Q&A with Dr. Gregory Carter: Developing Computational Strategies and the MODEL-AD Consortium

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Gregory Carter, Ph.D., is an Associate Professor at The Jackson Laboratory. His work is focused on developing computational strategies using genetic data to understand complex genetic systems. We recently spoke with Dr. Carter about his research and the MODEL-AD consortium.

NanoString (NS): Tell us a bit about your work and your focus at The Jackson Laboratory.
Gregory Carter (GC): My lab is focused on computational genetics and genomics of complex diseases, with a strong emphasis on Alzheimer’s disease (AD). We carry out parallel genetic studies in humans and mice and work to create novel mouse models that capture the range of pathologies leading to late-onset Alzheimer’s. We use genomics, imaging, and behavioral metrics to fully characterize each model and identify its specific translational relevance.

NS: What was the inspiration for the MODEL-AD consortium?
GC: Existing mouse models of AD introduce rare, amyloid-related mutations via transgenes into the mouse genome. These mice provide an excellent platform for studying amyloidosis but do not contain late-onset AD genetics or fully recapitulate the sporadic disease. With advances in the genetics of late-onset AD, systems biology characterization of the disease, and new gene editing technologies, it was recognized that we could augment the existing models with new mouse models and use the same technologies to understand how these models relate to human AD.

NS: Treatments for Alzheimer’s disease have been slower to materialize than many had hoped. How will novel mouse models address this challenge?
GC: By expanding the repertoire of models, we will provide a broader range of pathologies expressed in the animals. This makes them more effective as preclinical research tools, in which candidate therapeutics are screened in animal models. We will be able to identify the precise animal model that exhibits the specific pathology that a therapeutic aims to reverse. For example, models with neuro-immune genetic factors and pathology can be used to test if a drug engages and properly acts on this target process.

NS: What is the biggest hurdle in mouse model development today?
GC: The greatest challenge is that we don’t fully understand the etiology of late-onset Alzheimer’s. As a result, we don’t yet know the right genetic and environmental factors to combine in a model and, once created, we don’t yet have a clear expectation of when and where to look for the earliest changes. Of course, these are precisely what we hope to understand with new models, so directly addressing this challenge is our immediate priority.

NS: How has new technology enabled the development of better mouse models?
GC: There are three key technologies that are driving our next-generation mouse models. First, the ability to perform genome-wide association on large disease cohorts has revealed dozens of high-confidence genetic loci that contribute to AD risk. Second, advances in computational approaches are allowing systematic prioritization of candidate variants. Finally, the advent of CRISPR/Cas9 technology allows us to rapidly edit mouse genomes with high precision, so we can efficiently translate genetic variation into the experimental system.

NS: What lead you to begin working with NanoString?
GC: We’re creating about ten new mouse models per year in MODEL-AD, so we need efficient platforms for screening models for disease relevance. At the same time, the Accelerating Medicines Partnership for AD (AMP-AD) has created a multi-cohort catalog of gene expression alterations associated with Alzheimer’s. Our interest in rapidly assessing each mouse model for similar expression changes aligned well with NanoString technology.

NS: What has been the biggest benefit of NanoString analysis so far?
GC: By screening each model with the nCounter® Mouse AD Panel, we are able to rapidly and easily assess a broad panel of AD-related genes for differential expression. This is used to identify strains for comprehensive characterization. These data also indicate which specific processes are affected in a given model, thereby allow us to focus our follow-up studies on the most likely contributing pathologies.

NS: What’s next for the Alzheimer’s research field?
GC: I think the next major advances will be in understanding the heterogeneity of the disease and, in a related vein, how Alzheimer’s overlaps with other dementias. By using new systems biology and in vivo imaging-based methods, many researchers are beginning to identify different molecular and pathological manifestations of AD. This could allow us to (1) identify specific biomarkers that could be clinically informative in presymptomatic individuals and (2) develop therapies that are more precisely targeted to each flavor of AD, leading to more effective treatments.

To learn more about Dr. Gregory Carter’s work, view the webinar “A gene expression based screening platform for mouse models of late-onset Alzheimer’s disease”.

FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

By NanoString
For research use only. Not for use in diagnostic procedures.