Uncoupling Age- Versus Cognitive-Related Cellular Senescence in Alzheimer's Disease

阿尔茨海默病中年龄与认知相关的细胞衰老的解耦

• 批准号: 10043941
• 负责人: Sean Curtis Bendall
• 金额: $ 39.43万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10043941
• 关键词: Address; Affect; African Green Monkey; Age; Age-associated memory impairment; Aging; Alzheimer' s Disease; Alzheimer' s disease brain; American; Antibodies; Archives; Astrocytes; Automobile Driving; Axon; Biochemical; Blood Vessels; Brain; Brain Diseases; Brain imaging; Brain region; Cell Aging; Cells; Cerebellum; Cerebrum; Cessation of life; Clinical; Clinical Pathology; Cognitive; Communities; Complex; Data; Dementia; Dendrites; Disasters; Disease; Disease Marker; Family; Funding; Gold; Health Policy; Healthcare Systems; Heterogeneity; Hippocampus (Brain); Human; Image; Immune; Impaired cognition; Inferior; Infrastructure; Injury; Label; Lobule; Machine Learning; Maps; Measurement; Metabolic; Metals; Microglia; Mitotic; Modeling; Molecular and Cellular Biology; Multiplexed Ion Beam Imaging; Nerve Degeneration; Nervous System Physiology; Neurodegenerative Disorders; Neurofibrillary Tangles; Neuroglia; Neurons; Oligodendroglia; Parietal; Pathology; Pattern; Phenotype; Policy Maker; Population; Predisposition; Process; Proteins; Proteomics; Public Health; Research; Research Personnel; Resistance; Risk Factors; Running; Sampling; Senile Plaques; Severities; Specimen; Synapses; Technology; Time; Tissues; Tonsil; Validation; abeta accumulation; age related; aged; aging brain; area striata; brain tissue; cell injury; cohort; collaborative approach; deep learning; disability; entorhinal cortex; healthy aging; high dimensionality; human model; imaging platform; innovation; insight; learning strategy; loss of function; middle age; mild cognitive impairment; mind control; molecular imaging; molecular phenotype; nanometer resolution; nanoscale; neuronal cell body; neuropathology; nonhuman primate; normal aging; novel; novel imaging technique; predictive signature; prevent; programs; release factor; response; senescence; shared database; stressor; tau Proteins; therapeutic target; vervet

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is a leading cause of disability and death in the US and a major global public health problem. Time is running short if we wish to avert a global public health disaster with untold suffering, disruption of families, and severe challenges to health care systems and economies. Effectual solutions will come only from innovative research. While aging is the biggest risk factor for developing AD, it is unclear to what extent normal aging is distinct from AD and which age-related factors drive disease. Senescence is a homeostatic response, which aims to prevent the propagation of these damaged cells while they remain viable and metabolically active. Senescent-like phenotypes have been described in neurons despite neurons being post-mitotic cells and these cells may release factors that trigger senescence in surrounding glia. Senescent glia and senescent-like neurons increase in the brain with age and are thought to contribute to the loss of function associated with aging and age-related diseases like AD. Our application, entitled “Uncoupling Age- Versus Cognitive-Related Cellular Senescence in Alzheimer's Disease,” is highly responsive to the objectives outlined in the RFA-AG-20-025, by leveraging an innovative molecular imaging platform we invented at Stanford; multiplexed ion beam imaging (MIBI), in order to uncouple age- from cognitive decline-related cellular senescence. MIBI enables us to quantify, with low nanometer resolution, high-dimensional, protein-level expression patterns, single-cell (neuro/immune) interactions, and spatial localization of senescence- and AD- relevant molecules (Aim 1) in a model of healthy aging (Aim 2) and well-characterized cases of AD related cognitive impairment (Aim 3). Importantly, MIBI allows all of this to be accomplished in archival FFPE material, thus allowing retrospective analysis on a variety of existing cohorts. By creating in-depth, phenotypic cellular signatures with spatial context from our unique aging and cognitive cohorts, we will be able to provide insight for modifiable factors promoting cognitive decline by filtering those specifically associated with aging alone. In this research program, collaborative expertise in clinical neuropathology and cognitive decline, technological advancements in imaging, biochemical/molecular and cellular biology, and machine learning analytics converge in this proposed research program to address the spatio-cellular (neuro/immune, senescent) heterogeneity in non-human primate (NHP) and human models of healthy aging and AD brains. Furthermore, it will be synergistic to, and draw on expertise developed in existing infrastructure to image and organize AD clinical pathology (R01AG056287, R01AG057915, MPIs: SC Bendall, RM Angelo, TJ Montine) as well as the NIA-funded 90+ UCI cohort, control material housed in the Stanford ADRC, and NHP specimens (P50 AG047366 co-I: TJ Montine). We will reveal cellular senescent phenotypes that differentiate AD from normal age-associated senescence.

项目总结/文摘