Research in our laboratory focuses on dementia (Alzheimer’s disease & frontotemporal dementia) and addiction (alcohol dependence). In each of these projects our goal is to understand the molecular basis of disease in order to identify novel targets for therapeutic development. We use genetic and genomic approaches to identify susceptibility alleles, this work includes genome wide association studies and whole genome/exome sequencing in families multiply affected by disease and in case control cohorts. Since 2013 and the discovery of TREM2 as an AD risk factor (Guerreiro et al., 2013) we have focused on the role of myeloid cells in the genetics of AD. This has recently resulted in a paper (Huang et al., 2017) linking a network of AD risk genes to another myeloid expressed gene, SPI1. We have also pioneered the use of endophenotypes to uncover both risk and protective alleles in both our Alzheimer’s disease and our alcoholism studies. Our functional analyses are aimed at validating these and other genes identified in the genetic studies. We are using induced pluripotent stem cells from individuals with known genetic causes of disease in order to model the effects of these mutations in disease relevant cell types and performing in vivo analyses in collaboration with Drs. Edoardo Marcora and Anne Schaefer.
Genetic studies of Alzheimer's disease and related dementias
Identification and characterization of AD risk networks using multi-dimensional “omics” data
Genome-wide association, whole genome/exome sequencing and gene network studies have already enabled researchers to identify twenty loci influencing Alzheimer’s disease (AD) risk and another half dozen genes carrying specific rare variants that influence disease risk. With the new whole-genome sequence (WGS) and whole-exome sequence (WES) data from 10,000+ AD cases and controls from the ADSP, combined with mRNA expression data from 3,500+ individuals from AMP, it is now possible to develop a more comprehensive picture of the genetic architecture of AD and associated risk. Beyond refining AD genetic architecture, our goal is to identify and validate therapeutic targets for AD by identifying genes that functionally drive or protect from AD and interrogating their respective gene networks for therapeutic targets. We will do this using the largest, most comprehensive data set, to date. Genetic and pathway-based analyses have strongly implicated a small number of networks including immune response, phagocytosis, lipid metabolism and endocytosis. We will integrate data from genetic studies and gene expression/regulation studies to identify risk and resilience genes to pinpoint key networks that functionally drive AD development and progression. We will take two complementary approaches to identify risk and resilience AD genes: (1) we will use a family-based approach to identify both risk and protective alleles using publicly available data and our own WGS/WES data from both NIALOAD and Utah families; and (2) we will use publicly available high-dimensional molecular data from AD cases and controls to construct global interaction and causal networks. We will then focus our analysis of ADSP case control sequence data on the most compelling networks, thereby reducing our search space and increasing power. To identify therapeutic targets, we will use network analysis to test known drugs that target networks identified in our sequence analysis of both family-based and case control data. We will then validate our findings by performing in vitro experiments based our in silico observations and determine the functional consequences of risk/resilience alleles identified from the AD sequence data. Together, the findings from this study will pinpoint key networks that functionally drive AD and will provide critical insight into therapeutic intervention.
Modifier Genes that influence age at onset or protect against development of AD
Although most cases of Alzheimer’s disease (AD) have an age at onset above age 80yrs the range in age at onset is huge with the earliest ages at onset occurring in individuals as young as the third decade of life while other individuals may live beyond one hundred years and remain cognitively normal. Even within specific risk groups, for example presenilin (PSEN) mutation carriers or Apolipoprotein E e4 carriers (APOE4), the range in age at onset can vary by several decades. Individuals from an extended Colombian kindred, who develop AD, all carry the PSEN1-E280A variant but the range in age at onset in this family has been reported to span three decades (35-62yrs) (Lendon et al., 1997). Similarly, individuals who carry an APOE4 allele may develop AD as early as 50 yrs while other individuals with this risk factor may be cognitively normal and older than 80yrs of age (Corder et al., 1993). We hypothesize that in human populations there are both risk and protective alleles that influence the age at onset of AD. Support for this hypothesis comes from our knowledge of the known AD genes. APOE and amyloid precursor protein (APP) have both risk and protective alleles for AD. In the case of APOE these alleles are common (APOE4-risk; APOE2-protective), whilst in APP risk and protective alleles appear to be rare (Goate and Hardy, 2012; Jonsson et al., 2012a).
Suppressor and enhancer screens have been used successfully to identify modifiers of genetic phenotypes in yeast, Drosophila, the mouse and more recently in humans. The hypothesis driving the current proposal is that genetic variation that has arisen over the course of human population history provides a natural source of genetic modifiers. The goal of this study is to use genome-wide association data, exome chip data and whole genome/exome sequence data from unrelated individuals to identify novel genetic modifiers that accelerate disease or protect against development of AD.
