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
基本信息
- 批准号:10215418
- 负责人:
- 金额:$ 17.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-02-01 至 2022-11-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAdmission activityAffectAftercareAgeAntipsychotic AgentsBehavioralBeliefBrain imagingChinaChronicChronic SchizophreniaClinicClinicalClinical MarkersClinical ResearchCognitionCognitive deficitsCollaborationsComplexCorpus striatum structureDataData SetDisease ProgressionEarly DiagnosisEarly InterventionEarly treatmentExhibitsFunctional disorderFutureGenderGoalsHeterogeneityHippocampus (Brain)HospitalsHumanImpaired cognitionInfrastructureInterventionKnowledgeLinkLongitudinal StudiesMapsMeasuresMethodsNational Institute of Mental HealthNeurobiologyNeurocognitiveNeurodevelopmental DisorderNeurosciencesParticipantPathway interactionsPatientsPatternPharmaceutical PreparationsPhasePrognosisPsychosesResearchSample SizeSchizophreniaSensorySeveritiesSiteSourceStructureSymptomsSynapsesTestingThalamic NucleiThalamic structureTimeWorkbaseclinical applicationclinical effectclinically relevantcognitive functionconnectomefunctional declinefunctional disabilityimaging biomarkerimprovedindividualized medicinelongitudinal designmultimodalityneuroimagingneuroimaging markerneuropsychiatrynovelpre-clinicalprogramsrecruitreduce symptomsrelating to nervous systemresponders and non-respondersresponsestandard caretargeted treatmenttraittreatment responderstreatment response
项目摘要
PROJECT SUMMARY
Schizophrenia (SCZ) is a profoundly disabling neurodevelopmental disorder causing marked functional impairment. SCZ
is hypothesized to arise from synaptic disturbances affecting large-scale neural connectivity along cortico–thalamic-
striatal–cortical (CTSC) pathways. Neuroimaging evidence supports this view by showing alterations in associative
cortices and connectivity disruptions across CTSC circuits in chronic SCZ. Yet, the complex evolving neurobiology of
early-course SCZ remains uncharacterized. This limits treatments for early illness phases when intervention is crucial by
capitalizing on the narrow `window' of opportunity to halt disease progression. Thus, understanding the neurobiology of
early-course SCZ is a major objective for early detection, prognosis prediction and targeted individualized therapy. A
major complicating factor in many SCZ studies is the confounding presence of antipsychotic treatment. Thus, our goal is
to characterize co-occurring functional and structural dysconnectivity in unmedicated early-course SCZ and quantify
neural changes in relation to cardinal SCZ symptoms, cognitive deficits and treatment response. To achieve this, we will
examine longitudinal progression of neural dysconnectivity in 150 unmedicated early-course SCZ patients after their
initial admission into clinics affiliated with West China Hospital. We will follow patients longitudinally at 6, 12, and 24
months later in comparison with 150 matched healthy controls. We will use state-of-the-art functional and structural
methods optimized by the Human Connectome Project to achieve cutting-edge multi-modal neuroimaging integration. As
noted, mounting evidence implicates CTSC loops in SCZ, particularly higher-order prefrontal and thalamic regions (e.g.
medio-dorsal structures), suggesting mechanistic links between CTSC dysfunction and SCZ symptoms. Thus, first we aim
to test if the identified CTSC markers exhibit concurrent (or dissociable) structural and functional alterations in
unmedicated SCZ patients and if these circuits alter longitudinally. Second, we will test if structural and functional
neuroimaging alterations relate to severity of cardinal SCZ symptoms and cognitive deficits. This provides a much-needed
mapping between longitudinal CTSC dysconnectivity, symptoms and cognition in SCZ. Critically, this balanced
longitudinal design can distinguish `state' versus `trait' neuroimaging markers during early illness course in relation to
clinically relevant variables. Finally, it is well established that many SCZ patients do not respond well to antipsychotics.
Yet, the neural markers of poor treatment response remain unmapped (and conversely treatment response). A key
advantage of the proposed U.S.-China partnership is precisely the capacity to longitudinally study large sample sizes
starting from medication-free observations, afforded by extensive and robust recruitment infrastructure at West China
Hospital. Thus, our third aim is to quantify longitudinal structural and functional CTSC dysconnectivity in relation to
treatment response. Collectively, this study will map longitudinal `state' versus `trait' neural markers starting from
medication-free early illness stages (Aim 1), relate these changes to symptom dynamics (Aim 2) and treatment response
(Aim 3). This mapping is vital to inform future work aimed at maximizing individualized early intervention strategies.
