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）是一组遗传异质性的常染色体显性遗传性共济失调。其中，包括SCA 6在内的一些突变引起几乎纯小脑综合征，而包括SCA 2和SCA 3在内的其他突变是临床上以各种非小脑症状为特征的多系统疾病。迄今为止，功能成像研究已经报道了小脑和脑干中葡萄糖代谢的降低。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-病理变化往往涉及多个相互连接的脑区，这些脑区可以在空间分布的神经网络的背景下解释。因此，本研究的目的是确定特定的区域脑代谢协方差模式与特定的SCA突变，使用缩放的子轮廓模型和[18 F]氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）。识别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中涉及的神经系统的复杂性，而且还可能识别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.