| dc.description.abstracteng | The phenomenon of population aging, caused by increased life expectancy and declining birth rates, has resulted in a high, and continuously rising proportion of elderly people in the population. This means it is critical to improve our understanding of age-associated diseases and to develop new therapies for them. One of the conditions most commonly associated with aging is a decline in memory, which occurs at different rates in elderly individuals. At one end of the spectrum are cognitively healthy individuals who retain good memory capacities in old age. On the other are patients who suffer from Alzheimer’s disease and suffer a sharp decline in cognitive capabilities, with memory usually being one of the earliest-affected functions. There relationship between the various kinds of age-associated memory impairment and the degree to which they share molecular mechanisms is unclear. The aim of the experiments described in this thesis is to gain an understanding of age-associated memory impairment and Alzheimer's disease by studying RNA expression profiles.
Cellular RNA undergoes constant turnover, being transcribed, translated and degraded at varying rates. It thus provides a dynamic index of cellular status, being required for housekeeping functions as well as response to stimuli, stress or changes in the cellular environment. A learning stimulus is associated with a change in expression levels of large number of genes, and learning is impaired in the absence of these gene expression changes. In addition to protein-coding genes, there are a number of regulatory RNAs that likely play a role in the process, but their functions are not yet clear. Thus studying the coding and non-coding RNA under situations of disease or impaired function gives an insight not only into cellular protein expression but also into the regulatory or compensatory mechanisms that occur in response to stimuli or to disease. Clearly, the RNA profile of a cell at any given time depends both on the underlying genome and on the environment of the cell, allowing the study of their interaction. For these reasons, next generation RNA sequencing, followed by analysis of coding and non-coding RNA expression profiles was the method chosen for the study.
The first major aim of this project was to develop a mouse model that the inter-individual variation in age-associated memory impairment. We show that wild type mice show an age-dependent increase in intra-group variability that parallels the decline in memory. Thus, as in humans, a group of aging mice consists of some individuals who perform well on memory tests, at levels comparable to young mice and a some individuals who decline faster. These differences cannot be attributed to loss of motor or visual abilities and individual mice show remarkable consistency in day-to-day performance. This means that by testing over a number of days on the water maze task, ‘good learners’ can be distinguished from ‘poor learners’. This model was set up in a group of genetically identical wild-type mice which had been raised in the same environment, enabling us to study the hippocampal gene expression profiles and correlate them with memory performance in the absence of confounding factors. A large number of genes were found to have a significant correlation with performance, and a gene set enrichment analysis was performed on this dataset to look for functions or pathways that were over- or under-represented in the best- and worst-performing individuals. We found that high expression of the components of the translational machinery, including ribosomes, RNA-binding proteins, and translation initiation factors were associated with good memory performance in aging. Another finding was that high expression of components of the glutamatergic pathway was associated with age-associated memory impairment. These pathways merit further investigation as potential therapeutic targets in age-associated memory impairment.
Alzheimer's disease, a condition that has a very strong connection with aging, is one of the age-associated diseases for which no effective therapies exist. One possible reason for this is that our knowledge about the underlying molecular mechanisms is still incomplete, relying mainly on the pathological evidence of amyloid-beta accumulation and to genetic linkage studies. However, the majority of patients with AD suffer from a sporadic form of the disease, with the strongest risk factor being age. There is still no clear explanation for this strong relationship between aging and AD. While aging is often associated with a mild degree of memory loss, the rapid decline characteristic of Alzheimer’s disease is probably associated with distinct pathomechanisms.
Since the current methods to study the living brain in AD are limited to neuroimaging approaches, our knowledge of RNA expression in AD comes from post-mortem analyses and mouse models. In particular, we lack methods to study the progress of AD in live patients in the early stages of disease. Recently, it has been shown that cells secrete RNA into the extracellular space, enclosed in vesicles. If this RNA can be isolated and profiled from cerebrospinal fluid, it could serve as a “nanobiopsy” for brain tissue.
Thus the second major aim of this project was to determine if extracellular RNA isolated from cerebrospinal fluid could be used to help understand the underlying molecular mechanisms in live patients with AD. To this end, we isolated the vesicle fractions from human cerebrospinal fluid and tested for RNA yield. We were able to obtain a robust and reproducible RNA expression profile from CSF extracellular vesicles (EVs) that was distinct from the cellular RNA profile. Primary hippocampal neurons in culture were used to compare the RNA derived from EVs with the RNA in the neurons of origin. Interestingly, when the cells were challenged by application of amyloid-beta, there was a detectable response in the secreted vesicular RNA.
Before using this method to study CSF from patients with AD, the scalability of the RNA isolation and profiling protocol was tested for the small amounts of RNA typically available from 1‒2 ml of CSF. We show that it is possible to distinguish between subjects using as little as 0.25 ng of cerebrospinal EV-derived RNA.
Finally we compared EV RNA between the cerebrospinal fluid of patients with Alzheimer's disease and control subjects. One potential application of CSF RNA profiling is the development of biomarkers that allow early disease diagnosis. We used a machine learning approach to predict AD based on CSF microRNA and other non-coding RNA and were able to achieve a prediction accuracy of over 80%. If these findings can be extended to a larger set of patients, RNA isolated from cerebrospinal fluid could provide a new method not only for further research into early Alzheimer's disease, but also be useful as a diagnostic marker. | de |