Mitochondria are the energy-producing factories inside cells. Sometimes genetic mutations can cause these factories to go wrong, leading to a number of neurological diseases. The same genetic mutation affecting mitochondrial function can result in a specific deficit such as loss of vision or a more complicated disorder such as Parkinson’s-like disease. It is not yet known why the same mutation can have such varying effects.
One gene that behaves in this fashion when mutated is OPA1. Mutations of this gene are the commonest cause of dominantly inherited optic atrophy, but in 25% of affected individuals, they cause more diverse neurological symptoms including parkinsonism. Researchers at NDCN led by Dr Tofaris worked with patients experiencing optic atrophy with or without Parkinson’s symptoms due to loss of OPA1 function. They sequenced all their gene-coding regions and generated stem cell-derived neurons. The results, published in the Annals of Neurology, suggest that the genetic makeup of individuals with loss of OPA1 function may determine whether they develop Parkinson’s symptoms, by worsening the underlying mitochondrial defect.
The researchers showed how the loss of OPA1 function affects the ability of stem cell-derived neurons to generate energy as they age in culture in the lab. A defect in the mechanism that holds mitochondria linked together as networks, called OPA1-mediated fusion, is associated with cell death in the dish and clinical severity in patients. This is important because it suggests that targeting OPA1-mediated fusion in common diseases where mitochondria are especially important, such as Parkinson’s, could be a route to developing therapies to counteract neurodegeneration.
More broadly, the study demonstrates how this kind of deep-phenotyping of a rare disease using stem cell modelling can help contextualise key functions of essential mitochondrial proteins in the study of disease severity. It suggests that mapping the effect of individuals’ genetic makeup in mitochondrial diseases could have prognostic value.