Understanding the mechanism of SPl1 dependent Alzheimer disease risk
The primary goal of this project is to understand how variation within the SPI1 locus influences Alzheimer’s Disease (AD) risk. Recently, genetic and molecular evidence has implicated myeloid cells in the etiology of AD, including our finding that AD risk alleles are enriched for cis-eQTL effects in monocytes but not CD4+ T-lymphocytes. Our studies have identified SPI1 as a novel risk factor for Alzheimer’s disease, and that there are four non-coding variants that constitute the most likely functional variants, either individually or in combination. We have shown computationally and experimentally that SPI1, which codes for the transcription factor PU.1, regulates expression of many other AD risk factor genes including CD33, MS4A4A, MS4A6A, TYROBP, APOE, CLU. Indeed, genes regulated by PU.1 are highly enriched for AD risk loci suggesting that this network is a potential therapeutic target for AD prevention drugs. We are pursuing cell culture and animal models to determine the impact of variation in expression of SPI1 on global gene expression in microglia, function of microglia and AD pathology in mouse models.
Identification of Novel Alzheimer’s Disease Genes Using Next Generation Sequencing
Genetic studies of AD had identified mutations in the amyloid-beta precursor protein (APP) presenilin (PSEN1) and presenilin 2 (PSEN2) genes cause Mendelian forms of AD. These mutations have been found in a small number of people, but the identification of such mutations and genes provided a better understanding of the biology of AD. More recent studies using genome-wide association studies (GWAS) approaches in late onset AD have identified more than thirty loci that influence risk for AD. For some of these loci genetic variants in specific genes have been identified, but for the majority of these loci the disease gene remains to be identified. The goal of this project is to use genetic and genomic approaches to identify functional networks enriched for AD risk and protective loci, and to use this information to determine how myeloid cellular function is impacted by these genetic factors in disease-relevant cell types. The ultimate goal is to use this information to identify drugs that target these networks and to test the drugs in appropriate cellular models. During the last three years we have revealed substantial evidence to support the hypothesis that many AD risk genes operate within an inter-connected network that modulates myeloid cell function. We plan to extend this work to more fully characterize the affected network(s) using bioinformatics and to validate our findings through experimental approaches in BV2 cells and human induced pluripotent stem cells (hiPSC)-derived microglia.
Understanding the mechanism of MS4A-dependent AD risk
A major obstacle for the translation of Late onset AD (LOAD) GWAS data into an actionable (from a drug discovery perspective) understanding of disease etiology is not only the increased complexity of the genetic architecture of LOAD compared to autosomal-dominant AD, but also the fact that (with a few exceptions) the causal genes are much more difficult to identify unequivocally. Indeed, most genetic variants associated with LOAD don’t occur within genes but instead fall into non-coding regions of the genome that modulate the expression of one or more genes in specific cell types. By applying novel computational and statistical methods for integrated analyses of human genetics and genomics datasets, we have identified strong candidate genes, biochemical pathways and cellular processes. In particular, we have discovered that variants in most of the LOAD GWAS loci function to modulate the expression of genes that play important roles in cells of the myeloid lineage, such as monocytes and macrophages (including microglia), the professional phagocytes of the innate immune system. Several of these candidate genes (together with well-validated LOAD genes like APOE, TREM2 and ABCA7) cluster around the phagocytic clearance of lipid-rich cellular debris (hereafter referred to as efferocytosis), a core and evolutionarily conserved function of myeloid cells that is essential for the maintenance of tissue homeostasis, immune tolerance, and the resolution of inflammation.
A recent publication indicated that members of the MS4A family are lipid sensors in the olfactory system. This observation led us to proposed that the MS4A genes linked to AD could be lipid sensors for microglia, potentially unifying them with the efferocytosis hypothesis. The goal of this research is to identify candidate the causal gene(s) in the MS4A cluster (an AD-associated locus) and to investigate their role in AD pathogenesis for the development of therapeutic agents.
Genomic approach to identification of microglial networks involved in Alzheimer’s disease risk
The goal of this project is to use genetic and genomic approaches to identify functional networks enriched for Alzheimer’s disease (AD) risk and protective loci, and to use this information to determine how cellular function and physiology is impacted by these genetic factors in disease-relevant cell types and animal models. Initial analyses of both genome-wide association data and whole genome sequencing data provide substantial evidence to support the hypothesis that many AD risk genes operate within one or more inter-connected networks that modulate myeloid cell function. As part of this application we plan to extend this work to more fully characterize the affected network(s) by analyzing the largest GWAS and WGS datasets to date and integrating this data with macrophage and monocyte gene expression and epigenomic data. Further we will validate our findings through experimental approaches in iPSC-derived microglia/macrophages and an animal model.
Dominantly Inherited Alzheimer Network – genetics of early onset AD
DIAN is a multi-center observational study of autosomal dominant AD. In addition to longitudinal clinical, neuroimaging and fluid biomarker data we have genetic data on the entire cohort. We are using this data to identify genetic variants that modify phenotypic expression of disease in these families.
