Bridging Gaps to Translate Plasma Alzheimer's Disease Biomarkers to Diverse Populations

About This Grant

Project Summary/Abstract Plasma biomarkers for Alzheimer’s disease (AD) and related dementias (ADRDs) hold promise as accessible, affordable, and scalable tools for widespread use to support the detection, diagnosis, and care of patients affected by ADRDs. However, critical knowledge gaps remain in understanding plasma biomarker performance in broadly representative cohorts with the full spectrum of risk factors and systemic diseases seen in general populations to guide clinical and research use. Further, access to plasma biomarkers in sub-Saharan Africa (sSA), the region anticipated to have the fastest growth in older adults globally, remains a key barrier, and data to inform use in sSA populations is sorely lacking. The overarching research goal of this project is to address these gaps to advance plasma biomarkers towards appropriate use in populations in the US and in sSA. To do so, this proposal will leverage available data in two large, prospective population-based cohorts with available ADRD plasma biomarkers and deep-phenotyping of the full spectrum of risk factors and systemic diseases seen in the population: the Framingham Heart Study (FHS; n=2543) and the Uganda Aging Cohort Study (UACS; n=560). Specifically, Aim 1 proposes to identify demographic, lifestyle, genetic, and systemic diseases associated with elevated plasma biomarkers in population cohorts in the US and Uganda. Aim 2 will assess the validity of measuring ADRD biomarkers using dried plasma spots in Uganda as a new method to expand access to remote and resource-limited settings. Aim 3 intends to use 12-year follow-up data in the FHS to determine plasma biomarker performance in predicting incident dementia, and to develop a parsimonious ADRD risk prediction model using multimodal machine learning to optimize risk stratification in the US. In this K08 career development award, Dr. Jeremy Tanner, a behavioral neurologist and Assistant Professor at the Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases at the University of Texas Health San Antonio, proposes to use this research as a vehicle to develop translational research skills. His overarching career goal is to become a leader in the clinical translation of biomarkers to improve early detection, enable more accurate diagnosis, and guide precision care for individuals affected by ADRDs globally, including in resource-limited settings. Through the K08 award, Dr. Tanner aims to achieve these specific training objectives: 1) To develop expertise in AD fluid biomarkers; 2) To gain specialized competencies in conducting research in sSA populations and in health disparities; and 3) To acquire advanced statistical skills in (a) longitudinal data analysis and (b) applying machine learning to harness multimodal data to answer scientific questions. To achieve these goals and research independence, Dr. Tanner has assembled a stellar cross-disciplinary mentorship team of international experts in each area led by his primary mentor, Dr. Sudha Seshadri, a world leader in neuroepidemiology, biomarkers, and multimodal analyses.