Complex Dynamic Systems in Mood Disorders

描述（由申请人提供）：此K18应用程序旨在为重度抑郁症（MDD）和双相情感障碍（BD）的临床和生物标志物数据的复杂动态系统分析提供高级指导。MDD是一种严重的使人衰弱的疾病，预计到2020年将成为全球第二大残疾原因。双相情感障碍（BD）是一种终身、慢性和高度复发的情绪障碍，其特征是躁狂或轻躁狂发作和重度抑郁发作，是全球十大残疾原因之一。差距是MDD和BD的临床相关表型和病理生理学描述不佳。一个障碍是普遍使用静态线性统计措施来评估盈亏变量之间复杂的动态关系。传统的分析假设信号是线性和平稳的，并且在单个（特征时间）尺度标准上操作，这通常被现实世界的信号违反，即，它们是高度非线性的，在多个时间尺度上操作，并且由于生理和病理相变和其他突变（分叉）而也是非平稳的。 这个K18应用程序的发展目标是学习方法来分析复杂的动态非线性数据，应用于情绪障碍的研究，通过教学法和监督分析指导Ary L.他是贝斯以色列女执事医疗中心雷伊医学非线性动力学研究所和哈佛韦斯利生物启发工程研究所的主任。 该试点项目将使用24小时可穿戴设备分析5名MDD患者、5名年龄和性别匹配的BP患者和5名匹配的健康对照者的觉醒、心率、呼吸、运动和睡眠阶段的测量结果。这些分析将a）探索MDD和健康对照之间的差异; B）BD和健康对照之间的差异;以及c）MDD和BD之间的差异。 分析复杂动态系统的方法可以为理解情绪障碍打开创新的新窗口。申请人的长期目标是能够将非线性动力学应用于寻找生物学相关表型和临床有用的生物标志物的艰巨问题。 公共卫生相关性：这个研究培训计划将教申请人如何使用先进的统计方法来分析复杂的数据，随着时间的推移，从患者的情绪障碍。语音模式、心率、呼吸模式和24小时内的运动是几个例子。这些方法可以导致更好的诊断，更好的方法来理解情绪障碍的生物学，以及测量治疗反应的方法。

DESCRIPTION (provided by applicant): This K18 application is to provide advanced mentorship in complex dynamic system analyses of clinical and biomarker data for major depressive disorder (MDD) and bipolar disorder (BD). MDD is a serious, debilitating illness that is projected to become the second global leading cause of disability by 2020. Bipolar disorder (BD) is a lifelong, chronic and highly recurrent, mood disorder characterized by episodes of mania or hypomania and episodes of major depression and is one of the top 10 causes of disability worldwide. The gap is that clinically relevant phenotypes and pathophysiology of MDD and BD are poorly delineated. One obstacle has been the prevalent use of static linear statistical measures to assess complex dynamic relationships between waxing and waning variables. Conventional analyses assume that signals are linear and stationary, and operate on a single (characteristic time) scale criteria that are routinely violated by real-world signals, i.e, they are highly nonlinear, operate on multiple time scales and are also nonstationary due to physiologic and pathologic phase transitions and other abrupt changes (bifurcations). The developmental aim of this K18 application is to learn methods to analyze complex dynamic nonlinear data to apply to the study of mood disorders with 12 months of intensive mentorship to the applicant through didactics and supervised analyses mentored by Ary L. Goldberger, Director of the Rey Institute for Nonlinear Dynamics in Medicine at Beth Israel Deaconess Medical Center and Wyss Institute for Biological Inspired Engineering at Harvard. The pilot project will analyze measures of arousal, heart rate, respiration, movement, and sleep stages using a 24 hour wearable devices from 5 patients with MDD, 5 age and sex matched patients with BP, and 5 matched healthy controls. These analyses will a) explore differences between MDD and healthy controls; b) BD and healthy controls; and c) MDD and BD. Methods for analyzing complex dynamic systems can open innovative new windows into understanding mood disorders. The applicant's long-term goal is to be able to apply nonlinear dynamics to the daunting problem of finding biologically relevant phenotypes and clinically useful biomarkers. PUBLIC HEALTH RELEVANCE: This research training program will teach the applicant how to use advanced statistical methods to analyze complicated data that vary over time from patients with mood disorders. Voice patterns, heart rate, breathing patterns, and movements over 24 hours are a few examples. These methods can lead to better diagnoses, better ways to understand the biology of mood disorders, and ways to measure response to treatment.