The overall theme of this new project is to establish and validate blood- and imaging-based biomarkers associated with the risk and progression of late onset Alzheimer's disease (LOAD), mild cognitive impairment (MCI) and the rate of cognitive decline in late life. We also propose to develop a framework with which we can understand how biomarkers interact and how they fit into the temporal sequence from healthy aging to dementia. This proposal is built on two decades of epidemiological research and systematic data collection in the multi-ethnic, Washington Heights, Hamilton Heights, Inwood, Columbia Aging Project (PO1AG07232). Over the past 20 years, we have investigated the rates of LOAD, MCI and cognitive decline in this urban community in northern Manhattan. We have investigated environmental, health-related and genetic risk factors of disease and predictors of disease progression by collecting longitudinal data on cognitive performance, emotional health, independence in daily activities, blood pressure, anthropometric measures, cardiovascular status and selected biomarkers in this elderly, multi-ethnic cohort, including lipids, amyloid peptides, sex hormones, homocysteine, insulin and C-reactive protein (CRP), and MRI. We have reported that the rates of disease and the frequency of disease risk factors vary across ethnic groups. We have identified one of the largest, multi-ethnic groups of incident LOAD cases facilitating studies of disease progression. Clinical and genetic data as well as biological resources are present for several thousand individuals. Biomarkers, cellular, biochemical or molecular alterations measurable in human tissues, cells, or fluids or by radiological means, are typically chosen because they are directly or indirectly in the causal pathway of disease. The emergence of structural and functional brain imaging has revolutionized epidemiological studies, particularly those using biomarkers for Alzheimer's disease. Positron emission tomography brain imaging using 11C Pittsburgh compound B is considered an in vivo measure of brain amyloid plaque load, while structural MRI, especially changes in brain volume and cerebral blood flow (CBF), can be considered an in vivo measures of neurodegeneration. In this new proposal, we will focus this longitudinal investigation on two sets of blood biomarkers that not only show consistent and robust associations to the risk of LOAD, MCI and cognitive decline, but that address the putative mechanisms related to amyloid burden and insulin resistance. We will take full advantage of the prospective design in this multi-ethnic cohort and the clinical, biological and brain imaging data collected to address six major hypotheses. The first two primary specific aims consider blood biomarkers as not only predictors of cognitive decline, MCI, LOAD and LOAD progression, but also as intermediate steps in the disease pathway, including neurodegeneration and cerebrovascular burden (MRI) and amyloid plaque load (PIB). In the last primary specific aim, brain imaging variables are predictors and cognitive decline, MCI, LOAD as well as LOAD progression are main outcomes.

Public Health Relevance

There is general agreement that developing biomarkers that measure the risk of cognitive decline, LOAD and related diseases as well as the rate of disease progression would greatly enhance clinical, epidemiological, and pharmacological research. Furthermore developing biomarkers that can be easily obtained using standard and acceptable medical procedures such as blood samples or brain imaging would facilitate their use in developing methods to delay or prevent disease in the general community. Therefore the potential public health impact of developing reliable and valid biomarkers in a multi-ethnic community is a major benefit of this proposed investigation.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
Project #
Application #
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Anderson, Dallas
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Columbia University (N.Y.)
Schools of Medicine
New York
United States
Zip Code
Vivot, Alexandre; Power, Melinda C; Glymour, M Maria et al. (2016) Jump, Hop, or Skip: Modeling Practice Effects in Studies of Determinants of Cognitive Change in Older Adults. Am J Epidemiol 183:302-14
Tsapanou, Angeliki; Gu, Yian; O'Shea, Deirdre et al. (2016) Self-Reported Sleep Disordered Breathing as Risk Factor for Mortality in the Elderly. J Stroke Cerebrovasc Dis 25:1524-31
Hohman, Timothy J; Cooke-Bailey, Jessica N; Reitz, Christiane et al. (2016) Global and local ancestry in African-Americans: Implications for Alzheimer's disease risk. Alzheimers Dement 12:233-43
Zahodne, Laura B; Schupf, Nicole; Brickman, Adam M et al. (2016) Dementia Risk and Protective Factors Differ in the Context of Memory Trajectory Groups. J Alzheimers Dis 52:1013-20
Tsapanou, Angeliki; Gu, Yian; O'Shea, Deirdre et al. (2016) Daytime somnolence as an early sign of cognitive decline in a community-based study of older people. Int J Geriatr Psychiatry 31:247-55
Tosto, Giuseppe; Bird, Thomas D; Bennett, David A et al. (2016) The Role of Cardiovascular Risk Factors and Stroke in Familial Alzheimer Disease. JAMA Neurol 73:1231-1237
Gu, Yian; Vorburger, Robert S; Gazes, Yunglin et al. (2016) White matter integrity as a mediator in the relationship between dietary nutrients and cognition in the elderly. Ann Neurol 79:1014-25
Zahodne, Laura B; Manly, Jennifer J; Azar, Martina et al. (2016) Racial Disparities in Cognitive Performance in Mid- and Late Adulthood: Analyses of Two Cohort Studies. J Am Geriatr Soc 64:959-64
Chouraki, Vincent; Reitz, Christiane; Maury, Fleur et al. (2016) Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease. J Alzheimers Dis 53:921-32
Vorburger, Robert S; Habeck, Christian G; Narkhede, Atul et al. (2016) Insight from uncertainty: bootstrap-derived diffusion metrics differentially predict memory function among older adults. Brain Struct Funct 221:507-14

Showing the most recent 10 out of 121 publications