Alzheimer?s Disease (AD) is a major aging-related neurological disorder that afflicts roughly 5.3 million Americans, with total US annual costs of ~ $226 billion. Despite intensive efforts to characterize the regulation of pathological processes of AD, particularly the generation of ?-amyloid plaques, current interventions aimed at blocking ?-amyloid aggregation have only modest effects on clinical symptoms, suggesting that new approaches to find risk factors independent of ?-amyloid aggregation should be investigated, particularly to identify proximal causes of the disease. Genetic studies in model organisms have demonstrated that evolutionarily conserved pathways modulate aging, and interventions that target these pathways can dramatically extend mammalian healthspan and lifespan. C. elegans has been at the forefront of model organism longevity studies, revealing new genes, pathways, and molecular mechanisms that regulate the rate of aging and age-related declines, including cognitive decline. In parallel, Genome-wide association (GWAS) studies have implicated a role for gene regulatory changes as a risk factor for AD. AD risk variants in gene regulatory regions may dysregulate context-specific transcriptional outputs, contributing to susceptibility to AD independent of the regulation and generation of ?-amyloid plaques. Our hypothesis is that by defining a cell?s gene regulatory networks during aging and in genetically predisposed AD neuropathological states, it will be possible to both infer the environmental signals the cell receives and explain its resulting program of gene expression. These age- dependent transcriptional changes may be conserved in neurons across evolutionary time scales, and may contribute to cognitive decline in the model system C. elegans, as well. We will leverage the strengths of this model system (simple genetics, short lifespan, rapid aging, functional assays of learning and memory, and transcriptional analysis of isolated neurons), combined with data from genomic and genetic studies of AD and experimental results from human neuronal cells, to identify shared gene regulatory networks that may contribute to the susceptibility to AD. These genes and gene networks will provide important new targets for pharmaceutical interventions for the onset and progression of Alzheimer?s Disease.

Public Health Relevance

The loss of cognitive function with the onset of dementia, and in particular Alzheimer?s Disease (AD), is one of the most devastating, expensive, and widespread consequences of aging. Despite decades of research, at this point, no preventions or cures have been developed for AD, and costs of caring for patients with AD have risen with the US population?s rising average age. To increase the chance of developing effective therapeutics, new approaches to find risk factors independent of ?-amyloid aggregation should be investigated. To identify potential new targets for therapeutic intervention, we will combine information from human genome-wide association studies of AD, which indicate that gene regulatory changes underlie genetic AD risk, with studies of the powerful genetic model system, C. elegans, which we have shown to exhibit cognitive decline and evolutionarily conserved neuronal gene expression. Using the tools we have developed to study learning and memory in worms and to identify gene expression changes in worm neurons, we will identify genes that change with age that are also risk factors for AD, and we will test those genes for their roles in learning and memory and its decline with age in both worms and in human neuronal cells derived from AD patients. This approach will reveal new candidates for therapeutic intervention for the treatment of AD.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
1RF1AG057341-01
Application #
9414234
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Kohanski, Ronald A
Project Start
2017-09-15
Project End
2022-06-30
Budget Start
2017-09-15
Budget End
2022-06-30
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Albert Einstein College of Medicine, Inc
Department
Type
DUNS #
079783367
City
Bronx
State
NY
Country
United States
Zip Code
10461