Histopathology, Neuroimaging and Mechanism of Myelin Damage in Aging Monkey Brain

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): We will use the rhesus monkey as a model of normal aging as it is free from neurodegenerative disease but does show age-related cognitive declines in cognitive function that begin by 13 years of age (humans ~ 39) and accelerate after 20 (humans > 60). Examining the neural bases of this cognitive aging, we found that cortical neurons are not lost but instead, major pathology occurs in myelinated fibers of the white matter as seen in the electron microscope (EM) and in MR imaging. Though the relationship of MRI markers to EM markers is unknown, both are strong predictors of cognitive aging. Importantly the causes of myelin damage are unknown. One hypothesis is that damage is caused by age-related oxidative stress. A novel corollary hypothesis is that this damage is magnified by age-related reductions in myelin repair. We will explore both hypotheses in two cohorts of behaviorally tested male and female monkeys that range from young adults (~5) to the elderly (>20). The first cohort consists of 24 monkeys that will be behaviorally tested and their brains analyzed for this study. The second consists of archived tissue samples and associated data from 31 monkeys used in prior studies. Data on these 55 monkeys will include cognition, MRI scans, BrdU labeling, CSF samples and serum samples. In Aim 1, we will quantify myelin pathology in brain using immunohistochemistry with an antibody to damaged myelin (EP) and assess its relationship to other pathology (e.g. lipid peroxidation) using multilevel immunofluroescence. To identify other potentially causal factors, samples of CSF, serum and brain will be analyzed biochemically with cytokine arrays. In Aim 2, multi-label immunofluorescence with BrdU and markers of mature and immature oligodendroglia will assess the capacity to maintain and repair myelin. In Aim 3, sections processed with EP will be co-registered to MRI scans that yield measures of white matter volume and myelin pathology (e.g. fractional anisotropy) to validate how well these MRI measures reflect tissue constituents. Finally, all measures will be analyzed to determine which best predict cognitive aging. This will enable future studies to target experimental treatments at specific processes of myelin damage and use validated MRI measures to follow their effects.