Neuronal network screening and predictive profiling of pharmacological efficacy in a rat model of autism spectrum disorder

自闭症谱系障碍（ASD）和智力残疾（ID）是复杂的，异质性的疾病，其基础细胞和电路病理生理学知之甚少。然而，已知单基因突变占ASD个体和并发中度至重度ID的病例的很大比例。临床上，焦虑症和恐惧症在ASD个体中非常普遍，并且通常用于告知诊断1。编码跨膜蛋白神经连接素-3的基因中的突变与ASD和ID高度相关。最近，我们报道了缺乏Nlgn 3基因的大鼠（Nlgn 3-γ）表现出健壮的、恐惧/焦虑相关的表型2。这种行为异常与大脑的一个区域有关，该区域与适当的生存行为的协调密切相关，即中脑导水管周围灰质（PAG）。我们已经表明，与野生型对照相比，Nlgn 3-/y大鼠PAG背侧部分的神经元本质上是过度兴奋的，并且这种细胞异常可能是飞行冻结行为失衡的基础2。据我们所知，这是第一次，PAG异常已被链接到ASD，并因此突出的关键需要，以提高对参与神经发育障碍的脑回路的理解，以允许改进的，精确的治疗tools.Therefore，本项目的目的1是进一步了解神经回路机制驱动异常的恐惧反应在Nlgn 3-/y大鼠。通过同时记录来自PAG和一系列解剖学相关结构的脑深部LFP以及脑电描记术（EEG），学生将研究固有的PAG超兴奋性如何在大规模恐惧网络互动中表现出来，以及这如何与行为反应相关。脑深部LFP和表面EEG信号之间的功能联系/相关性也将被量化，以提供可翻译的生物标志物。这种治疗结果的变化是临床上的一个主要问题。因此，本项目的目的2是检查阿巴氯芬（一种强效GABA B激动剂）治疗对Nlgn 3-/y大鼠中观察到的稳健表型的影响。为了做到这一点，该药物将在开发过程中的不同时间点应用，无论是全身性的还是局部脑区（例如PAG），同时测量其对神经网络活动和行为反应的影响。在ASD 3中Arbacolfen治疗的可变疗效突出了对靶向方法的未满足需求，以识别具有较高治疗反应可能性的个体。Kristoffer Månsson博士（Karolinska Institutet）最近的研究表明，每时每刻的大脑信号变异性可以可靠地预测社交焦虑患者的精神治疗结果4，这是一种常见的ASD合并症。因此，目的3是测试神经元网络生物标志物如何有效地预测药理学功效。要做到这一点，学生将首先研究LFP/EEG信号变异性是否可以用于预测Nlgn 3-/y大鼠模型中的阿巴氯芬治疗结果。重要的是，学生将有机会将这些分析的应用扩展到其他单基因ASD大鼠模型的一系列行为和药物治疗数据。该项目的结果将加深我们对Nlgn 3-/y大鼠模型，并深入了解ASD和ID人群亚群的靶向药物治疗。这些发现将推动分析方法的发展，以优化生物转化，数据转化为预测模型。

Autism spectrum disorders (ASDs) and intellectual disabilities (IDs) are complex, heterogeneous disorders with poorly understood underlying cellular and circuit pathophysiology. Monogenic mutations are, however, known to account for a large proportion of cases where individuals present with ASD and co-occurring moderate to severe ID. Clinically, anxiety disorders and phobias are highly prevalent in individuals with ASD and are often used to inform diagnosis1.Mutations in the gene encoding for transmembrane protein neuroligin-3 are highly correlative with ASD and ID. Recently, we reported that rats lacking the Nlgn3 gene (Nlgn3-/y) exhibit robust, fear/anxiety related phenotypes2. This behavioral abnormality has been linked to a region of the brain critically involved in the orchestration of appropriate survival behaviors, the periaqueductal gray (PAG). We have shown that neurons in the dorsal part of the PAG are intrinsically hyper-excitable in Nlgn3-/y rats compared to wild type controls and that this cellular abnormality may underlie the imbalance in flight-freeze behaviors observed2. To our knowledge, this is the first time that PAG abnormality has been linked to ASD and as such highlights the critical need for improved understanding of brain circuitry involved in neurodevelopmental disorders to allow development of improved, precision therapeutic tools.Therefore, Aim 1 of this project is to further understand the neural circuit mechanisms driving aberrant fear responses in Nlgn3-/y rats. By simultaneously recording deep-brain LFP from PAG and a range of anatomically linked structures, alongside electroencephalography (EEG), the student will examine how intrinsic PAG hyper-excitability manifests in large-scale fear network interaction and how this correlates to behavioral responses. Functional links/correlations between deep brain LFP and surface EEG signals will also be quantified to deliver translatable biomarkers.Pharmacological treatment studies in people with ASD have met been variable in success3. This variation is treatment outcome is a major issue clinically. Therefore, Aim 2 of this project is to examine the effect of Arbaclofen (a potent GABA B agonist) treatment on observed, robust phenotypes in Nlgn3-/y rats. To do this, the drug will be applied at various time points during development, either systemically or to local brain regions (e.g. PAG) while measuring its impact upon neural network activity and behavioral responses.The variable efficacy of Arbacolfen treatment in ASD3 highlights the unmet need for targeted approaches to identifying individuals with higher likelihood of treatment responsivity. Recent work from Dr Kristoffer Månsson (Karolinska Institutet) has revealed that moment-to-moment brain signal variability can reliably predict psychiatric treatment outcomes in patients with social anxiety4, a common ASD co-morbidity. Therefore, Aim 3 is to test how effectively neuronal network biomarkers can predict pharmacological efficacy. To do this, the student will first investigate whether LFP/EEG signal variability can be used to predict Arbaclofen treatment outcomes in the Nlgn3-/y rat model. Importantly, the student will have opportunity to expand the application of these analyses to a range of behavioral and pharmacological treatment data available from other monogenic rat models of ASD.The results of this project will deepen our understanding of brain networks underlying the behavioural deficits observed in Nlgn3-/y rat model and give insight into targeted drug treatment for subpopulations of people with ASD and ID. The findings will drive development of analytical methods to optimize the transformation of biological data into predictive models.