Strategy for identifying biomarkers of aging in long-lived species

If effective anti-aging interventions are to be identified for human applic ation, then the development of reliable and valid biomarkers of aging are e ssential for this progress. Despite the apparent demand for such gerotechno logy, biomarker research has become a controversial pursuit. Much of the co ntroversy has emerged from a lack of consensus on terminology and standards for evaluating the reliability and validity of candidate biomarkers. The i nitiation of longitudinal studies of aging in long-lived non-human primates has provided an opportunity for establishing the reliability and validity of biomarkers of aging potentially suitable for human studies. From the pri mate study initiated in 1987 at the National Institute on Aging (NIA), the following criteria for defining a biomarker of aging have been offered: (1) significant cross-sectional correlation with age; (2) significant longitud inal change in the same direction as the cross-sectional correlation (3) si gnificant stability of individual differences over time. These criteria rel ate to both reliability and validity. However, the process of validating a candidate biomarker requires a greater standard of proof. Ideally, the rate of change in a biomarker of aging should be predictive of lifespan. In sho rt-lived species, such as rodents, populations differing in lifespan can be identified, such as different strains of rodents or groups on different di ets, such as those subjected to calorie restriction (CR), which Live marked ly longer. However, in the NIA primate study, the objective is to demonstra te that CR retards the rate of aging and increases lifespan. In the absence of lifespan data associated with CR in primates, validation of biomarkers of aging must rely on other strategies of proof. With this challenge, we ha ve offered the following strategy: If a candidate biomarker is a valid meas ure of the rate of aging, then the rate of age-related change in the biomar ker should be proportional to differences in lifespan among related species . Thus, for example, the rate of change in a candidate biomarker of aging i n chimpanzees should be twice that of humans (60 vs 120 years maximum Lifes pan); in rhesus monkeys three times that of humans (40 vs 120 years maximum lifespan). The realization of this strategy will be aided by developing a primate aging database, a project that was recently launched in cooperation with the NIA, the National Center for Research Resources, and the Universi ty of Wisconsin Regional Primate Research Center. Published by Elsevier Sci ence Inc.