Genomic approach to identification of microglial networks involved in Alzheimer disease risk

点击翻译按钮获取中文摘要

Project Summary Alzheimer's disease (AD) is the only disease among the top ten killers in the U.S. without a disease modifying therapy. Genetic studies provide a powerful means to identify genes and pathways that are causally linked to disease etiology. Technological advances have substantially reduced the cost of genomic analyses enabling the generation of large publicly available datasets that can be integrated to perform multi-scale analyses. Hypotheses generated from these data can then be validated in cell and animal models. A major problem encountered by genome-wide studies is power, particularly when searching for rare variants. One approach to this problem is to perform gene-based or gene-set-based analyses. Over the last three years it has become apparent that AD risk loci (both common and rare variants) are enriched for myeloid cell expressed genes, including APOE, TREM2, CD33, SORL1, ABCA7. Microglia are the resident phagocytic cells of the brain and share a common embryonic lineage with peripheral myeloid cells. We propose to use genomic and functional approaches to test the hypothesis that microglial function is modulated by AD risk and protective alleles in genes that are enriched within specific functional networks. This proposal will use publicly available whole genome/exome sequence data generated by the Alzheimer's Disease Sequencing Project (ADSP) and genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) and others together with gene expression data from purified macrophages and monocytes to identify myeloid expressed genes that carry rare or common variants that influence risk for AD (Aim 1). By integrating this data into co-expression networks in monocytes and macrophages we will determine whether AD loci lie within one or more regulatory networks (Aim 1). To validate these networks and determine the functional consequences of risk/protective alleles we will perform global transcriptomics and ATACseq in parallel with functional assays in microglial cells derived from isogenic human iPSC cell lines and mouse BV2 microglial cells, in which candidate gene expression is knocked-down or mutations are knock-in (Aim 2). Finally, we will use in vivo knock-down of gene expression specifically in adult microglia to test the physiological consequences of disrupting an AD-linked functional network (Aim 3). To enable these studies, we have developed a novel mouse model that can be used to profile the ribosome-bound transcriptome of microglial cells in the brain while also conditionally and specifically down-regulating the expression of a gene of interest like MS4A6A in microglia. Using the same model crossed with an AD mouse model, we will investigate AD-related outcomes like micro-gliosis and ß-amyloid deposition in the context of reduced MS4A6A expression in microglia. Together these studies will not only further our understanding of the genetic architecture of AD but also provide key information regarding the molecular mechanisms, setting the stage for novel therapeutic development.