A Translational and Neurocomputational Evaluation of a D1R Partial Agonist for Schizophrenia
D1R 部分激动剂治疗精神分裂症的转化和神经计算评估
基本信息
- 批准号:10248465
- 负责人:
- 金额:$ 367.52万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-23 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AgingAgonistAntipsychotic AgentsAtlasesAttenuatedBehavioralBiological MarkersBrainChronicClinicalClinical TrialsCognitionCognitiveComputer ModelsDataDevelopmentDopamineDopamine D1 ReceptorDoseDrug IndustryDrug usageEvaluationExhibitsFunctional Magnetic Resonance ImagingFutureGoalsGoldHaloperidolHumanImpaired cognitionInterneuronsInvestmentsKetamineLigandsMATRICS Consensus Cognitive BatteryMapsMeasuresMemory impairmentMissionModelingMolecularMulticenter StudiesNIH Program AnnouncementsNational Institute of Mental HealthNeuropsychologyOutcome MeasurePatientsPatternPerformancePharmaceutical PreparationsPharmacodynamicsPilot ProjectsPlasmaPositron-Emission TomographyPrimatesPsychiatryPsychopharmacologyPublic HealthPublished CommentRecurrenceResearch PersonnelRestRoleSchizophreniaShort-Term MemorySignal TransductionSystemTestingTherapeutic AgentsUp-RegulationVariantWorkbasebiophysical modelbiophysical propertiesclinical developmentclinical effectclinical predictorscomputational neurosciencecostdesigndrug developmentdrug testingfunctional disabilityhippocampal pyramidal neuronimprovedindexingneuroimagingneuroimaging markerneurotransmissionnonhuman primatepatient subsetsprecision medicinepreclinical studyprimary outcomereceptorrelating to nervous systemresponsesimulationtranscriptomicstranslational frameworktranslational neuroscience
项目摘要
PROJECT SUMMARY
This UO1 application is a response to the NIMH Program Announcement intended to accelerate the development of a high
priority therapeutic agent by establishing its dose-related pharmacodynamic effects on biomarkers designed to inform subse-
quent clinical development. Dopamine D1 receptor (D1R) agonism is among the most highly prioritized adjunctive treatment
mechanisms for schizophrenia. Currently, all D1R agonists are also D5R agonists. D1R/D5R agonists have pro-cognitive
and antipsychotic-like effects in preclinical studies, reflecting their ability to stabilize prefrontal cortical network activity in
the face of distractors, and to enhance the precision of spatial working memory (sWM) by enhancing inhibitory tuning of
prefrontal cortical (PFC) functional connectivity (FC). Yet, dose-related benefits of D1R/D5R agonism in patients could not
be demonstrated in prior pilot studies. This application proposes that the testing of D1R/D5R agonists requires both a more
direct translational/computational neuroscience framework (i.e., the most appropriate biomarkers) and a precision medicine
strategy (i.e., the appropriate subpopulation of patients). To accelerate the selection of an optimal dose, we propose a multi-
center study that densely maps the dose-related effects of the D1R/D5R partial agonist, PF-06412562 immediate release (IR),
on three informative translational functional neuroimaging (fMRI) biomarkers as primary outcome measures: i) sWM-related
activation; ii) task-based FC; and iii) resting-state FC in early course schizophrenia patients. Primary Aim 1 will apply a mul-
tivariate analytic strategy to these three outcome measures (sWM-related activation, task-based FC and resting-state FC) to
test if PF-06412562 produces a dose-related effect. This multivariate translational neural marker is designed and powered to
inform a clear Go/No-Go decision with regards to proceeding to a full-scale clinical trial. A Go decision will be indicated if
there is a significant dose-related drug effect on the neural signal measured via the multivariate combination of task-evoked
activation and FC during the sWM task and FC during rest. Conversely, a No-Go decision will be reached if there is an
absence of a dose-related effect on the multivariate index. Secondary Aim 2 will quantify dose-related drug effects on sWM
precision based on behavioral data collected during fMRI. Exploratory Aim 3 will model the biophysical properties of PF-
06412562 in a cortical circuit model capable of sWM simulations, which will simulate hypothesized molecular mechanisms
governing pro-cognitive PF-06412562 effects on sWM. In turn, we will will test if the dose-related pattern of PF-06412562
effects on resting FC in patients maps onto D1R and D5R receptor transcriptomic profiles in humans derived from from Allen
Human Brain Atlas. Finally, Exploratory Aim 4 will study potential clinical predictors and moderators of PF-06412562 ef-
fects on neuroimaging biomarkers. Collectively, this translational biomarker study informs the highest priority experimental
treatment mechanism identified by the NIMH MATRICS Initiative using a precision medicine strategy that targets a specific
subpopulation of early course schizophrenia patients who may pro-cognitively respond to D1R/D5R agonism.
