core, led by Drs. Toga, Law, and Thompson. Projects 1 and Project 2 share a complementary focus on the role of Neurovascular and Metabolic Factors on AD pathogenesis, thereby giving scientific cohesiveness to the Center as a whole. The Data core (Toga) makes available the imaging, biomarker, and clinical-pathological data from ADRC participants online and without embargo. Thus, the USC ADRC is prepared to serve as the nexus for translational research at USC and to bring unique resources to the national ADC research enterprise. The databasing, automatic quality control, and visualization tools of LONIR will facilitate the management of this longitudinal data and re-use for future Alzheimer’s disease related projects. The innovative connectomic analysis tools will allow us to better evaluate how white matter tract microstructure may relate to vascular and metabolic risk in non-demented older adults.