RESUMO
To discover rare disease-gene associations, we developed a gene burden analytical framework and applied it to rare, protein-coding variants from whole genome sequencing of 35,008 cases with rare diseases and their family members recruited to the 100,000 Genomes Project (100KGP). Following in silico triaging of the results, 88 novel associations were identified including 38 with existing experimental evidence. We have published the confirmation of one of these associations, hereditary ataxia with UCHL1 , and independent confirmatory evidence has recently been published for four more. We highlight a further seven compelling associations: hypertrophic cardiomyopathy with DYSF and SLC4A3 where both genes show high/specific heart expression and existing associations to skeletal dystrophies or short QT syndrome respectively; monogenic diabetes with UNC13A with a known role in the regulation of ß cells and a mouse model with impaired glucose tolerance; epilepsy with KCNQ1 where a mouse model shows seizures and the existing long QT syndrome association may be linked; early onset Parkinson's disease with RYR1 with existing links to tremor pathophysiology and a mouse model with neurological phenotypes; anterior segment ocular abnormalities associated with POMK showing expression in corneal cells and with a zebrafish model with developmental ocular abnormalities; and cystic kidney disease with COL4A3 showing high renal expression and prior evidence for a digenic or modifying role in renal disease. Confirmation of all 88 associations would lead to potential diagnoses in 456 molecularly undiagnosed cases within the 100KGP, as well as other rare disease patients worldwide, highlighting the clinical impact of a large-scale statistical approach to rare disease gene discovery.
RESUMO
BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.).