Scientists at the National Institutes of Health (NIH) has made a breakthrough in identifying genetic risk factors for two types of non-Alzheimer’s dementia. The findings, published in Cell Genomics, describe the discovery of large-scale DNA changes known as structural variants by analyzing a large number of DNA samples.
The researchers, hailing from the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA) at NIH, collaborated on the project. Structural variants, which encompass significant alterations in DNA sequences, were found to be potential risk factors for Lewy body dementia (LBD) and frontotemporal dementia (FTD). These variants are more challenging to study compared to the more commonly studied mutations that affect individual or a few nucleotides.
Using state-of-the-art computer algorithms and machine learning techniques, the research team analyzed whole-genome data from thousands of patient samples and control groups. Through this approach, they identified a previously unknown variant in the TCPN1 gene, which was found in samples from LBD patients. This variant, involving the deletion of over 300 nucleotides from the gene, was associated with a higher risk of developing LBD. Interestingly, TCPN1 is already recognized as a risk factor for Alzheimer’s disease, suggesting its potential relevance in a broader context of dementia.
Furthermore, by focusing on 50 genes associated with inherited neurodegenerative diseases, the scientists discovered additional rare structural variants, some of which are known to cause disease. They also confirmed the presence of two established risk factors for FTD, located in the C9orf72 and MAPT genes. These findings reinforce the validity of the study’s new discoveries and indicate the effectiveness of the algorithms employed.
To overcome the limited reference maps for existing structural variants, the researchers created a catalog based on the data obtained in their analyses. They have made the analysis code and raw data available to the scientific community, facilitating further investigations in this field. Additionally, an interactive app has been developed to help researchers study their genes of interest and determine the presence of variants in control groups versus LBD or FTD cases. These resources aim to make complex genetic data more accessible to non-bioinformatics experts, thus accelerating the pace of discovery.
The scientists involved in the study anticipate that the dataset will continue to expand as more data is analyzed. Their research contributes to the growing body of knowledge surrounding the genetic underpinnings of neurodegenerative diseases, paving the way for future advancements in scientific understanding and precision medicine approaches to combat these debilitating disorders.
Source: National Institutes of Health