Alzheimer's disease (AD) is an age-related neurodegenerative disease characterized by progressive cognitive decline and dementia. Although the mechanisms underlying AD are still largely unknown, it is clear that aging of the brain is a key risk factor for this disease. Several lines of evidence indicate that microglia, the myeloid immune cells of the brain, play a crucial role in the processes involved in normal aging of the central nervous system and development of AD. Recent genetic studies have identified over twenty novel AD risk loci, and network analysis have shown that a major part of these loci play a role in the myeloid immune system. In addition, gene expression changes have been found in microglia of aged individuals, subjects with AD and in microglia in mice models for AD. How these microglia changes contribute to AD is not yet clear. Answering this question is an important step towards understanding the mechanisms involved in AD. In addition, this could lead to unravelling novel targets for treatment of AD and related neurodegenerative disorders. The long-term goal of this project is to deepen our insight into the role of microglia cells in AD and to identify microglia-related targets for treatment of age-related disorders of the central nervous system. An important first step towards reaching this goal is to understand what the changes that have been found microglia in AD tell us in terms of changes in gene and protein expression and functions. The overall objective of this study is therefore to identify the AD-associated common genetic variants that alters microglia gene expression at baseline and in response to inflammatory stimuli. By combining the unique expertise of the two PIs in the isolation and culture of human microglia, as well as advanced computational genomics analysis of human myeloid immune cells.
In Aim 1, we will use 264 existing microglia samples that we have previously isolated of different regions of 103 brain donors to generate genotype and transcriptome profiles. By combining these data with existing microglia transcriptomic datasets, we will be able to generate a map of how AD-associated genetic loci influence gene expression (or expression quantitative trait loci, eQTL) and splicing (sQTL).
In aim 2, we will use interferon (IFN) stimulated microglial samples that we have previously collected to characterize how AD-associated risk variants alter IFN-stimulated transcriptome changes. These profiles will be validated in new microglia transcriptomes from an independent cohort of 15 donors to determine the response of these samples to interferon and A? and sort subsets with different phagocytic capacity. The transcriptome profiles and expression and splicing QTL that will be generated in these two aims will be made publically available and we will apply these profiles to very large available gene datasets on aged and AD brain tissue and peripheral monocytes to investigate how gene expression changes relate to changes in microglia function. Together, we expect that this study will provide key information bridging AD genetics to molecular mechanisms in microglia, setting the stage for future mechanistic studies in model systems.
The premise of this application is that microglia plays an important role in brain in Alzheimer's disease (AD) but a clear scientific gap exists in our understanding how microglia contribute to these processes at the functional level. The long-term goal of this project is to deepen our insight into the role of microglia cells in AD and to identify microglia-related targets for treatment of the disease. If successful, discoveries from this study will provide a foundation for more ambitious plans to identify potential mechanisms and modulating factors for the increased risk of neurodegenerative disease.
