Report: NIA Workshop on Measures of Physiologic Resiliencies in Human Aging

Abstract

Background/objectives: Resilience, the ability to resist or recover from adverse effects of a stressor, is of widespread interest in social, psychologic, biologic, and medical research and particularly salient as the capacity to respond to stressors becomes diminished with aging. To date, research on human resilience responses to and factors influencing these responses has been limited.

Methods: The National Institute on Aging convened a workshop in August 2015 on needs for research to improve measures to predict and assess resilience in human aging. Effects of aging-related factors in impairing homeostatic responses were developed from examples illustrating multiple determinants of clinical resilience outcomes. Research directions were identified by workshop participants.

Results: Research needs identified included expanded uses of clinical data and specimens in predicting or assessing resilience, and contributions from epidemiological studies in identifying long-term predictors. Better measures, including simulation tests, are needed to assess resilience and its determinants. Mechanistic studies should include exploration of influences of biologic aging processes on human resiliencies. Important resource and infrastructure needs include consensus phenotype definitions of specific resiliencies, capacity to link epidemiological and clinical resilience data, sensor technology to capture responses to stressors, better laboratory animal models of human resiliencies, and new analytic methods to understand the effects of multiple determinants of stress responses.

Conclusions: Extending the focus of care and research to improving the capacity to respond to stressors could benefit older adults in promoting a healthier life span.

Keywords: Biologic aging; Epidemiology; Human aging; Physiologic resilience.

Figure 1.

Trajectory of change in a physiologic property or function from baseline levels after exposure to a stressor (S). L: lag time before perturbation begins; T_P: interval from initial to maximum perturbation; A: maximum perturbation: T_S: interval from maximum perturbation to stabilization; P: persisting difference from baseline level. Adapted from figure in Kirkland and colleagues (6).

Figure 2.

Dynamical responses to a stressor. Relationships between a stressor and responses in two systems with feedback loops controlling the rate and magnitude of the responses. Source: Varadhan and colleagues (10).

Figure 3.

The manner by which resilience factors may interact across different systems. (A) A single stressor (eg, alcohol ingestion) may result in multiple different adverse clinical outcomes (eg, cognitive deficit; poor mobility, and enhanced fall risk; nocturia and enhanced incontinence risk). (B) Multiple different stressors (eg, alcohol ingestion; lack of sleep; benzodiazepine ingestion) may also both individually and collectively enhance the risk of a relevant clinical outcome (eg, diminished driving responses and safety). In both cases, declines in resilience mechanisms shared across different systems might contribute to enhanced vulnerability in the face of multiple varying stressors or outcomes.