Whole-Exome Sequencing Identifies Mitochondrial Disorder Biomarkers

This technique is considerably faster and more economical than classical whole-genome sequencing.

Mitochondrial disorders are recognized as a common cause of inherited disease, but their diagnosis remains challenging. Multiple respiratory chain complex defects are particularly difficult to diagnose at the molecular level because of the huge number of nuclear genes potentially involved in mitochondrial protein synthesis, with many not yet linked to human disease.

Investigators at Newcastle University (United Kingdom) sought biomarkers that would be useful for diagnosing respiratory chain complex defects. To this end they used whole-exome sequencing to evaluate 53 patients referred to two national centers in the United Kingdom and Germany between 2005 and 2012. The majority (96%) of the patients developed disease symptoms during childhood (less than 15 years old) and most (66%) developed symptoms within the first year of life. The most frequent clinical features were muscle weakness, central neurological disease, cardiomyopathy, and abnormal liver function; a combination of these abnormalities was present in most cases.

Presumptive causal variants were identified in 28 patients and possible causal variants were identified in four patients. Together these accounted for 32 patients and involved 18 different genes. These included recurrent mutations in the RMND1, AARS2, and MTO1 genes and potential novel mutations in four possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1). Distinguishing clinical features included deafness and renal involvement associated with RMND1 and cardiomyopathy with AARS2 and MTO1. In 20 patients with prominent heart disease, the causative mutation was detected in 80%, while the detection rate was much lower in patients with liver disease (33%). It was not possible to confidently identify the underlying genetic basis in 21 patients (40%).

The authors concluded that, “Our findings contrast with large-scale candidate gene analysis using conventional and next-generation sequencing approaches, both of which had a lower diagnostic yield (10%–13%) and by definition did not discover new potential disease genes. Additional study is required to determine the utility of this approach compared with traditional diagnostic methods in independent patient populations.”

The study was published in the July 2, 2014, issue of the Journal of the American Medical Association (JAMA).

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