Characterization of physiological systems: biomarkers and statistical methods to measure changes in physiology across time and species

生理系统的表征：测量跨时间和物种生理变化的生物标志物和统计方法

• 批准号: 402079-2011
• 负责人: Cohen, Alan
• 金额: $ 2.11万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=506531
• 关键词: Characterization; physiological; systems; biomarkers; statistical

Biologists have long sought to explain variation in animal life history traits (lifespan, reproductive rate, development rate) as a result of environment, and more recently to explain how natural selection works through physiology to affect life histories. However, the basic predictions have not been well supported: although life history traits often correlate with physiological markers such as hormones, immune function, and oxidative stress, these correlations vary in unpredictable ways across time and species. At the same time, aging scientists still have no convincing theory to explain the underlying physiological mechanisms of aging. Recently, I have proposed a new theory of physiology, aging, and evolution that explains these questions. Many aspects of physiology are linked in complex regulatory networks. Over time, the regulatory system can break down, resulting aging. These physiological systems will have properties such as evolvability and stability over time (e.g. resulting in longer lifespan) that will be determined by their structure and not be evident from their components alone. Here, I propose a research program to begin understanding these physiological systems from an ecological, evolutionary, and statistical perspective. Working under the hypothesis that directly measurable aspects of physiology are imperfect proxies for underlying processes, I will use sophisticated statistical tools such as PCA, SEM, and Bayesian multi-level models to identify and characterize these processes, establish their effects on each other over time, and measure how all of this varies at different time scales and across species. I will work on three systems to represent three timescales and levels of analysis: Tree Swallows will be used to measure changes in physiology over a short-term stress response, Bighorn Sheep will be used to measure changes over seasons and years, and an existing physiological database on 100+ bird species will be used to characterize changes over evolutionary time. The results are expected to establish new paradigms for (a) how ecologists study physiology, (b) how natural selection affects physiology and aging, and (c) the physiological processes underlying aging and chronic disease.

生物学家长期以来一直试图解释动物生活史特征（寿命、繁殖率、发育率）的变化是环境的结果，最近又试图解释自然选择是如何通过生理学影响生活史的。然而，基本的预测并没有得到很好的支持：尽管生活史特征通常与激素、免疫功能和氧化应激等生理标记相关，但这些相关性在不同的时间和物种中以不可预测的方式变化。与此同时，衰老科学家仍然没有令人信服的理论来解释衰老的潜在生理机制。最近，我提出了一个关于生理、衰老和进化的新理论来解释这些问题。生理学的许多方面在复杂的调节网络中相互联系。随着时间的推移，调节系统会崩溃，导致衰老。这些生理系统将具有随时间推移的可进化性和稳定性（例如导致更长的寿命）等特性，这些特性将由它们的结构决定，而不仅仅是它们的组成部分。在这里，我提出了一个研究计划，从生态学、进化论和统计学的角度开始理解这些生理系统。在假设生理学的直接可测量方面是潜在过程的不完美代理的情况下，我将使用复杂的统计工具，如PCA， SEM和贝叶斯多级模型来识别和表征这些过程，建立它们随着时间的推移相互影响，并测量所有这些在不同时间尺度和物种之间的变化。我将研究三个系统来代表三个时间尺度和分析水平：树燕将用于测量短期应激反应的生理变化，大角羊将用于测量季节和年份的变化，现有的100多种鸟类的生理数据库将用于表征进化时间的变化。这些结果有望为(a)生态学家如何研究生理学，(b)自然选择如何影响生理学和衰老，以及(c)衰老和慢性疾病背后的生理过程建立新的范式。