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How CRISPR-Based Gene Engineering Is Helping To Accelerate Alzheimer’s Disease Research

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Researchers from the National Institutes of Health (NIH) recently outlined plans in Neuron of a project that aims to accelerate research on Alzheimer’s disease and related dementias (ADRD). The ambitious project – the Induced Pluripotent Stem Cell Neurodegenerative Disease Initiative (iNDI) – will model more than 100 mutations associated with ADRD in isogenic induced pluripotent stem cell (iPSC) lines.

To learn about some of the main challenges associated with generating a large library of edited iPSCs and the role that Synthego, a genome engineering company, is playing in the iNDI project, we spoke to Synthego’s CSO, Dr Robert Dean.

Anna MacDonald (AM): Why is reliance on a “one gene at a time” approach to Alzheimer’s disease research and therapeutic discovery insufficient?

Robert Deans (RD):
ADRD are neurodegenerative disorders affecting more than 5 million people in the United States. Although about 50 genes are associated with this disease cohort, the interplay between them is unclear and their functional dependencies are unknown. Knowledge of gene linkages and converging disease pathways is key to developing therapeutics that could leverage drug design for patients with mutations in related genes. Studying these genetic linkages necessitates developing disease models with multiple variants per gene target in a relevant cell type. Studying disease alleles in iPSC models allows interrogation of developmental effects which manifest at later stages of life. A library of clinically-relevant disease models that offers insights into functional linkages between genes implicated in ADRD would expedite research in this field.

AM:  How can CRISPR-based gene engineering accelerate research in this area?

The combination of discoveries of numerous gene mutations associated with a disease and advancements in CRISPR editing technologies have made it possible to model and study the effects of specific disease mutations in relevant cell types. Placing disease alleles in iPSC, for example, would allow experimental testing in all mature cell types of the body.

Being able to make precise CRISPR edits at scale puts researchers on the cusp of being able to study thousands of genes, and examine hundreds of variants of those genes. This will allow scientists to more faithfully model the complexity of a human disease, which could lead to the development of therapeutic drugs or next-generation gene therapies for many serious diseases.

AM: Can you tell us more about the NIH’s iNDI project and its aims?

The NIH initiated the iNDI to help scientists better understand how genetic mutations lead to the brain damage underlying ADRD. The goal of iNDI, the largest-ever induced pluripotent stem cell genome engineering project, is to create a library of hundreds of disease models for ADRD studies within the neuroscience community. Generating a standardized collection of hundreds of isogenic iPS cell lines carrying ADRD relevant mutations will be valuable for the global research community.

AM:  What are the main challenges of generating a library of edited iPSCs?

Generating a library of edited iPS cell lines is not an easy feat. Attempting this manually is a laborious process, and this is where Synthego’s engineering solutions make even creating heterozygotic variants tractable and fast. Success is largely impacted by several factors. These include guide design, transfection optimization, precise handling and maintenance of the cells and reagent quality.

Data from the CRISPR Benchmark survey showed that researchers spend 472 hours of hands-on time, amounting to several months of total duration, on CRISPR editing. Performing multiple edits in a challenging cell type such as iPS cells means months of laborious hard work with no guarantee of success.

We created the Eclipse Platform to address these challenges. Eclipse is designed to enhance disease modeling, drug target identification and validation and accelerate cell therapy manufacturing. To ensure the success of any type of edit, Eclipse uses machine learning to apply experience from several hundred thousand genome edits across hundreds of cell types. With this machine learning, combined with automation, Eclipse can reduce costs and increase the scalability of engineered cell production. We engineered Eclipse to use a cell-type agnostic process and immediately benefit researchers working with iPS cells and immortalized cell lines.

By industrializing cell engineering, Eclipse will enable economies of scale, turning a historically complex process into one that is flexible, reliable and affordable.

AM: What role is Synthego playing in the project?

The iNDI project required CRISPR-mediated multiple single nucleotide variants (SNVs) per gene across several targets in iPS cells. Scaling CRISPR experiments to generate hundreds of clones is a challenge – and serial processes would require years of investment. Furthermore, CRISPR editing a difficult-to-handle cell type like iPS cells is an additional challenge that could impede progress and delay the project further.

The iNDI project required the generation of genome-engineered human iPS cell lines harboring ADRD-associated mutations at scale across 22 gene targets. Synthego took on this challenge through the use of Eclipse™, our high-throughput cell engineering platform. Eclipse is designed to accelerate drug discovery and validation by providing highly predictable CRISPR-engineered cells at scale through the integration of engineering, bioinformatics and proprietary science. Leveraging our in-house automated processes and CRISPR expertise, we delivered 264 iPS cell clones – 12 variants per gene across 22 targets. Our standardized, automated process allowed us to edit iPS cells in parallel, thus enabling the generation of clones within just a few months.

The iNDI project will generate the largest library yet for neurodegeneration studies, and our generation of industrialized CRISPR iPS cells in a rapid timeframe lays the foundation for a second CRISPR revolution.

Dr Robert Deans was speaking with Anna MacDonald, Science Writer for Technology Networks.