Computer analysis of large genetic datasets reveals etiologies of rare diseases

Using a new computational approach they developed to analyze large sets of genetic data from cohorts of rare diseases, researchers from the Icahn School of Medicine at Mount Sinai and their colleagues have discovered genetic causes previously unknown three rare diseases: lymphedema (characterized by tissue swelling), thoracic aortic aneurysm disease and congenital deafness. The work was carried out in collaboration with colleagues from the University of Bristol, UK; KU Leuven, Belgium; the University of Tokyo; the University of Maryland; Imperial College London, and others around the world.

A better understanding of the functions of the genes implicated in these and other disorders could pave the way for the development of treatments. The results were published in the March 16 online issue of natural medicine https://www.nature.com/articles/s41591-023-02211-z [DOI: 10.1038/s41591-023-02211-z].

Rare diseases affect approximately 1 in 20 people, but only a minority of patients receive a genetic diagnosis. Less than half of the 10,000 recorded rare diseases have a known genetic cause. Genome sequencing of large cohorts of patients with rare diseases provides a pathway to uncovering genetic causes that remain unknown. However, it is difficult to work with large sets of genetic data, which significantly slows research, say the researchers.

Although rare diseases are rare individually, collectively they are quite common. It is important for our understanding of human biology and for the development of diagnostics and therapeutics that the remaining causes are found. Many people with a rare disease struggle for many years to get a genetic diagnosis. By developing and applying statistical methods and computational approaches to find new causes of rare diseases, we hope to expand knowledge about the underlying causes of these diseases, speed up patient diagnosis, and pave the way for the development of treatments.

Ernest Turro, PhD, lead study author, associate professor of genetics and genomics at Icahn Mount Sinai

Researchers studied a collection of 269 classes of rare diseases using data from 77,539 participants in the 100,000 Genomes Project, one of the largest datasets of rare disease patients phenotyped and sequenced across the entire genome. The researchers identified 260 associations between genes and classes of rare diseases, including 19 associations previously absent from the literature. Through international academic collaboration, the authors validated the three most plausible novel associations by identifying additional cases in other countries and through experimental and bioinformatics approaches.

“We hope that our computational framework will help accelerate the discovery of the remaining unknown etiologies of rare diseases at all levels. For now, we anticipate that genetic diagnosis will be feasible for some families with previously unexplained primary lymphedema. , thoracic aortic aneurysm disease, and deafness,” said Daniel Greene, PhD, postdoctoral fellow at Icahn Mount Sinai and senior study author. “We also plan to apply our methods in innovative ways and in other datasets, with the aim of continuing to unravel the genetic causes of rare diseases.”