Researchers from the Icahn School of Medicine at Mount Sinai and colleagues from the University of Bristol employed a new computational approach developed to analyse large genetic datasets from rare disease cohorts to discover previously unknown genetic causes of three rare conditions: primary lymphedema (tissue swelling), thoracic aortic aneurysm disease, and congenital deafness.
The research was carried out in collaboration with colleagues from the University of Leuven in Belgium, the University of Tokyo, the University of Maryland, Imperial College London, and other institutions around the world.
An improved understanding of the functions of the genes involved in these and other disorders may pave the way for treatment development. The findings were published on March 16 in the online issue of Nature Medicine.
Rare diseases affect approximately one in every twenty people, but only a small percentage of patients receive a genetic diagnosis. Only about half of the 10,000 rare diseases have a known genetic cause. The genome sequencing of large groups of patients with rare diseases provides a path towards discovering the genetic causes that are still unknown. Large genetic datasets, on the other hand, are difficult to work with and significantly slow down research, according to the researchers.
The researchers looked at 269 rare disease classes using data from 77,539 people in the 100,000 Genomes Project, which is one of the largest datasets of phenotyped and whole-genome-sequenced rare disease patients. The researchers discovered 260 associations between genes and rare disease classes, including 19 previously unknown associations. The authors validated the three most plausible novel associations through an international academic collaboration by identifying additional cases in other countries and using experimental and bioinformatic approaches.