Prospective New Technologies of mtDNA Diagnosis

Mitochondrial diseases include a wide range of clinical phenotypes due to the involvement of mitochondrial and nuclear genes in the etiology of these diseases, which makes clinical as well as molecular diagnosis very difficult and significantly lengthens the time to establish a definitive diagnosis. Correct clinical identification is further complicated by different types of inheritance, often with incomplete penetrance, which is mainly due to the heteroplasmy of mitochondrial DNA variants and its threshold effect. There is still no established diagnostic algorithm for diagnosing patients with mitochondrial disease. NGS technology brought a significant improvement compared to other diagnostic approaches, while using this method we can identify new genes involved in the etiology of mitochondrial diseases in a time and cost-effective manner. However, the generation of large amounts of data is associated with bioinformatics challenges of how to collect and organize the generated information. Furthermore, the complexity of interpreting mitochondrial variants increases exponentially, requiring better and specific predictive tools to assess the pathogenicity of variants in mitochondrial DNA. In the future, it will be necessary to develop guidelines that will refine the diagnostic algorithm and facilitate diagnosis in individuals with signs of mitochondrial disease with different levels of heteroplasmy in the context of their specific variant and also haplogroup. Overcoming all these technical challenges is a prerequisite for uncovering the underlying causes of mitochondrial diseases and ultimately for the development of effective treatments.