Mitochondrial DNA variant detection in over 6,500 rare disease families by the systematic analysis of exome and genome sequencing data resolves undiagnosed cases - Sarah L. Stenton; Kristen Laricchia; Nicole J. Lake; Sushma Chaluvadi; Vijay Ganesh; Stephanie DiTroia; Ikeoluwa Osei-Owusu; Lynn Pais; Emily O’Heir; Christina Austin-Tse; Melanie O’Leary; Mayada Abu Shanap; et al. (HGG Advances)
Summary: Variants in the mitochondrial genome (mtDNA) cause a diverse collection of mitochondrial diseases and have extensive phenotypic overlap with Mendelian diseases encoded on the nuclear genome. The mtDNA is not always specifically evaluated in patients with suspected Mendelian disease, resulting in overlooked diagnostic variants. Here, we analyzed a cohort of 6,660 rare disease families (5,625 genetically undiagnosed [84%]) from the Genomics Research to Elucidate the Genetics of Rare diseases (GREGoR) Consortium, as well as other rare disease cohorts. Using dedicated pipelines to address the technical challenges posed by the mtDNA—circular genome, variant heteroplasmy, and nuclear misalignment—we called single nucleotide variants, small insertions/deletions, and large mtDNA deletions from exome and/or genome sequencing data, in addition to RNA sequencing data when available. Diagnostic mtDNA variants were identified in 10 previously genetically undiagnosed families (1 large deletion, 8 reported pathogenic variants, and 1 previously unreported likely pathogenic variant), as well as candidate diagnostic variants in a further 11 undiagnosed families. In one additional undiagnosed proband, detection of >900 heteroplasmic variants provided functional evidence of pathogenicity to a de novo variant in the nuclear gene POLG (DNA polymerase gamma), responsible for mtDNA replication and repair. Overall, mtDNA variant calling from data generated by exome and genome sequencing—primarily for nuclear variant analysis—resulted in a genetic diagnosis for 0.2% of undiagnosed families affected by a broad range of rare diseases, as well as the identification of additional promising candidates in 0.2%.