Recent advances in understanding the molecular genetic basis of mitochondrial disease. Issue 1 (10th May 2019)

• Record Type: Journal Article
• Authors: Thompson, Kyle; Collier, Jack J.; Glasgow, Ruth I. C.; Robertson, Fiona M.; Pyle, Angela; Blakely, Emma L.; Alston, Charlotte L.; Oláhová, Monika; McFarland, Robert; Taylor, Robert W.
• Is Part Of: Journal of inherited metabolic disease. Volume 43:Issue 1(2020)
• Page Start: 36
• Page End: 50
• Publication Date: 2019-05-10
• Subjects: diagnosis -- mitochondrial disease -- molecular mechanisms -- next generation sequencing; Metabolism, Inborn errors of -- Periodicals; Metabolism -- Disorders -- Periodicals; 616.39042
• DOI: 10.1002/jimd.12104
• Languages: English
• ISSNs: 0141-8955

Abstract

Abstract: Mitochondrial disease is hugely diverse with respect to associated clinical presentations and underlying genetic causes, with pathogenic variants in over 300 disease genes currently described. Approximately half of these have been discovered in the last decade due to the increasingly widespread application of next generation sequencing technologies, in particular unbiased, whole exome—and latterly, whole genome sequencing. These technologies allow more genetic data to be collected from patients with mitochondrial disorders, continually improving the diagnostic success rate in a clinical setting. Despite these significant advances, some patients still remain without a definitive genetic diagnosis. Large datasets containing many variants of unknown significance have become a major challenge with next generation sequencing strategies and these require significant functional validation to confirm pathogenicity. This interface between diagnostics and research is critical in continuing to expand the list of known pathogenic variants and concomitantly enhance our knowledge of mitochondrial biology. The increasing use of whole exome sequencing, whole genome sequencing and other "omics" techniques such as transcriptomics and proteomics will generate even more data and allow further interrogation and validation of genetic causes, including those outside of coding regions. This will improve diagnostic yields still further and emphasizes the integral role that functional assessment of variant causality plays in this process—the overarching focus of this review.