@article {R{\o}yrvik072348, author = {E.C. R{\o}yrvik and J.P. Burgstaller and I.G. Johnston}, title = {mtDNA diversity in human populations highlights the merit of haplotype matching in gene therapies}, elocation-id = {072348}, year = {2016}, doi = {10.1101/072348}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Modern gene therapies aim to prevent the inheritance of mutant mitochondrial DNA (mtDNA) from mother to offspring by using a third-party mtDNA background. Technological limitations mean that these therapies may result in a small amount of maternal mtDNA admixed with a majority of third-party mtDNA. This situation is unstable if the mother{\textquoteright}s mtDNA experiences a proliferative advantage over the third-party mtDNA, in which case the efficacy of the therapy may be undermined. Animal models suggest that the likelihood of such a proliferative advantage increases with increasing genetic distance between mother and third-party mtDNA, but in real therapeutic contexts the genetic distance, and so the importance of this effect, remains unclear. Here we harness a large volume of available human mtDNA data to model random sampling of mother and third-party mtDNAs from real human populations. We show that even within the same haplogroup, genetic differences around 20-80 SNPs are common between mtDNAs. These values are sufficient to lead to substantial segregation in murine models, over an organismal lifetime, even given low starting heteroplasmy, inducing increases from 5\% to 35\% over one year. Randomly pairing mothers and third-party women in clinical contexts thus runs the risk that substantial mtDNA segregation will compromise the beneficial effects of the therapy. We suggest that choices of {\textquoteleft}mtDNA donors{\textquoteright} be based on recent shared maternal ancestry, or, preferentially, explicit haplotype matching, in order to reduce the potential for problems in the implementation of these therapies.}, URL = {https://www.biorxiv.org/content/early/2016/08/31/072348}, eprint = {https://www.biorxiv.org/content/early/2016/08/31/072348.full.pdf}, journal = {bioRxiv} }