项目摘要
精神分裂症(SCZ)是一种严重的致残性神经发育障碍,导致明显的功能障碍。SCZ
被假设是由突触紊乱引起的,突触紊乱影响了沿着皮质-丘脑-
纹状体-皮质(CTSC)通路。神经影像学证据支持这一观点,显示了相关的改变,
慢性SCZ中CTSC回路的皮质和连接中断。然而,复杂的进化神经生物学,
早期SCZ仍无特征。这限制了早期疾病阶段的治疗,而干预是至关重要的,
利用狭窄的机会“窗口”阻止疾病进展。因此,了解神经生物学
早期病程SCZ是早期发现、预后预测和针对性个体化治疗的主要目标。一
在许多SCZ研究中,一个主要的复杂因素是抗精神病药物治疗的混杂存在。因此,我们的目标是
描述未用药的早期SCZ中同时发生的功能和结构连接障碍,并量化
与主要SCZ症状、认知缺陷和治疗反应相关的神经变化。为了实现这一目标,我们将
在150名未用药的早期SCZ患者中检查神经连接障碍的纵向进展,
首次入住华西医院附属诊所。我们将在6岁、12岁和24岁时纵向随访患者
月后与150名匹配的健康对照组进行比较。我们将使用最先进的功能和结构
人类连接组项目优化的方法,以实现尖端的多模态神经成像集成。作为
注意到,越来越多的证据表明CTSC环在SCZ,特别是高阶前额叶和丘脑区域(例如,
中背结构),表明CTSC功能障碍和SCZ症状之间的机制联系。因此,首先我们的目标是
为了测试鉴定的CTSC标志物是否在CTSC中表现出同时的(或可分离的)结构和功能改变,
未经药物治疗的SCZ患者以及这些回路是否纵向改变。第二,我们将测试结构和功能
神经影像学改变与主要SCZ症状和认知缺陷的严重程度有关。这提供了一个急需的
纵向CTSC连接障碍、症状和SCZ认知之间的映射。关键是,这种平衡
纵向设计可以区分早期病程中的“状态”与“特质”神经影像学标志物,
临床相关变量。最后,许多SCZ患者对抗精神病药物的反应不佳,这是公认的。
然而,治疗反应差的神经标志物仍然未映射(反之亦然)。一个关键
美国提议的优势-中国伙伴关系恰恰是纵向研究大样本量的能力
从中国西部广泛而强大的招募基础设施提供的无药物观察开始
医院因此,我们的第三个目标是量化与以下相关的纵向结构和功能CTSC连接障碍:
治疗反应。总的来说,这项研究将绘制纵向“状态”与“特质”神经标记,从
无药物早期疾病阶段(目标1),将这些变化与症状动力学(目标2)和治疗反应联系起来
(Aim(3)第三章。这种映射是至关重要的,以告知未来的工作,旨在最大限度地个性化的早期干预策略。
项目成果
期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Structural and functional deficits and couplings in the cortico-striato-thalamo-cerebellar circuitry in social anxiety disorder.
- DOI:10.1038/s41398-022-01791-7
- 发表时间:2022-01-21
- 期刊:
- 影响因子:6.8
- 作者:Zhang X;Suo X;Yang X;Lai H;Pan N;He M;Li Q;Kuang W;Wang S;Gong Q
- 通讯作者:Gong Q
Using deep learning to classify pediatric posttraumatic stress disorder at the individual level.
- DOI:10.1186/s12888-021-03503-9
- 发表时间:2021-10-28
- 期刊:
- 影响因子:4.4
- 作者:Yang J;Lei D;Qin K;Pinaya WHL;Suo X;Li W;Li L;Kemp GJ;Gong Q
- 通讯作者:Gong Q
Morphological fingerprinting: Identifying patients with first-episode schizophrenia using auto-encoded morphological patterns.
- DOI:10.1002/hbm.26098
- 发表时间:2023-02-01
- 期刊:
- 影响因子:4.8
- 作者:
- 通讯作者:
Cortical thickness abnormalities in patients with first episode psychosis: a meta-analysis of psychoradiologic studies and replication in an independent sample.
- DOI:10.1093/psyrad/kkab015
- 发表时间:2021-12
- 期刊:
- 影响因子:0
- 作者:Wen K;Zhao Y;Gong Q;Zhu Z;Li Q;Pan N;Fu S;Radua J;Vieta E;Kumar P;Kemp GJ;Biswal BB
- 通讯作者:Biswal BB
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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:
10248465 - 财政年份:2019
- 资助金额:
$ 17.99万 - 项目类别:
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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 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:
$ 17.99万 - 项目类别: