Rare diseases collectively affect between 4% and 6% of individuals worldwide. Despite advances in genetic testing, the lack of evidence on the genetic variations that could lead to disease results in up to 80% of people who have a rare disease remaining undiagnosed even after genomic sequencing.
To address this issue, an international team of researchers led by Professor Damian Smedley, Dr Valentina Cipriani and Dr Letizia Vestito from Queen Mary's William Harvey Research Institute developed an analytical framework for identifying the genetic causes of Mendelian diseases through rare variant gene burden analysis and applied it to the genetic records of 34,851 people and their family members (72,690 genomes in total) from the 100,000 Genomes Project, a ground-breaking project to map the genomes of people affected by rare disease and cancer. Our Vice Principal for Health, Professor Sir Mark Caulfield, delivered the 100,000 Genomes Project when he served as Chief Scientist at Genomics England, unleashing the potential for a genomic medicine service in the NHS.
The study, published in Nature, identified genetic variants in 69 genes previously unknown to be associated with rare disease. In 30 of these cases, the new genetic findings were supported by existing experimental evidence, thereby confirming the accuracy of the novel approach.
Importantly, the strongest overall genetic and experimental evidence supported the newly-discovered genetic variants for rare forms of diabetes, schizophrenia, epilepsy, Charcot-Marie-Tooth (CMT) disease, and anterior segment ocular abnormalities.
Dr Valentina Cipriani, Senior Lecturer in Statistical Genomics at Queen Mary University of London and first author of the study, said: "By making our analytical framework openly available and for generic use beyond the study's data, we aim to facilitate its global application across rare disease datasets, accelerating disease-gene discovery and molecular diagnoses worldwide".
Dr Letizia Vestito, Research Fellow in Computational Genomics at Queen Mary University of London and joint first author of the study, said: "For many rare disease patients, receiving a diagnosis is the first crucial step toward appropriate care and treatment. By uncovering new disease-gene associations, our study aims to make a transformative impact, offering hope and tangible benefits to rare disease patients and their families".
Professor Damian Smedley, Professor of Computational Genomics at Queen Mary University of London and senior author of the study, said: "The 100,000 Genomes Project data has provided a unique opportunity to showcase the clinical impact of large-scale statistical approaches in rare diseases for discovering new associations and to end the diagnostic odyssey for many rare disease patients and their families."