Genetics of Progressive Supranuclear Palsy and Related Neurodegenerative Diseases (Tauopathies)
The overall aim of this project is to study genetic risk factors for Progressive Supra Nuclear Palsy (PSP) and related disorders (tauopathies). Several neurodegenerative disorders, including PSP and Parkinson’s disease are associated with a large inversion in the genome sequence on chromosome 17, that includes the MAPT locus. The goal of this study is to identify the specific DNA sequences associated with these disorders and determine why they increase risk for disease. Importantly, although the same haplotype is associated with increased risk in each of these disorders we do not know whether they represent pleiotropy (same risk allele different phenotypes) or whether different risk alleles exist on a common haplotype leading to different disorders. We are using long-read sequencing of DNA and RNA from people with these disorders to generate more accurate maps of this structurally complex genetic locus. In addition to genetic studies we are using iPSC systems to understand the functional consequences of disease risk variation in MAPT and other genes within this locus. This research will deepen our understanding of PSP and associated conditions, and could eventually lead to new therapies for these devastating disorders.
Addiction: Collaborative study on the genetics of alcoholism (COGA)
Collaborative Study on the Genetics of Alcoholism
The Collaborative Study on the Genetics of Alcoholism (COGA) is a tightly integrated, multifaceted and interdisciplinary project, with three overarching goals: to identify and characterize genes in which variations confer risk for (or protection from) the development of alcohol use disorders (AUDs) and related phenotypes; to understand the mechanisms by which these variants work at the molecular and cellular level; and to understand how genetic, environmental, and neurocognitive factors interact to influence the developmental trajectories of alcohol use and AUDs through an ongoing prospective study of at-risk individuals.
To accomplish these goals, COGA has assembled a team spanning a broad range of expertise, recruited a unique sample of large, ethnically diverse families densely affected by AUDs and a set of comparison families, and is carrying out a Prospective Study of adolescents and young adults from these families to elucidate how genetic risk unfolds across development against a background of documented environmental factors. We will continue our successful efforts to study a wide range of alcohol-related phenotypes, including neurophysiological endophenotypes, to maximize our power to detect novel variants/genes across the allelic spectrum. We will study the mechanism of action of newly identified genes to better understand how they affect risk and examine how the variants identified in one generation affect important precursor phenotypes and developmental trajectories during the critical adolescent/young adult phase of the next generation. At the same time, we will also explore how gender, ethnicity and environmental factors interact with these variants to moderate their effect on outcomes.
The overarching specific aims of the molecular genetics component for the next five years of COGA are:
- To identify additional genes that contribute to the risk for AUD and related phenotypes
- To explore mechanisms of action of key genes
- To examine the effects of genes and environmental factors on clinical and neurophysiological phenotypes related to the vulnerability for risky drinking, AUDs and SUDs across adolescence and young adulthood.
COGA also plays a major role in The Psychiatric Genomics Consortium’s Substance Use Disorders (PGC-SUD) Working Group and led the largest GWAS meta-analysis of alcohol dependence diagnosis.
“Election to the National Academy of Medicine is considered one of the highest honors in medicine,” says Dennis S. Charney, MD, the Anne and Joel Ehrenkranz Dean of the Icahn School of Medicine at Mount Sinai. “The election of Drs. Goate and Richardson is a notable achievement and well-deserved recognition of each of their leadership efforts and important contributions to their particular fields of study.” Read More.
Huang et al. A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease
A genome-wide survival analysis of 14,406 Alzheimer’s disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. Read More.
TCW et al. An Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells.
Growing evidence implicates the importance of glia, particularly astrocytes, in neurological and psychiatric diseases. Here, we describe a rapid and robust method for the differentiation of highly pure populations of replicative astrocytes from human induced pluripotent stem cells (hiPSCs), via a neural progenitor cell (NPC) intermediate. Read More.
Microglial cell function is implicated in the etiology of Alzheimer’s disease by human genetics. In this issue of Immunity, Krasemann et al. (2017) describe a gene expression signature associated with an APOE- and TREM2-dependent response of microglia to brain tissue damage that accumulates in aging and disease, defining an axis that might be amenable to therapeutic targeting. Read More.
Meet the Team
Merck’s Director of Neuroscience Matthew Kennedy shares why these early results have him feeling hopeful. He is joined by Alison Goate, the director of the Ronald M. Loeb Center for Alzheimer’s Disease at Mount Sinai. Read More
As the director of the Ronald M. Loeb Center on Alzheimer’s Disease at Mount Sinai, Dr. Alison Goate specializes in researching the disease’s basic mechanisms to improve our treatment options. November is National Alzheimer’s Disease Awareness Month. Read More
Alzheimer's Association recognizes four scientists with Lifetime Achievement Awards at AAIC 2015 — July 21, 2015
The Alzheimer’s Association recognizes four leading scientists for their contributions to advancing Alzheimer’s disease and dementia research. The awards were presented during the opening session at the Alzheimer’s Association International Conference® 2015 (AAIC® 2015) in Washington, D.C. Read More
Scientists have identified early genetic markers that can potentially predict who is at an increased risk for developing Alzheimer’s, Medical Daily reported.Currently, in order to determine if someone will develop Alzheimer’s disease, doctors use tests that analyze the amount of Tau protein buildup in the central nervous system. The more Tau in an individual’s system, the more likely he or she will progress towards dementia. Read More