Assessing whole genome sequencing as a diagnostic test for mitochondrial disease.
Professor Patrick Chinnery
Samples and data
Institution or company
University of Cambridge
Genomics and Rare Diseases
Mitochondria are organelles which produce energy in nearly all the cells in the human body. They contain their own DNA, mtDNA, which is distinct from the DNA in the nucleus. Mutations in this mtDNA can cause mitochondrial disease, where the cells are unable to make enough energy, which often presents with variable neuromuscular phenotypes.
Mitochondrial disease is further complicated by the phenomenon of heteroplasmy, where multiple mtDNA genotypes are present within the same patient. The level of heteroplasmy is related to the variable phenotype associated with mitochondrial disease. The level of heteroplasmy can be low (<10%) in blood samples of affected individuals.
Whole genome sequencing is a technique used to sequence every gene in the human genome. We have shown that it is possible to detect mtDNA variants from whole genome sequence data down to ~1% heteroplasmy levels. Our aim here is to validate these findings using the independent laboratory technique currently used to diagnose mtDNA diseases across a range of different heteroplasmy values.
If successful, this will immediately feed into the NHS diagnostic pipeline, allowing mtDNA diseases to be diagnosed using whole genome sequencing.
Participation: For this study we provided samples from 23 volunteers from the Rare Diseases BioResource.
Organisation: This study is organised by Professor Patrick Chinnery from the University of Cambridge.