Multimodal MRI markers of nigrostriatal pathology in Parkinson's disease

描述（由申请人提供）：帕金森病（PD）的病理特征是基底神经节（BG）黑质（SN）的多巴胺神经元丢失和路易小体的存在。缺乏反映pd相关细胞损失和相关病理/生理过程的体内生物标志物阻碍了发现研究，并限制了评估潜在疾病改善疗法的能力。利用18FDOPA-PET和[123I]b-CIT SPECT进行放射成像，可以评估纹状体多巴胺末梢的活性或密度。然而，这些技术并不能直接反映SN的病理过程，可能无法将PD与其他帕金森综合征区分开来，并且可能受到对症治疗的影响。此外，这两种技术都需要暴露在放射性中，PET需要的设施并不普遍。磁共振成像（MRI）是非侵入性的，易于获取，并且广泛可用，然而其测量方法很难与特定的病理生理机制联系起来。据报道，扩散张量（DTI）和R2*成像可以检测PD患者SN的变化，并有望成为MRI生物标志物。然而，缺乏对其临床意义和生物学/病理学基础的理解。我们的试点数据支持这样的假设，即分数各向异性（FA）和R2*指标反映了黑质纹状体病理的不同方面，可以作为诊断PD和跟踪其进展的生物标志物。我们建议利用PI的R01（2009-2014）的纵向临床人群和现有基础设施来检验上述假设。此外，我们在开发疾病生物标志物方面具有相当的专业知识，特别是与铁（Fe）代谢相关的生物标志物。通过将体内高分辨率DTI和R2* MRI数据与体液中铁相关蛋白谱的评估相结合，我们期望在预测PD进展方面获得显著的见解。此外，我们在死后脑组织病理学和铁相关蛋白分析方面的优势将允许体内临床和脑MRI测量与大脑生化变化的相关性。这将提供铁在PD中作用的机制理解，可能导致新的生物标志物或治疗靶点的发现。基于功率分析试点数据，将实现四个目标：1)建立DTI和R2*在PD检测和进展中的差异作用；2)证实黑质纹状体DTI和R2*可区分PD与帕金森综合征；3)询问体液中的铁相关蛋白作为生物标志物；4)获取MRI生物标志物与死后病理相关数据。该研究的成功将产生PD检测及其进展的有效标记物，这些标记物可以整合到可预见的未来，并有望影响改善疾病的临床试验。临床和MRI数据以及收集并保存在PDBP DMR中的生物样本将为生物标志物领域的研究人员提供探索和理解黑质纹状体途径之外的变化和非fe相关蛋白及其与我们提出的标记物的关系的机会。

DESCRIPTION (provided by applicant): Parkinson's disease (PD) is marked pathologically by dopamine neuronal loss in the substantia nigra (SN) of the basal ganglia (BG) and the presence of Lewy bodies. The lack of in vivo biomarker(s) reflecting PD-related cell loss and associated pathoetiological/physiological processes has hindered discovery research and limited the ability to evaluate potentially disease-modifying therapies. The best available technology, radioimaging using 18FDOPA-PET and [123I]b-CIT SPECT, can assess the activity or density of striatal dopamine terminals. These techniques, however, do not reflect directly the pathological process in the SN, may not distinguish PD from other parkinsonian syndromes, and can be affected by symptomatic therapy. In addition, both techniques require exposure to radioactivity and PET requires facilities not widely available. Magnetic resonance imaging (MRI) is noninvasive, easily accessible, and widely available, yet its measures have been difficult to relate to a specific pathophysiological mechanism. Diffusion tensor (DTI) and R2* imaging have been reported to detect changes in the SN in PD, and offer the promise of being MRI biomarkers. There is, however, a lack of understanding of their clinical implications and biological/pathological underpinnings. Our pilot data support the hypothesis that fractional anisotropy (FA) and R2* measures reflect different aspects of nigrostriatal pathology that can be used as biomarkers for diagnosing PD and following its progression. We propose to leverage the longitudinal clinical population and existing infrastructure of the PI's R01 (2009-2014) to test the above hypothesis. In addition, we have considerable expertise in developing disease biomarkers, particularly related to iron (Fe) metabolism. By melding in vivo high-resolution DTI and R2* MRI data with assessment of Fe-related protein profiles in body fluids, we expect to gain marked insight into predicting PD progression. Moreover, our strengths in postmortem brain histopathology and analysis of Fe-related proteins will permit the correlation of the in vivo clinical and brain MRI measures with biochemical changes in the brain. This will provide a mechanistic understanding of the role of Fe in PD that may lead to the discovery of new biomarkers or therapeutic targets. Based on power analysis pilot data, four aims will be performed: 1) Establish the differential roles of DTI and R2* in PD detection and progression; 2) Demonstrate that nigrostriatal DTI and R2* differentiate PD from parkinsonian syndromes; 3) Interrogate Fe-related proteins in body fluids as biomarkers; 4) Obtain MRI biomarker and postmortem pathological correlation data. The success of the study shall yield valid markers for both detection of PD and its progression that can be integrated into and hopefully impact disease-modifying clinical trials within the foreseeable future. The clinical and MRI data and the biosamples collected and deposited to the DMR of the PDBP shall provide investigators in the biomarker community the opportunity to explore and understand changes outside of nigrostriatal pathways and non Fe-related proteins and their relationship with our proposed markers.