Implicating novel microglial mechanisms of late-onset Alzheimer's disease with variant-to-gene mapping methods

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ABSTRACT Late-onset Alzheimer’s disease (LOAD) is the most common neurodegenerative disease among the elderly population, affecting nearly 6 million US adults over the age of 65. Despite being the 6th leading cause of death in the US, there are still no effective therapies that can slow or halt disease progression. The prevailing molecular feature that differentiates LOAD from other types of neurodegenerative dementia is the extracellular aggregation of inappropriately cleaved amyloid-b protein plaques (Ab1-42) in the brain. In response to Ab1-42 production, microglia, the resident macrophages of the central nervous system (CNS) activate and migrate to the site of plaque accumulation, and then break down and phagocytose the plaques, while also secreting pro-inflammatory cytokines to stimulate the innate immune response. Persistent production of these cytokines reduces microglial ability to clear Ab1-42 in a negative feedback loop, and results increased formation of interfibrillary tangles in the neurons that exacerbates neurodegeneration. Large genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) that associate with LOAD and reside near genes with known rare coding variants that affect microglial function, further emphasizing the importance of microglia in LOAD pathology. However, while GWAS has successfully identified numerous genetic loci associated with LOAD, it cannot directly identify the causal SNP implicated by these loci, as a GWAS sentinel SNP is representative of an entire haplotype of SNPs. Additionally, the majority of these GWAS SNPs lie within non-coding regions of the genome, and may not necessarily implicate the nearest gene as causal. Instead, these SNPs likely regulate the expression of LOAD-associated genes by modulating the activity of distal regulatory elements, such as enhancers, which in turn regulate LOAD gene expression. Therefore, I hypothesize that LOAD GWAS SNPs contribute to the dysregulated inflammation and phagocytosis in the brains of LOAD patients by altering the regulatory activity of microglial enhancers and the expression of their linked effector genes. In Aim 1, I will utilize a “variant-to-gene mapping” approach to identify putatively causal LOAD GWAS SNPs in the microglia by identifying SNPs that lie within open chromatin, are enriched in marks of active enhancers, and function as expression quantitative trait loci in microglial cell models. I will validate the activity of these enhancers through luciferase assays in the microglial cell models, and I will also identify the likely effector genes whose expression are modulated by these enhancers through our lab’s promoter-focused Capture-C assay. In Aim 2, I will functionally validate the phenotype conferred by LOAD-associated microglial enhancers by knocking out these enhancers in microglial cell models using CRISPR, and then assessing how these knockouts impact global gene expression, inflammation, and phagocytosis. Taken together, these aims will provide insight into microglial genetic mechanisms of LOAD, and may lead to the development of new therapies that can cure or prevent the disease.