The role of physiological complexity in aging and evolution

衰老是生物学中最不为人所知的现象之一。在生理层面上，确实有数百种机械理论，而在进化层面上，我们仍然没有令人信服的方法来解释物种寿命的多样性，或者为什么许多物种似乎根本不会衰老。我的研究项目的核心是努力理解复杂系统动力学在衰老的生理和进化中的作用。我首先提出的原则是，体内平衡是一种由调节网络结构决定的紧急特性，因此，自然选择必须在整个网络上运作，以在不干扰体内平衡能力的情况下调节生理。反过来，体内平衡的逐渐丧失（失调）可能是衰老过程的一个组成部分。因此，理解和测量复杂网络中的稳态和失调的方法可以揭示生理进化、衰老进化和衰老机制。

Aging is one of the least understood phenomena in biology. At a physiological level, there are literally hundreds of mechanistic theories, and at an evolutionary level we still have no convincing way to explain the diversity of lifespans across species, or why many species appear not to age at all. The core of my research program is an effort to understand the role of complex systems dynamics in both the physiology and evolution of aging. I start with the principle that homeostasis is an emergent property determined by the structure of regulatory networks, and that natural selection must thus operate on whole networks to adjust physiology without perturbing homeostatic capacity. In turn, gradual loss of homeostasis (dysregulation) is likely to be an integral part of the aging process. Ways to understand and measure homeostasis and dysregulation in complex networks could thus shed light on physiological evolution, the evolution of aging, and the mechanisms of aging. My key contribution over the last several years has been to show that much of the aging process can be quantified using readily available blood biomarkers integrated through appropriate statistical methods. In particular, I have shown in several species that a statistical distance method can be used to quantify how far an individual's physiological state is from the population average across a series of blood biomarkers, and that this measure corresponds to dysregulation, which increases with age and predicts mortality. The metric is not sensitive to the precise choice of biomarkers, confirming a complex systems interpretation, and can be measured either globally or for separate physiological systems. Dysregulation rates across systems are only weakly correlated. Over the next five years, I will follow up on this with a series of targeted projects under four long-term objectives: 1) Characterizing system-by-system physiological dysregulation during aging using experimental approaches and bioinformatics approaches to high-throughput data 2) Statistical, mathematical, and theoretical development of multivariate approaches to measure physiological state 3) Developing a practical and theoretical framework for use of biomarkers in physiological ecology 4) Continuing development of a comparative and theoretical framework to understand the evolution of lifespan and aging across the tree of life The results generated will contribute to basic knowledge on the mechanisms and evolution of aging, and to advancing theoretical models of how homeostasis is maintained and adjusted and how it evolves. At a practical level, they will serve to guide the measurement of body condition in ecophysiological research. The interdisciplinary nature of my program will continue to provide an excellent training environment for some of the next generation's most talented HQP.