Developing new computational strategies to understand complex genetic systems.
The Carter Lab uses data to strengthen the interface between experimental systems and common disease in humans, such as Alzheimer's and Type 2 Diabetes. We develop computational methods to analyze genetic architecture, design translatable studies of model systems, perform data alignment to precisely quantify disease relevance, and share data through open science platforms. This work involves mapping networks of interacting genes, integrating phenotypic and molecular data, critically evaluating models with experimental tests, and exploring how biological complexity is encoded in genetic data.
Our primary disease focus is leveraging genetic and genomic data to identify and test potential treatments for Alzheimer’s disease. We are using human genetics to create the next generation of late-onset Alzheimer’s disease mouse and non-human primate models. These models comprise a multi-species strategy to understand Alzheimer’s disease origins and progression in molecular and pathophysiological detail. They are designed to be preclinical platforms for the rapid validation of diagnostic biomarkers and rigorous evaluation of precision therapeutics that target the pathways that drive dementia. We also comprehensively analyze data from human and experimental studies to critically assess therapeutic hypotheses. Through this work, we are derisking molecular targets to accelerate the discovery of precise, targeted therapeutic approaches.
We are embedded in a network of collaborative projects and centers including MODEL-AD, TREAT-AD, and MARMO-AD. By integrating knowledge and standardizing analytical strategies across these research consortia, we are maximizing the translational value of computational and experimental research. We are creating data resources and analytical tools that enable researchers to rapidly and reliably test new findings across prior studies, with the goal of accelerating Alzheimer’s research by avoiding past failures and instantly reinforcing promising new discoveries.
The Carter Lab is pioneering modern approaches to Alzheimer’s disease research, including cross-species machine learning on big genomic data that leverages the power of model systems to understand the biology of the disease. We play a leading role in three major efforts: MODEL-AD, TREAT-AD, and MARMO-AD. Each of these is a multi-institutional, cross-disciplinary program with funding from the National Institute on Aging. In MODEL-AD, we are creating the next generation of mouse models for studying Alzheimer’s biology and use in preclinical testing of precision therapeutics. To date, we have created over 40 new models, over 25 of which have been aged and studied for human disease relevance. These models are based on the latest human genetic studies, which has allowed us to lead discovery of how these genetic factors act to drive disease risk in a living animal model. In TREAT-AD, we are combining big data from a broad range of sources and using advanced machine learning to identify the most promising molecular targets for novel therapeutic targeting. We then work with structural biology and medicinal chemistry teams to test the potential for drug development. In MARMO-AD, we are establishing the marmoset as a non-human primate model of Alzheimer’s disease. This project involves genetics, genomics, and in vivo imaging to provide a detailed map of how dementia originates and progresses, ending in multi-faceted cognitive decline. From these studies, we will discover and validate blood and imaging biomarkers that might diagnose early Alzheimer’s and guide novel treatments.
Advanced Computational Strategies for Complex Genetics
Common diseases like diabetes, cancer, arthritis, and dementia are notoriously difficult to understand and treat due to their complex genetic and environmental etiologies. We develop computational strategies to dissect this complexity and map the molecular networks that drive health outcomes. We have developed a software tool called CAPE, which integrates genetic and environmental risk factors across multiple traits to infer a concise model of how these risk factors interact to influence a panel of disease outcomes. We are also developing multi-dimensional mediation approaches to connect molecular and physiological traits driven by genetic variation. With this approach we have discovered networks of genes that affect diabetes-related measures through distinct organs in mice. This analysis has enabled the specification of which organs exhibit key dysfunction due to each genetic factor. For example, we have mapped an axis of inflammation in fat tissues that exacerbates insulin resistance and hyperglycemia. This parsing of genetic risk into resident organs is uniquely possible in the complex mouse studies.
Complex Genetics of Healthy Aging
Genetic risk factors for common diseases are rarely entirely determinant of health outcomes. Even the strongest risk factor for Alzheimer’s disease, the ε4 version of the APOE gene, amounts to only a two-fold increase in lifetime risk. One potential modulator of this risk is other genetic factors that counter-act the detrimental APOEε4 genetics. Recent human genetics has shown that a certain version of the klotho gene, KL-VS, protects APOEε4 carriers from Alzheimer’s. Other studies have shown that high klotho levels are linked to longevity. However, klotho is present at very low levels in the brain, suggesting that it affects Alzheimer’s risk through peripheral activity. To understand the interaction between klotho and APOE, we have created a new panel of genetically engineered mouse models that carry either risk or protective alleles of both genes in all combinations. This will allow us to sort out the precise differences between all combinations and pinpoint the mechanism of protection by KL-VS. Our current hypothesis is that high soluble klotho levels better maintain the blood-brain barrier, which is more likely to fail in APOEε4 carriers. Living, aging organisms are essential for this work and we hope our mouse models will rapidly determine if klotho can serve as a potential therapy for healthy aging.
Our Collaborative Research Network
Our work is woven into an international network of researchers, including partner labs at JAX and collaborators at Indiana University, the University of Pittsburgh, Sage Bionetworks, Emory University, the Structural Genomics Consortium, the University of California Santa Cruz, the University of Minnesota, Duke University, Stanford University, the University of California San Francisco, Helmholtz University, and the University of Washington.
Inheriting a specific genetic variant, APOEε4, is linked with 15-20 percent rise in risk of developing Alzheimer’s, with at least 20 other genes implicated. JAX researchers are studying how APOEε4 risk depends on other genes, in mice with a wide variety of genetic backgrounds.
Currently there are no effective cures for age-related macular degeneration and other heritable retinal diseases.
Alzheimer’s disease is still poorly understood despite its huge costs and burden. Greg Carter is working at the intersection between patient and mouse research to develop accurate disease models and develop effective therapies.
For the first time, researchers have the tools to build new mouse models that truly represent patients with Alzheimer’s disease.