Health
Computer Analysis of Large Genetic Datasets Reveals Pathogenesis of Rare Diseases
Using a novel computational approach they developed to analyze large genetic datasets from rare disease cohorts, researchers and colleagues at the Icahn School of Medicine at Mount Sinai identified three previously unknown rare diseases. found a genetic cause. lymphedema (characterized by tissue swelling), thoracic aortic aneurysm disease, and congenital deafness. This work was done in collaboration with colleagues at the University of Bristol, UK. KU Leuven, Belgium. University of Tokyo; University of Maryland; Imperial College London, and others from around the world.
A better understanding of the function of genes involved in these and other diseases could pave the way for the development of therapeutics. The survey results were published online on March 16. natural medicine https://www.nature.com/articles/s41591-023-02211-z [DOI: 10.1038/s41591-023-02211-z].
Rare diseases affect about 1 in 20 people, but only a minority of them receive a genetic diagnosis. Of his 10,000 documented rare diseases, less than half have a known genetic cause. Genome sequencing of large cohorts of patients with rare diseases provides avenues for discovering genetic causes that remain unknown. However, large genetic datasets are difficult to work with, researchers say, and research has been significantly delayed.
Rare diseases are rare individually but collectively very common. Discovering the remaining causes is important for understanding human biology and developing diagnostics and treatments. Many people with rare diseases struggle for years to obtain a genetic diagnosis. Developing and applying statistical and computational methods to discover new causes of rare diseases, expanding knowledge about the underlying causes of these diseases, shortening patient time to diagnosis and improving treatment. I hope it paves the way for the development of law. ”
Ernest Turro, PhD, Senior Research Author, Associate Professor of Genetics and Genomics Sciences, Icahn Mount Sinai
Researchers studied a collection of 269 rare disease classes using data from 77,539 participants in the 100,000 Genomes Project. The researchers identified 260 associations between genes and rare disease classes, including 19 previously absent in the literature. Through international academic collaboration, the authors identified additional cases in other countries and validated the three most plausible new associations through and bioinformatics approaches.
“We hope that our computational framework will help accelerate the discovery of the remaining unknown etiologies of rare diseases. and hearing loss,” said Daniel Greene, Ph.D., a postdoctoral fellow at Icahn Mount Sinai and lead author of the study. “We also plan to apply our method to new methods and other data sets with the aim of continuing to unravel the genetic causes of rare diseases.”
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Journal reference:
green, D. others(2023). Genetic association studies of 77,539 genomes reveal the etiology of rare diseases. natural medicine. doi.org/10.1038/s41591-023-02211-z.
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