Burton Charles P, Chumin Evgeny J, Collins Alyssa Y, Persohn Scott A, Onos Kristen D, Pandey Ravi S, Quinney Sara K, Territo Paul R
Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis IN 46202 USA.
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis IN 46202.
bioRxiv. 2023 Dec 7:2023.11.10.566574. doi: 10.1101/2023.11.10.566574.
Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core.
Chronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling.
Pharmacokinetics of LEV showed a sex and dose dependence in C, CL/F, and AUC, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e. positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling.
This study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration- dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value towards informing clinical study design.
亚临界癫痫样活动与认知功能受损有关，常见于阿尔茨海默病（AD）患者。抗惊厥药物左乙拉西坦（LEV）目前正在进行临床试验，评估其降低AD患者癫痫样活动和改善认知功能的能力。本研究的目的是将药代动力学（PK）、医学影像网络分析、基因转录组学和PK/PD建模应用于一组淀粉样蛋白生成小鼠，以使用MODEL-AD临床前测试核心的严格临床前流程，确定LEV如何以剂量依赖的方式恢复或驱动小鼠脑网络的改变。
根据PK模型按异速生长比例缩放的临床剂量水平，对两性5XFAD小鼠给予慢性LEV治疗3个月。数据收集和分析采用多模态方法，包括F-FDG PET/MRI成像与分析、转录组分析以及PK/PD建模。
LEV的药代动力学在C、CL/F和AUC方面表现出性别和剂量依赖性，通过模拟来估计给药方案。10、30和56mg/kg的慢性给药显示，F-FDG在脑摄取方面存在特定区域差异，在全脑协方差测量中，如聚类系数、度、网络密度和连接强度（即正性和负性）也存在差异。此外，通过nanoString进行的转录组分析显示，与F-FDG摄取和网络变化一致的通路中基因表达存在剂量依赖性变化，PK/PD建模显示关键基因存在浓度依赖性，但网络协方差建模不存在。
本研究是第一份详细描述5XFAD小鼠中LEV给药导致的代谢协方差和转录组网络变化之间关系的报告。总体而言，我们的结果突出了基于剂量和性别的非线性动力学，其中基因表达分析显示LEV存在剂量和浓度依赖性变化，以及与人类AD相关的脑代谢和/或脑稳态机制，这与F-FDG图像的网络协方差分析密切相关。总体而言，本研究展示了多模态连接组学、转录组学和药代动力学方法在临床前研究中进一步研究剂量依赖性关系的价值，对临床研究设计具有转化价值。
