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Multi-scale functional connectivity in preclinical models of Parkinson's disease

帕金森病临床前模型的多尺度功能连接

基本信息

批准号：
10543831
负责人：
Ashley M Stokes
金额：
$ 39.94万
依托单位：
ST. JOSEPH'S HOSPITAL AND MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10543831
关键词：
Acute Back Basal Ganglia Behavioral Biochemical Biological Markers Blood Vessels Brain Chronic Clinical Clinical Trials Contrast Sensitivity Control Groups Coupled Coupling Detection Development Disease Disease Progression Disease model Dopamine Dorsal Early Diagnosis Etiology Functional Magnetic Resonance Imaging Functional disorder Future Genetic Genetic Techniques Goals Healthcare Imaging Techniques Intervention L-DOPA induced dyskinesia Levodopa Link Magnetic Resonance Imaging Measures Methods Modality Modeling Motor Nature Neurodegenerative Disorders Neurons Neurotransmitters Oxidopamine Parkinson Disease Parkinsonian Disorders Pathologic Patients Perfusion Play Population Pre-Clinical Model Progressive Disease Research Rest Rodent Model Role Sensitivity and Specificity Signal Transduction Structure Techniques Technology Testing Therapeutic Time Translations Validation alpha synuclein base clinical phenotype clinical translation diagnostic value dopaminergic neuron genetic manipulation imaging biomarker imaging modality improved insight locus ceruleus structure magnetic resonance imaging biomarker motor symptom network dysfunction neuronal circuitry neuropathology neurophysiology neurovascular coupling non-motor symptom noradrenergic novel pharmacologic potential biomarker pre-clinical pre-formed fibril preclinical study prognostic value receptor side effect standard care synuclein synucleinopathy translational therapeutics

项目摘要

PROJECT SUMMARY / ABSTRACT: Parkinson’s disease is a progressive neurodegenerative disorder and is associated with significant motor and non-motor symptoms, traceable to the loss of nigral dopamine neurons in addition to widespread circuit dysfunction extending beyond the dying nigrostriatal tract. Imaging-based biomarkers play a critical role in assessing Parkinson’s-related pathological changes, but current biomarkers are limited in their diagnostic and prognostic ability, particularly in early disease stages when intervention would be most beneficial. Functional magnetic resonance imaging (fMRI) enables the study of brain activation and has been widely used to study global functional network changes in Parkinson’s disease. However, standard fMRI is limited in its ability to robustly measure subtle changes with disease, in part due to low sensitivity and specificity; furthermore, interpretation of standard fMRI is challenging due to the indirect link between neuronal function and MRI signal change. This lack of robust direct biomarkers is a critical gap that ultimately limits our ability to understand the underlying pathological changes, as well as evaluate emerging therapies. To overcome these limitations, we propose to leverage an advanced multi-contrast fMRI method that provides high contrast sensitivity, as well as distinct microvascular sensitivity. By coupling this method with pharmacological and chemogenetic manipulations, a direct link between fMRI-based functional networks and underlying neuronal function can be inferred. More specifically, this project aims to a) characterize multi-contrast (total vascular and microvascular) functional connectivity networks in two complementary preclinical models that recapitulate classic hallmarks of Parkinson’s disease - the progressive PFF synucleinopathy model and the acute 6-OHDA model; b) assess the effect of pharmacological dopamine modulation on functional networks, using both acute and chronic treatment paradigms, analogous to the standard treatment paradigm; and c) investigate the effect of endogenous modulation of the dorsal raphe serotonergic circuit and the locus coeruleus noradrenergic circuit – both of which are proposed to be involved in certain non-motor symptomology – on functional networks using chemogenetic methods. These studies will provide insight into functional network changes that occur over different vascular scales and via different neurotransmitter populations. The development of robust MRI biomarkers that relate to dopaminergic, serotonergic, and noradrenergic circuit function and dysfunction may also provide insight into the multifaceted nature of Parkinson’s disease that contributes to both motor and non-motor symptoms. As functional brain network dysfunction is widely observed in Parkinson’s disease, this integrative approach will enable the development of robust biomarkers of Parkinson’s disease with well-characterized pathophysiological origins, which is a critical shortcoming of current technologies.