An In Vivo Voltammetric Serotonin Biomarker for Antidepressant Efficacy

 描述(申请人提供)：在抗抑郁药物开发的临床前阶段，没有可靠的筛查工具来预测临床结果，这是一个分析缺陷，导致最近用于抗抑郁药物发现的资源减少。鉴于到2030年抑郁症预计将成为全球主要疾病负担之一，创造准确筛查 抗抑郁治疗的疗效。这项拟议研究的长期目标是了解抗抑郁剂如何调节5-羟色胺系统，从而建立一个用于早期药物筛选的5-羟色胺生物标志物。这项建议的目标是：a)能够在体内精确测量小鼠海马区5-羟色胺的基础水平和诱发水平，b)建立控制健康和抑郁小鼠细胞外5-羟色胺的机制，以及c)以不同的抗抑郁剂调节5-羟色胺的方式将化学模式与临床疗效相关联。我们的初步数据有力地支持了我们提出的目标。我们在用快速扫描循环伏安法和一种新的方法--快速扫描控制吸附伏安法首次测量海马区基础和诱发的5-羟色胺方面取得了重大进展。此外，我们测量了抑郁小鼠模型的基础和诱发的5-羟色胺，发现抑郁小鼠的5-羟色胺水平更高，通过计算模型提出了这一发现的机制。最后，我们在数学上将不同抗抑郁药后5-羟色胺的细胞外反应与临床疗效相关联，并对一种已知化合物的疗效做出了准确的预测。这些初步数据使我们能够做出中心假设，即抗抑郁剂通过不同的机制影响细胞外5-羟色胺水平，产生独特的“5-羟色胺信号”，可用于预测其临床疗效的可能程度。其基本原理是，通过将化学5-羟色胺模式与临床疗效相关联，“5-羟色胺生物标记物”可以识别临床上最有效的化合物。我们采取跨学科的方法，通过三个具体的目标来检验中心假设：1.对海马体中5-羟色胺的环境和诱发化学进行基本的FSCV测量。2.建立健康和抑郁动物模型体内调节细胞外5-羟色胺水平的机制。3.抗抑郁药对细胞外5-羟色胺(环境和诱发)的影响能力与临床疗效的相关性。这种方法具有创新性，因为它将先进的分析技术、数学和动物行为结合在一起，以应对重要的分析挑战。这项拟议的研究具有重要意义，因为它最终可以提供一种通过5-羟色胺生物标记物筛选抗抑郁药物的方法。拥有早期筛查工具是药物发现者重新努力改善抗抑郁治疗的强大动力，使个人、社会和经济受益。这项研究还将对更广泛的研究议程产生影响。5-羟色胺测量工具和体内5-羟色胺机制的工作模型可以开启和推进与5-羟色胺相关的全新研究。

 DESCRIPTION (provided by applicant): There are no reliable screening tools that predict clinical outcome in the preclinical stages of antidepressant drug development, this is an analytical shortcoming that has led to a recent decline in resources for antidepressant drug discovery. Given that by 2030 depression is predicted to become one of the leading global disease burdens, it is particularly pertinent to create analytical tools that accurately screen the efficacy of antidepressant therapies. The long-term goal of the proposed research is to understand how antidepressants modulate the serotonin system thereby establishing a serotonin biomarker for early stage drug screening. The objectives of this proposal are to a) enable precise measurements of serotonin's basal and evoked levels in vivo in the mouse hippocampus, b) establish the mechanisms that control extracellular serotonin in healthy and depressed mice and c) correlate chemical patterns in the way that different antidepressants modulate serotonin to clinical efficacy. Our preliminary data strongly support our proposed objectives. We have made significant progress in making the first measurements of basal and evoked serotonin in the hippocampus with fast scan cyclic voltammetry and a novel method, fast scan controlled adsorption voltammetry. Furthermore, we measured basal and evoked serotonin in depressed mouse models and found that serotonin levels are higher in depressed mice, proposing a mechanism for this finding via computational modeling. Finally, we mathematically correlated serotonin's extracellular response after different antidepressants to clinical efficacy and made an accurate prediction of efficacy for a known compound. This preliminary data allows us to make the central hypothesis that antidepressants influence extracellular levels of serotonin via different mechanisms, giving rise to unique "serotonin signatures", which can be used to predict their likely degree of clinical efficacy. The rationale i that by correlating chemical serotonin patterns to clinical efficacy, a `serotonin biomarker' can identify the most clinically efficacious compounds. We take an interdisciplinary approach to test the central hypothesis via three specific aims: 1. Perform Fundamental FSCV Measurements of Serotonin's Ambient and Evoked Chemistry in the Hippocampus. 2. Establish Mechanisms Regulating In Vivo Extracellular Serotonin Levels in Healthy and Depressed Animal Models. 3. Correlate the Ability of Antidepressants to Influence Extracellular Serotonin (Ambient and Evoked) to Clinical Efficacy. The approach is innovative because it brings together advanced analytical techniques, mathematics and animal behavior to tackle important analytical challenges. The proposed research is significant because it can ultimately provide a means to screen antidepressants via a serotonin biomarker. Having an early stage screening tool is a powerful impetus for drug discoverers to resume their efforts in improving antidepressant therapies, benefiting individuals, society and the economy. The research will also have impact on a much broader research agenda. Serotonin measurement tools and working models of in vivo serotonin mechanisms can open and advance entire new lines of serotonin-related research.