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Cracking the genetic code: SickKids researchers develop new method to classify genetic variants
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Cracking the genetic code: SickKids researchers develop new method to classify genetic variants


A new study from SickKids published in Nature Biotechnology details a novel genome-editing strategy using CRISPR technology to better understand genetic variations.

A team of researchers from The Hospital for Sick Children (SickKids) is working to make the human genome easier to understand. As whole genome sequencing (WGS) becomes more accessible, researchers and clinicians are grappling with the massive amount of information that can be obtained from one genome. Each time a genome is sequenced, it shows where variants, or changes in the genetic code, may have occurred. Sometimes, clinicians can identify when a genetic variant has led to a medical condition but, more often than not, it’s unknown whether a variant is potentially harmless or harmful.

Led by Drs. Evgueni (Zhenya) Ivakine, Scientist in the Genetics & Genome Biology program, and Ronald Cohn, Senior Scientist, Geneticist, Paediatrician and President and CEO at SickKids, the research team developed a novel genome-editing strategy that can analyze and interpret multiple variants at once in any cell type. Their findings were published on February 21, 2022, in Nature Biotechnology.

A genome-editing strategy to study variants in any cell type

Previously, interpreting genetic variants could only be done for genes expressed in a specific type of cell, called haploid cells. These cells have only one copy of the 23 chromosomes that make up human DNA, whereas the majority of human cells have both copies. It’s easier to link variants to clinical presentations in haploid cells because scientists only need to consider variants on one set of chromosomes. However, not all genes are expressed in these cells.

“We have to first understand what it is that our genomes are trying to tell us before we can act on the genetic variations we find,” says Ivakine, who is also an Assistant Professor in the Department of Physiology at the University of Toronto. “Previously, scientists could only interpret genetic variants within one haploid cell line, HAP1. Opening up the opportunity to interpret variants in any cell line of any cell type cracks open the genetic code to be read in its entirety.”

1,000 variants classified, assigned functionality score in gene causing Niemann-Pick disease

To develop and test their method, the team looked at one of the genes that causes Niemann-Pick disease called NPC1. Niemann-Pick disease is a rare, inherited disorder that impacts the ability of cells to metabolize cholesterol. While the NPC1 gene has already been linked to Niemann-Pick disease, there are approximately 12,000 different kinds of variations that can occur within NPC1 and each variation can contribute to a different level of disease severity. Although many different variants have been observed, not all have been classified as benign or disease-causing.

The researchers took a different kind of cell type that expresses NPC1 and has two copies of chromosomes. They were able to make it into a cell line with only one copy of the NPC1 gene remaining. They then used a new CRISPR technology called prime editing to make nearly 1,000 precise variants in the gene.

CRISPR prime editing can serve as a “search and replace” mechanism for the genetic code. The researchers used it to identify the code they wanted to change and replace it with the exact alterations they were looking to make. Then, the team looked at how each variant contributed to changes in the cell’s ability to metabolize cholesterol, therefore indicating the extent to which individual variants contributed to disease severity.

Method could be applied to study other disease-causing genes

The researchers subsequently demonstrated their methodology could be applied to different genes in different cell types by applying their technique to the BRCA2 gene, a well-studied gene known to cause breast cancer.

“Not only are we able to see which variants are associated with disease but we can also look at the extent of disease that can be caused by any given variant,” says Steven Erwood, first author of the study and Research Fellow in the Genetics & Genome Biology program at SickKids. “Using our method, we’ve generated functionality scores for each variant we identified. Even if a clinician hasn’t seen one of these variants in their patients before, the data we’ve provided lends some insight into the clinical presentation they might see as a result.”

Research team hopes to create reference guides for genetic variants

In the long -term, the researchers envision scaling up their genome-editing strategy to generate reference guides for clinicians that would show whether different variants in different genes are likely to be benign or disease-causing. The team has categorized approximately 10 per cent of the total possible variations in NPC1 and says they plan to continue work to define all possible NPC1 variants.

“This is incredibly exciting for its diagnostic potential, but it also holds great promise for the development of novel therapeutics,” says Ivakine. “Using this technology, we can determine which variants will be responsive to targeted treatments in the lab, enabling us to design more focused clinical trials for rare, genetic conditions.”

This work was supported by Niemann-Pick Canada, the University of Pennsylvania Orphan Disease Center in partnership with The Andrew Coppola Foundation, and SickKids Foundation.

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