Automated, high-dimensional evaluation of physiological aging and resilience in outbred mice

Behavior and physiology are essential readouts in many studies but have not benefited from the high-dimensional data revolution that has transformed molecular and cellular phenotyping. To address this, we developed an approach that combines commercially available automated phenotyping hardware with a systems biology analysis pipeline to generate a high-dimensional readout of mouse behavior/physiology, as well as intuitive and health-relevant summary statistics (resilience and biological age). We used this platform to longitudinally evaluate aging in hundreds of outbred mice across an age range from 6 months to 3.4 years. In contrast to the assumption that aging can only be measured at the limits of animal ability via challenge-based tasks, we observed widespread physiological and behavioral aging starting in early life. Using network connectivity analysis, we found that organism-level resilience exhibited an accelerating decline with age that was distinct from the trajectory of individual phenotypes. We developed a method, Combined Aging and Survival Prediction of Aging Rate (CASPAR), for jointly predicting chronological age and survival time and showed that the resulting model is able to predict both variables simultaneously, a behavior that is not captured by separate age and mortality prediction models. This study provides a uniquely high-resolution view of physiological aging in mice and demonstrates that systems-level analysis of physiology provides insights not captured by individual phenotypes. The approach described here allows aging, and other processes that affect behavior and physiology, to be studied with sophistication and rigor.

A Hierarchical Process Model Links Behavioral Aging and Lifespan in C. elegans

Aging involves a transition from youthful vigor to geriatric infirmity and death. To study the relationship between youthful vigor and lifespan, we developed a new version of “the lifespan machine” that can simultaneously measure age-associated changes in behavior and lifespan at high precision in large populations. Across diverse interventions, we find that behavioral aging and lifespan are not parsimoniously explained as manifestations of a single underlying aging process. Instead, the correlation between youthful vigor and lifespan is better explained as the result of two partially independent aging processes that progress during adulthood under the influence of a shared, systemic factor. Our model provides a framework for separating the direct, targeted effects of lifespan-altering interventions from their broad, systemic effects—supporting future efforts in the rational design of clinical interventions in aging.

Physical Contexts and Behavioral Aging

Along with the social, economic, care-related, organizational, and technological context, the physical and infrastructural environment indoors and out of the home has gained attention in behavioral aging research as well as in gerontology as a whole since the 1960s. There is, however, an ongoing trend to downplay physical-infrastructural environments in behavioral aging research at the conceptual and empirical level. Therefore, substance is provided to support the usefulness of ecology and aging perspectives for the psychology of aging by mainly addressing North American and European research in the area.