Dynamics of the most common pathogenic mtDNA variant m.3243A > G demonstrate frequency-dependency in blood and positive selection in the germline

The A-to-G point mutation at position 3243 in the human mitochondrial genome (m.3243A > G) is the most common pathogenic mtDNA variant responsible for disease in humans. It is widely accepted that m.3243A > G levels decrease in blood with age, and an age correction representing similar to 2% annual decline is often applied to account for this change in mutation level. Here we report that recent data indicate that the dynamics of m.3243A > G are more complex and depend on the mutation level in blood in a bi-phasic way. Consequently, the traditional 2% correction, which is adequate 'on average', creates opposite predictive biases at high and low mutation levels. Unbiased age correction is needed to circumvent these drawbacks of the standard model. We propose to eliminate both biases by using an approach where age correction depends on mutation level in a biphasic way to account for the dynamics of m.3243A > G in blood. The utility of this approach was further tested in estimating germline selection of m.3243A > G. The biphasic approach permitted us to uncover patterns consistent with the possibility of positive selection for m.3243A > G. Germline selection of m.3243A > G shows an 'arching' profile by which selection is positive at intermediate mutant fractions and declines at high and low mutant fractions. We conclude that use of this biphasic approach will greatly improve the accuracy of modelling changes in mtDNA mutation frequencies in the germline and in somatic cells during aging.

Automated summary

The A-to-G point mutation at position 3243 in the human mitochondrial genome (m.3243A > G) is the most common pathogenic mtDNA variant responsible for disease in humans. It is widely accepted that m.3243A > G levels decrease with age in blood, and a 2% annual decline correction is often applied. However, recent data suggest that the dynamics of m.3243A > G are more complex and depend on the mutation level in blood in a biphasic way. This biphasic approach can greatly improve the accuracy of modeling changes in mtDNA mutation frequencies.