Identification of regional cerebral metabolic covariance patterns specifically associated with the dominant ataxias SCA2, -3 and -6 using FDG-PET uptake measures

脊髓小脑共济失调（SCA）是一种遗传异质性的常染色体显性遗传性共济失调。其中，包括SCA6在内的一些突变引起几乎纯粹的小脑综合征，而包括SCA2和-3在内的其他突变则是多系统疾病，临床上以各种非小脑症状为特征。到目前为止，功能成像研究已经报道了小脑和脑干的葡萄糖代谢降低。然而，缺乏关于假定的特定区域代谢模式的信息。不同脑区的功能病理改变往往涉及多个相互关联的脑区，这可以在空间分布的神经网络的背景下解释。因此，本研究旨在使用缩放亚剖面模型和[18F]氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）确定与特定SCA突变相关的特定区域脑代谢协方差模式。确定特定的代谢模式不仅有助于理解遗传定义的神经退行性疾病所涉及的神经系统的复杂性，而且还可能确定对症治疗的假定靶点。

The spinocerebellar ataxias (SCA) are a genetically heterogeneous group of autosomal dominantly inherited ataxias. Among these, some mutations including SCA6 give rise to an almost pure cerebellar syndrome while others including SCA2 and -3 are multisystemic disorders characterized clinically by a variety of non-cerebellar symptoms. Functional imaging studies so far have reported decreased glucose metabolism in the cerebellum and brainstem. However, information on putative specific regional metabolic patterns is lacking. Functional-pathologic changes in distinct brain areas are apt to involve multiple interconnected brain regions which may be interpreted in the context of spatially distributed neural networks. The present study therefore aims to identify specific regional cerebral metabolic covariance patterns associated with a given SCA mutation using a scaled subprofile model and [18F]fluorodeoxyglucose positron emission tomography (FDG-PET). The identification of a specific metabolic pattern will not only help to understand the complexity of neural systems involved in genetically defined neurodegenerative disorders but might also identify putative targets for symptomatic therapy.