Scientists at the National Institutes of Health have identified new genetic risk factors for two types of dementia unrelated to Alzheimer’s. These findings were published in Cellular Genomics and details how researchers identified large-scale DNA changes, known as structural variants, by analyzing thousands of DNA samples. The team discovered several structural variants that could be risk factors for Lewy body dementia (LBD) and frontotemporal dementia (FTD). The project was a collaborative effort between scientists at the National Institute of Neurological Disorders and Stroke (NINDS) and the NIH’s National Institute on Aging (NIA).
Structural variants have been implicated in a variety of neurological disorders. Unlike the more commonly studied mutations, which often affect one or a few DNA building blocks called nucleotides, structural variants account for at least 50 but often hundreds or even thousands of nucleotides at a time, making them more difficult to study.
“If you imagine that all of our genetic code is a book, a structural variant would be a paragraph, a page, or even an entire chapter that was deleted, duplicated, or inserted in the wrong place,” said Sonja W. Scholz, MD. , Ph.D., a researcher in the NINDS Neurogenetics Branch and lead author of this study.
By combining state-of-the-art computer algorithms capable of mapping genome-wide structural variations with machine learning, the research team analyzed genome-wide data from thousands of patient samples and several thousand unaffected controls.
A previously unknown variant in the TCPN1 gene was found in samples from patients with LBD, a disease that, like Parkinson’s disease, is associated with abnormal deposits of the protein alpha-synuclein in the brain. This variant, in which more than 300 nucleotides of the gene are deleted, is associated with an increased risk of developing LBD. While this finding is new for LBD, TCPN1 is a known risk factor for Alzheimer’s disease, which could mean that this structural variant plays a role in the broader dementia population.
“From a genetic point of view, this is a very exciting finding,” said Dr. Scholz. “It provides a benchmark for cell biology and animal model studies and possibly, in the future, a target for intervention.”
By looking at a group of 50 genes implicated in inherited neurodegenerative diseases, the researchers were able to identify additional rare structural variants, including several known to cause disease. The analyzes also identified two well-established risk factors for FTD changes in the C9orf72 and MAPT genes. These proof-of-concept findings reinforced the strength of the new study findings by demonstrating that the algorithms worked correctly.
Because currently available reference maps for structural variants are limited, the researchers generated a catalog based on the data obtained from these analyses. The analysis code and all raw data are now available for the scientific community to use in their studies. An interactive app also allows researchers to study their genes of interest and ask which variants are present in controls vs. LBD or FTD cases. The authors claim that these resources can make complex genetic data more accessible to bioinformatics experts, thereby accelerating 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, MD, Ph.D., NIA Principal Investigator. “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.”
The researchers expect the data set to continue to grow as additional data is analysed.
This work was supported in part by the Intramural Research Program at NINDS and NIA.
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