项目摘要
此UO 1应用程序是对NIMH计划公告的响应,旨在加速开发一个高性能的
通过确定其对生物标志物的剂量相关药效学效应,
quent临床开发。多巴胺D1受体(D1 R)激动剂是最优先的连续治疗之一
精神分裂症的发病机制目前,所有D1 R激动剂也是D5 R激动剂。D1 R/D5 R激动剂具有促认知作用,
和抗精神病药样作用,反映了它们稳定前额叶皮层网络活动的能力,
干扰物的面孔,并通过增强空间工作记忆(sWM)的抑制性调谐来提高空间工作记忆(sWM)的精度。
前额叶皮层(PFC)功能连接(FC)。然而,D1 R/D5 R激动剂在患者中的剂量相关益处不能
在之前的试点研究中得到证实。本申请提出,D1 R/D5 R激动剂的测试需要更多的
直接翻译/计算神经科学框架(即,最合适的生物标志物)和精准医学
策略(即,适当的患者亚群)。为了加速选择最佳剂量,我们提出了一种多-
一项密集绘制D1 R/D5 R部分激动剂PF-06412562速释(IR)剂量相关效应的中心研究,
三种信息性翻译功能性神经成像(fMRI)生物标志物作为主要结果指标:i)sWM相关
激活; ii)基于任务的FC;和iii)在早期病程精神分裂症患者的静息状态FC。主要目标1将应用穆尔-
对这三种结果测量(sWM相关激活,基于任务的FC和静息状态FC)进行变量分析策略,
检测PF-06412562是否产生剂量相关效应。这种多变量翻译神经标记物被设计和供电,
告知关于进行全面临床试验的明确的进行/不进行决定。如果出现以下情况,将指示执行决定
通过任务诱发的多变量组合测量的神经信号上存在显著的剂量相关的药物效应,
sWM任务期间的激活和FC以及休息期间的FC。相反,如果存在以下情况,则将做出不通过决定:
对多变量指数无剂量相关影响。次要目的2将量化药物对sWM的剂量相关影响
精确度基于功能性磁共振成像期间收集的行为数据。探索性目标3将模拟PF的生物物理特性,
06412562在能够进行sWM模拟的皮质回路模型中,其将模拟假设的分子机制
控制PF-06412562对sWM的促认知作用。反过来,我们将检测PF-06412562的剂量相关模式是否
对患者静息FC的影响映射到源自艾伦的人体D1 R和D5 R受体转录组学谱
人脑图谱。最后,探索性目的4将研究PF-06412562 ef的潜在临床预测因子和调节因子。
影响神经影像学生物标志物。总的来说,这项翻译生物标志物研究为最高优先级的实验提供了信息。
NIMH MATRICS计划使用针对特定的精确医学策略确定的治疗机制
可能对D1 R/D5 R激动剂有前认知应答的早期病程精神分裂症患者亚群。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Sex-Specific Genetic and Transcriptomic Liability to Neuroticism.
- DOI:10.1016/j.biopsych.2022.07.019
- 发表时间:2023-02-01
- 期刊:
- 影响因子:10.6
- 作者:
- 通讯作者:
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{{ truncateString('ALAN ANTICEVIC', 18)}}的其他基金
A Translational and Neurocomputational Evaluation of a D1R Partial Agonist for Schizophrenia
D1R 部分激动剂治疗精神分裂症的转化和神经计算评估
- 批准号:
10021712 - 财政年份:2019
- 资助金额:
$ 367.52万 - 项目类别:
Brain Network Changes Accompanying and Predicting Responses to Pharmacotherapy in OCD
伴随并预测强迫症药物治疗反应的大脑网络变化
- 批准号:
10543781 - 财政年份:2018
- 资助金额:
$ 367.52万 - 项目类别:
Brain Network Changes Accompanying and Predicting Responses to Pharmacotherapy in OCD
伴随并预测强迫症药物治疗反应的大脑网络变化
- 批准号:
10311477 - 财政年份:2018
- 资助金额:
$ 367.52万 - 项目类别:
Development of Thalamocortical Circuits and Cognitive Function in Healthy Individuals and Youth At-Risk for Psychosis
健康个体和有精神病风险的青少年丘脑皮质回路和认知功能的发展
- 批准号:
9893033 - 财政年份:2018
- 资助金额:
$ 367.52万 - 项目类别:
Mapping the Longitudinal Neurobiology of Early-course Schizophrenia
绘制早期精神分裂症的纵向神经生物学图谱
- 批准号:
10215418 - 财政年份:2017
- 资助金额:
$ 367.52万 - 项目类别:
Mapping the Longitudinal Neurobiology of Early-course Schizophrenia
绘制早期精神分裂症的纵向神经生物学图谱
- 批准号:
9910455 - 财政年份:2017
- 资助金额:
$ 367.52万 - 项目类别:
Characterizing Schizophrenia Progression via Multi-modal Neuroimaging and Computation
通过多模式神经影像和计算表征精神分裂症进展
- 批准号:
9272935 - 财政年份:2016
- 资助金额:
$ 367.52万 - 项目类别:
Administrative Supplement to 1R03MH105765: Neuropsychiatric Classification via Connectivity and Machine Learning
1R03MH105765 的行政补充:通过连接和机器学习进行神经精神分类
- 批准号:
9076865 - 财政年份:2014
- 资助金额:
$ 367.52万 - 项目类别:
Neuropsychiatric Classification via Connectivity and Machine Learning
通过连接和机器学习进行神经精神分类
- 批准号:
8808026 - 财政年份:2014
- 资助金额:
$ 367.52万 - 项目类别:
Characterizing Cognitive Impairment in Schizophrenia via Computational Modeling a
通过计算模型描述精神分裂症的认知障碍
- 批准号:
8715432 - 财政年份:2012
- 资助金额:
$ 367.52万 - 项目类别:
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