Mutation and catastrophe in the aging genome

In the 1960s, Leslie Orgel proposed what is now known as the error catastrophe theory of aging, arguing that errors in protein translation that reduce the fidelity of the protein-translating enzymes would lead to a feedback loop of increasingly inaccurate protein synthesis, terminating in the death of the organism. This mechanism of aging would be consistent with the exponential increase of mortality observed in humans, but the error catastrophe theory of aging has been generally disregarded by researchers due to a lack of evidence for an age-related increase in protein errors. Another theory of aging, proposed at roughly the same time, is Leo Szilard's two-hit model of somatic mutation accumulation, which assumed a linear increase in mutations over time but explained the nonlinear pattern of human mortality through a mechanism of genetic and cellular redundancy which kept mortality low until the redundancy was exhausted, at which point mortality rapidly rose. Here, we synthesize the two theories, along with the latest advances in genomics research. We propose a new catastrophe theory of aging, this time with somatic mutations as the primary agent of the feedback loop. Similar to protein errors affecting translation itself, somatic mutations in genes involved in DNA replication and repair would lead to a feedback loop of exponentially increasing mutation load. The difference from protein errors is that somatic mutations would mainly affect gene regulatory regions rather than the much smaller part of the genome encoding protein-coding information. Although the self-stimulating accumulation of somatic mutations is not mutually exclusive with the Szilard-based loss of redundancy, we present evidence that suggests that the accumulated mutations themselves could be numerous enough to cause mortality. Finally, we acknowledge the limits of our current knowledge and propose a course of research practices that will help to confirm or refute our model and advance the field of aging research as a whole.