LETTERS TO THE EDITOR Mitochondrial replacement and its effects on human health

Sir, In a recent paper Dobler et al. (Dobler et al., 2018) assess the likely consequences of mitochondrial replacement therapy using estimates of the effects of combining mitochondrial DNA with a novel nuclear background in animal and human studies. However, their conclusions are unsound since they do not follow elementary statistical principles. What they fail to draw attention to, and properly model in their statistical analysis, is the high degree of statistical non-independence in their data. They have collected 1004 estimates of the effect of placing a mitochondrial DNA in a novel nuclear background. However, many of these estimates are from the same lines assayed for multiple traits. For example, 364 estimates come from the seed beetle, Callosobruchus maculatus, in which the same 25 lines, from the reciprocal crossing of only five lines, have been assayed for multiple traits, and 131 estimates come from the copepod Tigriopus caifornicus, where six crosses have been made between three lines. In some cases, the traits are very similar; 22 of their estimates come from a comparison of two mouse strains in which the mice were weighed every few days. They claim to account for the non-independence by adding publication ID into their model as a random factor, however this will fail to account for the non-independence for two reasons. First, the random factor accounts for mean differences in effect size between publications, it does not take account of the fact that estimates of the variances in the model are incorrect. This is elementary statistics; you cannot test whether males and females differ in height by repeatedly measuring the height of a single male and female over and over again. Second, including publication ID in an analysis does not take into account that multiple publications have used the same strains. In short, they have far less statistical power than they acknowledge. Finally, they present a risk analysis of mitochondrial replacement therapy. They use estimates of how often significant negative effects are observed in animal studies to estimate what they expect in humans. However, again, the problems of non-independence are evident. A large proportion of the significant negative estimates (65 out of 136) come from a single study in which four traits were measured for three pairs of reciprocal crosses. The experiment in question was conducted by Ellison and Burton (Ellison and Burton, 2008) on T. californicus. Each pair of strains were crossed to form an F1; here the mtDNA finds itself in a nuclear genome which is 50% novel (i.e. from the paternal strain). They then crossed the F1s to yield F2s; the mtDNA is now in a variant of the F1 genome; on average 50% of the genome is paternal and 50% maternal. Finally, they backcrossed the F2s to the original parental strain such that on average 75% of the genome would be of one parental strain. They treat each of these as a statistically independent estimates of the effect of placing a mtDNA in a novel nuclear environment. This is inappropriate. A risk assessment conducted with this level of care could essentially come to any conclusion. In summary, while the aims of the study of Dobler et al. (Dobler et al., 2018) are laudable, they have not followed basic statistical principles and as such their analysis does not substantiate their claims. Other reviews of the issues and evidence surrounding mito-nuclear interactions and mitochondrial replacement therapy are available (Eyre-Walker, 2017).