A novel, wave-shaped profile of germline selection of pathogenic mtDNA mutations is discovered by bypassing a classical statistical bias.

The shift of the level of disease-causing mtDNA mutations (heteroplasmy) from mother to child is typically negatively correlated with the mothers heteroplasmy (Hm). In other words, mothers with low Hm tend to have children with a higher mutation level (Hch) than their own. In contrast, mothers with high Hm typically see a decrease in heteroplasmy in their children. This trend has been commonly interpreted as a result of a descending germline selection profile, i.e., positive selection at low Hm, gradually turning negative at high Hm. Here we demonstrate, however, that the negative correlation is mostly driven by RTM, or Regression To the Mean, a classical statistical bias. We further show that RTM can be nullified by using the average between the mother and child heteroplasmy, as a new variable, instead of the commonly used mother heteroplasmy in blood. Additionally, we demonstrate that mother/child average is a better approximation of the actual germline heteroplasmy. Moreover, the elimination of RTM revealed a previously hidden wave-shaped HS-profile (positive mother-to-child shift at intermediate average mother-child heteroplasmy, decreasing towards high and low average heteroplasmy). In confirmation of this finding, we show that simulations that involve both wave-shaped HS-profile and RTM,reproduce the observed patterns of inheritance of mtDNA mutations in unprecedented detail. From the health care perspective, the uncovering of the wave-shaped HS-profile (and the removal of the RTM bias) are crucial for families affected by mtDNA disease. From the fundamental perspective, the wave-shaped profile offers a novel understanding of the dynamics of mtDNA in the germline and a novel potential mechanism that prevents the spread of detrimental mtDNA mutations in the population.