“If you imagine that our entire genetic code is a book, a structural variant would be a paragraph, page, or even an entire chapter that has been removed, duplicated, or inserted in the wrong place,” said Sonja W. Scholz, M.D., Ph.D., investigator in the neurogenetics branch of NINDS and senior author of this study.
By combining cutting-edge computer algorithms capable of mapping structural variations across the whole genome with machine learning, the research team analyzed whole-genome data from thousands of patient samples and several thousand unaffected controls.
A previously unknown variant in the gene TCPN1 was found in samples from patients with LBD, a disease, that like Parkinsons disease, is associated with abnormal deposits of the protein alpha-synuclein in the brain. This variant, in which more than 300 nucleotides are deleted from the gene, is associated with a higher risk for developing LBD.
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“From a genetics standpoint, this is a very exciting finding,” said Dr. Scholz. “It provides a point of reference for cell biology and animal model studies and possibly down the road, a target for intervention.”
By looking at a group of 50 genes implicated in inherited neurodegenerative diseases, the investigators were able to identify additional rare structural variants, including several that are known to cause disease. The analyses also identified two well-established risk factors for FTD changes in the C9orf72 and MAPT genes. These proof-of-concept findings bolstered the strength of the study’s new findings by demonstrating that the algorithms were properly working.
Because reference maps for currently-available structural variants are limited, the researchers generated a catalog based on the data obtained in these analyses. The analysis code and all the raw data are now available to the scientific community for use in their studies. An interactive app also allows investigators to study their genes of interest and ask which variants are present in controls vs. LBD or FTD cases. The authors assert these resources may make complex genetic data more accessible to non-bioinformatics experts, which will accelerate the pace of discovery.
“Research to unravel the intricate genetic architecture of neurodegenerative diseases is resulting in significant advances in scientific understanding,” said Bryan J. Traynor, M.D., Ph.D., senior investigator at NIA. “With each discovery, we shed light on the mechanisms behind neuronal cell death or dysfunction, paving the way for precision medicine to combat these debilitating and fatal disorders.”
Reference :
- Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias – (https://www.sciencedirect.com/science/article/pii/S2666979X23000848?via%3Dihub)
Source: Eurekalert
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