Circadian Role in Diurnal Pattern of Cardiovascular Risk

描述(申请人提供)：大量流行病学研究表明，心脏性猝死、肺栓塞、心肌梗死和中风有24小时的每日模式，高峰大致在上午9：00至11：00之间。这种日常模式背后的机制尚不清楚。作为阐明机制的重要的第一步，我们提出了一种方法，将昼夜心血管生理学与使用我们开发的并被证明是心脏动力学和心脏风险的敏感指标的新的统计方法分析唯一的现有数据集相结合。我们的主要机制目标是区分(I)内在的昼夜节律和(Ii)活动水平的昼夜节律变化对心脏动力学的单独影响。我们将分析现有的四个生理相关变量(心率、血压、温度和活动水平)的数据集，这些变量是通过两个互补的昼夜节律方案在表面上健康的个体中同时记录的，其中受试者的行为(包括活动水平和睡眠-觉醒周期)受到控制，环境是恒定的。这些方案是：(I)10天强制去同步化方案(其中受试者的睡眠-觉醒周期调整为28小时，以便他们的行为发生在所有昼夜节律阶段)和(Ii)38小时恒定常规方案(其中受试者保持清醒和半卧位)。核心体温将被用作昼夜节律的相位标记。从这些数据中，我们将用我们新颖而灵敏的分析工具提取动力结构的互补统计指数：(I)累积变化幅度分析；(Ii)去趋势波动分析；(Ii)震级标度分析；以及(Iii)多重分形分析。对这些与昼夜节律阶段或单独的行为模式相关的统计数据的分析，可能会揭示与心血管易损性的日常模式相关的心脏动力学，并将使我们能够推断可能构成心脏动力学基础的变量之间的机械联系。此外，通过比较在相同实验室条件下从年轻人和老年人获得的指数，我们的目标是揭示心脏动力学中与年龄相关的特定变化，这些变化可能是与年龄相关的心脏风险增加的基础。我们未来的目标(超越这一应用)将是确定在健康个体中的结果是否与已知的心血管风险患者有关。我们认为，这类研究最终可能有助于通过改变活动水平或定时药物干预来合理化心血管疾病的时间生物学治疗。

DESCRIPTION (provided by applicant): Numerous epidemiological studies demonstrate that sudden cardiac death, pulmonary embolism, myocardial infarction, and stroke have a 24-hour daily pattern with a broad peak between 9:00 to 11:00 AM. The mechanisms underlying this daily pattern are unknown. As an important first step to elucidate mechanisms, we propose an approach that combines circadian cardiovascular physiology with analysis of a unique existing data set using novel statistical approaches that we have developed and shown to be sensitive indicators of cardiac dynamics and cardiac risk. Our primary mechanistic aim is to distinguish the separate effects upon cardiac dynamics of (i) the intrinsic circadian rhythm and of (ii) circadian variations in activity level. We will analyze existing data sets of four physiologically related variables (heart rate, blood pressure, temperature and activity level) that were simultaneously recorded in ostensibly healthy individuals throughout two complementary circadian protocols in which subjects' behaviors (including activity level and sleep-wake cycle) are controlled and the environment is constant. The protocols were: (i) a 10 day Forced Desynchrony protocol (wherein subjects' sleep-wake cycles are adjusted to 28 hours so that their behaviors occur across all circadian phases) and (ii) a 38 hour constant routine protocol (wherein subjects remain awake and semi-recumbent). Core body temperature will be used as a circadian phase marker. From these data we will extract complementary statistical indices of dynamical structure with our novel and sensitive analysis tools: (i) Cumulative Variation Amplitude Analysis; (ii) Detrended Fluctuation Analysis; (ii) Magnitude Scaling Analysis; and (iii) Multifractal Analysis. Analyses of these statistics in relation to the phase of the circadian rhythm, or separately the behavioral pattern, may reveal cardiac dynamics related to the daily pattern of cardiovascular vulnerability, and will enable us to deduce mechanistic links among variables that could underlie the cardiac dynamics. Further, by comparing indices obtained from young and older individuals under identical laboratory conditions, we aim to uncover specific age-related changes in cardiac dynamics that may underlie the age-related increase in cardiac risk. Our future aim (beyond this application) would be to determine whether the results in healthy individuals relate to patients with known cardiovascular risk. We believe that such studies may ultimately help rationalize chronobiological therapies for cardiovascular diseases in terms of modification of activity levels or timed pharmacological intervention.