Lithium Effects on the Brain's Functional and Structural Connectome in the Treatment of Bipolar Disorder

摘要 锂是双相情感障碍（BD）最具体和有效的治疗方法之一，但其机制 行动仍不清楚。这阻碍了监测其影响的方法和新的 具有相似功效和特异性的药物。锂剂治疗双相情感障碍的临床疗效及安全性 对多种大脑生理功能的复杂影响，可能最好使用网络来破译 属性度量方法这种方法是至关重要的，因为它提供了深入了解的功能， 脑网络（例如，抗干扰能力，中心枢纽），这可能与 行为结果此外，还探讨了锂的神经影像学效应与其 对人类的分子效应研究得更少。这项建议涉及这些重要的 通过测量急性脑损伤前后的脑功能和结构连接组学， 和长期锂治疗。我们将研究90种无药物治疗的双相抑郁症 (BDD)II型受试者在基线和锂单药治疗2、8和26周后。我们还将 研究30名密切匹配的健康对照，他们将在相同的时间点进行成像，但不会 接受任何治疗。BDD II受试者将接受静息状态功能磁共振检查 成像（fMRI）扫描和扩散加权结构成像扫描。除了成像，我们将 同时收集外周血淋巴细胞RNA样本，探讨锂诱导的外周血淋巴细胞基因表达。 表情变化。功能和结构扫描将使用图论指标进行分析 (GTM)独立成分分析（伊卡）图论度量超越简单 大脑连接的描述并提供对网络功能的洞察（例如，对破坏的适应能力， 区域中心）。伊卡分析确定了一致的和明确定义的独立成分， 静止状态数据，例如默认模式和显著性网络。我们研究的初步数据 表明锂对GTM和伊卡指标的显著影响以及这些指标变化的相关性。 临床改善的指标。在这个提议中，我们将在最先进的7-T上获取图像 扫描仪，进行严格的运动校正，并应用最先进的GTM和伊卡分析。我们将 将GTA和伊卡指标的变化与短期内抑郁症和情绪的改善相关联 BDD II受试者的长期稳定性。此外，我们将进行探索性分析， 关于外周基因表达的变化与改善 使用GTA指标变化作为中介和使用伊卡的精神病学和情绪稳定性 多模态融合分析这将是一个探索性的分析，以产生数据，为未来更明确的 锂效应的人类和基础科学研究。因此，这项研究将提供独特的数据， 关于锂单药治疗的影像学和分子相关性及其与锂的关系 治疗躁郁症的疗效此外，本研究将提供一个新的范式来研究 使用网络性质度量作为生物标志物的锂和其他精神药物， 治疗监测和药物开发。

ABSTRACT Lithium is one of the most specific and effective treatments for bipolar disorder (BD) yet its mechanism of action remains unclear. This has impeded methods to monitor its effects and the development of new medications with similar efficacy and specificity. Clinical efficacy of lithium in bipolar disorder, and its complex effects on multiple brain physiological functions, may be best deciphered using a network properties-metric approach. This approach is critical because it provides insight into the function of brain networks (e.g., resilience to disruption, central hubs), which is likely to be more closely linked to behavioral outcomes. Furthermore, the relationship of the neuroimaging effects of lithium and its molecular effects in humans has been studied even less. This proposal addresses these important gaps in knowledge by measuring brain functional and structural connectomics before and after acute and longer term treatment with lithium. We will study 90 medication free bipolar disorder depressed (BDD) type II subjects at baseline and after 2, 8 and 26 weeks of lithium monotherapy. We will also study 30 closely matched healthy controls who will be imaged at the same time points but will not receive any treatment. BDD II subjects will undergo resting state functional magnetic resonance imaging (fMRI) scans and diffusion weighted structural imaging scans. In addition to imaging, we will also collect RNA samples from peripheral blood lymphocytes to explore lithium induced peripheral gene expression changes. Functional and structural scans will be analyzed using graph theory metrics (GTM) and Independent Component Analysis (ICA). Graph theory metrics move beyond simple description of brain connectivity and provide insight into network function (e.g., resilience to disruption, regional hubs). ICA analysis has identified consistent and well defined independent components in resting state data e.g the default mode and salience networks. Preliminary data from our studies indicates significant effect of lithium on GTM and ICA metrics and correlation of the changes in these metrics to clinical improvement. In this proposal, we will acquire images on a state-of-the-art 7-T scanner, conduct rigorous motion correction and apply cutting-edge GTM and ICA analytics. We will correlate changes in GTA and ICA metrics to improvement in depression in the short term and mood stability in the longer term in BDD II subjects. Furthermore, we will conduct an exploratory analysis regarding association between changes in peripheral gene expression and improvement in symptomatology and mood stability using the GTA metrics change as mediators and using ICA multimodality fusion analysis. This will be an exploratory analysis to yield data for future more definitive human and basic science studies of lithium effect. This study will therefore provide unique data regarding imaging and molecular correlates of lithium monotherapy and its relationship to lithium efficacy in bipolar disorder. In addition, this study will provide a novel paradigm to investigate effects of lithium and other psychotropics using network-property metrics as biomarkers which can be used for treatment monitoring and drug development.