The role of genetic variation in determining m.3243A>G variant heteroplasmy

Abstract

Mitochondrial DNA (mtDNA) is a maternally inherited, multi-copy genome that has the potential to be heteroplasmic, meaning that there can be different populations of mtDNA in a single cell. This is caused by the presence of different alleles, some of which can be pathogenic. Different alleles can be acquired throughout our lifetime in the context of aging for example, due to somatic mutation, but also inherited through the maternal lineage. Heteroplasmy levels vary between individuals, tissues, and cells, and there are various hypotheses that try to explain the variability in the level of pathogenic variants a disease carrier or affected mother can transmit to her offspring. The exact mechanisms involved in this variability are yet unclear however, genetic bottlenecks, mtDNA segregation, random genetic drift, and selection are the major candidates. The m.3243A>G variant is the most common, heteroplasmic pathogenic mitochondrial variant that is associated with several mitochondrial disorders, most notably MELAS (Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke like episodes). Knowledge of the genetic factors that influence levels of pathogenic mtDNA variants may contribute to drug discovery that manipulates heteroplasmy levels, as well as aid clinicians and genetic counsellors with providing accurate success rates in case mitochondrial donation therapies are considered. Family-based heritability studies have estimated that ~72% of the variance in m.3243A>G, can be attributed to additive genetic factors; the aim of this project was to identify these factors to further our knowledge of the pathways that influence m.3243A>G variability between individuals. To elucidate this, nuclear genome wide association studies (GWAS) were performed with the variable, age corrected m.3243A>G variant allele levels as the phenotype, within a cohort of 408 individuals carrying the m.3243A>G mutation from a multicentre cohort, which includes samples collected from centres across the UK, Italy, and Germany. Additional m.3243A>G carriers were identified using whole genome sequencing data from two large publicly available datasets (UK Biobank (UKBB) and 100,000 genomes project (100kGP Genomics England)). None of the GWAS analyses yielded a significant association peak. META analysis combining GWAS data of the large public cohorts revealed a peak approaching significance on chromosome eight, led by SNP with rs1512802 (8:5882269G>C) (-log10(Pvalue) = 6.9). A mtDNA-GWAS was undertaken to determine whether mtDNA sequence context influences m.3243A>G levels, documenting an association in the 100kGP cohort which mapped to haplogroup U (m.16356T>C, -log10(Pvalue ) = 3.5). This association was not observed in the META analysis, which combined the mtDNA GWAS analyses on 100kGP and the UKBB cohorts, suggesting that the association might have been a false positive. These results indicate that sample size is a significant limitation of this study, necessitating the identification of further m.3243A>G carrier samples to increase analysis detection power.