The ionome is the elemental composition of a tissue, organ, or individual. This composition changes over the course of aging, and may do so in ways that allow the production of an aging clock, a measure of chronological or physiological age. This line of development adds to work on the well-known epigenetic clocks, proteomic clocks, and other assessments of age constructed from algorithmic compositions of simple biomarkers. At the end of the day, all of these approaches need a great deal more validation if they are to be used as originally intended, as a way to rapidly assess potential rejuvenation therapies and thus speed up the field. Since it remains quite unclear as to what exactly these clocks measure, meaning which processes of aging cause the clock numbers to change, the results are not yet actionable.


Aging involves coordinated yet distinct changes in organs and systems throughout life, including changes in essential trace elements. However, how aging affects tissue element composition (ionome) and how these changes lead to dysfunction and disease remain unclear. Here, we quantified changes in the ionome across eight organs and 16 age groups of mice. This global profiling revealed novel interactions between elements at the level of tissue, age, and diet, and allowed us to achieve a broader, organismal view of the aging process. We found that while the entire ionome steadily transitions along the young-to-old trajectory, individual organs are characterized by distinct element changes.

The ionome of mice on calorie restriction (CR) moved along a similar but shifted trajectory, pointing that at the organismal level this dietary regimen changes metabolism in order to slow down aging. However, in some tissues CR mimicked a younger state of control mice. Even though some elements changed with age differently in different tissues, in general aging was characterized by the reduced levels of elements as well as their increased variance. The dataset we prepared also allowed to develop organ-specific, ionome-based markers of aging that could help monitor the rate of aging. In some tissues, these markers reported the lifespan-extending effect of CR. These aging biomarkers have the potential to become an accessible tool to test the age-modulating effects of interventions.

Link: https://doi.org/10.1111/acel.13119