Nonlinear Dynamics of Frailty in Aging

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DESCRIPTION (provided by applicant): Over the past 2 decades of collaborative work using the tools of nonlinear dynamics and fractal analysis, our research team has shown that aging and disease are associated with a loss of complexity in the dynamics of a variety of physiologic systems. We have proposed that this loss of complexity can lead to reduced adaptive capacity, functional decline, and frailty. Nonlinear mathematical techniques that can quantify the dynamics of physiologic systems and their interactions may, therefore, help characterize the syndrome of frailty. Accordingly, we aim: 1) To determine cross- sectionally in a representative population of elderly people aged 70 years and over, whether there is a relationship between "frailty" and loss of complexity in the dynamics of multiple physiologic systems, including cardiovascular (interbeat (RR) intervals and blood pressure (BP)), cerebrovascular (cerebral blood flow velocity (BFV)), respiratory (interbreath intervals), and balance (center-of-pressure trajectories) control systems. We will also determine whether interactions between these systems degrade in frail elderly individuals by examining the correlations, coherence, phase, and transfer function gains between the dynamic measures of interacting systems (e.g., cardiac and respiratory, or systemic BP and cerebral BFV). 2) To determine whether a loss of complexity in cardiovascular, cerebrovascular, and/or balance dynamics, is associated with an impaired ability to adapt to common physiologic stresses imposed on these systems. We will examine specifically the relationships between: a) resting BP, RR intervals, or cerebral blood flow dynamics and their responses to posture change, and b) quiet standing center-of pressure trajectories and their response to a superimposed cognitive task. 3) To determine, longitudinally over a two-year follow-up period in the same population, whether reduced complexity in the dynamics of these physiologic systems at baseline, or loss of complexity in these systems over time, is predictive of the subsequent development of frailty, its component symptoms, and/or other measures of physical and cognitive functional decline. To achieve these aims we will process and analyze physiologic data that are being gathered from a well-characterized, prospectively followed, population-based sample of 800 elderly people over age 70 who are participating in an ongoing NIA-funded Program Project Grant (the HRCA/Harvard Research Nursing Home, P01-AG004390). The experience of the research team in clinical geriatric research, physiology, dynamic systems, and biostatistics, as well as the outstanding resources of the Hebrew Rehabilitation Center and Harvard Medical School will help assure the project's success.