Neuroimaging signatures of frontotemporal dementia genetics: C9ORF72, tau, progranulin and sporadics.
Neuroimaging signatures of frontotemporal dementia genetics: C9ORF72, tau, progranulin and sporadics.
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DOI：
10.1093/brain/aws001
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发表时间：
2012-03
期刊：
影响因子：
--
通讯作者：
Josephs KA
中科院分区：
文献类型：
--
作者：
Whitwell JL;Weigand SD;Boeve BF;Senjem ML;Gunter JL;DeJesus-Hernandez M;Rutherford NJ;Baker M;Knopman DS;Wszolek ZK;Parisi JE;Dickson DW;Petersen RC;Rademakers R;Jack CR Jr;Josephs KA
最近的一项重大发现是在额颞痴呆和肌萎缩侧索硬化症患者中发现了C9ORF72基因中非编码GGGGCC六核苷酸重复序列的扩展。已知另外两个基因的突变可以解释家族性额颞叶痴呆：微管相关蛋白tau和原颗粒蛋白。尽管之前已经报道了tau和原颗粒蛋白突变的受试者的成像特征，但C9ORF72中还没有发表过成像特征。此外，目前尚不清楚这些突变之间的萎缩模式是否存在差异，以及区域差异是否有助于在单一受试者水平上将C9ORF72与其他两个突变区分开来。我们的目的是确定与C9ORF72基因突变相关的脑萎缩的区域模式，并确定哪些区域最能区分C9ORF72与tau和原颗粒突变的受试者，以及与散发性额颞叶痴呆。本研究共纳入76例行为变异型额颞叶痴呆患者，其中56例临床诊断为行为变异型额颞叶痴呆患者，其中19例为C9ORF72突变，25例为tau突变，12例为前颗粒蛋白突变；20例散发性行为变异型额颞叶痴呆患者(其中50%为肌萎缩侧索硬化症)。基于体素的形态计量学被用来评估和比较灰质萎缩的模式。使用自动解剖标记图谱和统计参数绘图软件进行基于Atlas的分割，以计算37个感兴趣区域的体积。计算大脑半球的不对称性。使用惩罚多项Logistic回归建立预测模型，利用区域体积和不对称性评分来区分不同组。主成分分析对组内差异进行评估。C9ORF72伴有对称性萎缩，主要累及背外侧、内侧和眶前叶，并伴有前颞叶、顶叶、枕叶和小脑的缺失。相反，显著的前内侧颞叶萎缩与tau突变相关，而颞顶萎缩与前颗粒基因突变相关。散发性组伴有额叶和前额叶萎缩。保守的惩罚性多项Logistic回归模型确定了14个变量，可以准确地对受试者进行分类，包括额部、颞部、顶部、枕部和小脑的体积。主成分分析显示，所有疾病组内的异质性程度相似。因此，在C9ORF72、tau和前颗粒蛋白突变以及散发性额颞叶痴呆的受试者中，萎缩模式是不同的。我们的分析表明，成像有可能有助于在单一受试者水平上将C9ORF72与其他组区分开来。
A major recent discovery was the identification of an expansion of a non-coding GGGGCC hexanucleotide repeat in the C9ORF72 gene in patients with frontotemporal dementia and amyotrophic lateral sclerosis. Mutations in two other genes are known to account for familial frontotemporal dementia: microtubule-associated protein tau and progranulin. Although imaging features have been previously reported in subjects with mutations in tau and progranulin, no imaging features have been published in C9ORF72. Furthermore, it remains unknown whether there are differences in atrophy patterns across these mutations, and whether regional differences could help differentiate C9ORF72 from the other two mutations at the single-subject level. We aimed to determine the regional pattern of brain atrophy associated with the C9ORF72 gene mutation, and to determine which regions best differentiate C9ORF72 from subjects with mutations in tau and progranulin, and from sporadic frontotemporal dementia. A total of 76 subjects, including 56 with a clinical diagnosis of behavioural variant frontotemporal dementia and a mutation in one of these genes (19 with C9ORF72 mutations, 25 with tau mutations and 12 with progranulin mutations) and 20 sporadic subjects with behavioural variant frontotemporal dementia (including 50% with amyotrophic lateral sclerosis), with magnetic resonance imaging were included in this study. Voxel-based morphometry was used to assess and compare patterns of grey matter atrophy. Atlas-based parcellation was performed utilizing the automated anatomical labelling atlas and Statistical Parametric Mapping software to compute volumes of 37 regions of interest. Hemispheric asymmetry was calculated. Penalized multinomial logistic regression was utilized to create a prediction model to discriminate among groups using regional volumes and asymmetry score. Principal component analysis assessed for variance within groups. C9ORF72 was associated with symmetric atrophy predominantly involving dorsolateral, medial and orbitofrontal lobes, with additional loss in anterior temporal lobes, parietal lobes, occipital lobes and cerebellum. In contrast, striking anteromedial temporal atrophy was associated with tau mutations and temporoparietal atrophy was associated with progranulin mutations. The sporadic group was associated with frontal and anterior temporal atrophy. A conservative penalized multinomial logistic regression model identified 14 variables that could accurately classify subjects, including frontal, temporal, parietal, occipital and cerebellum volume. The principal component analysis revealed similar degrees of heterogeneity within all disease groups. Patterns of atrophy therefore differed across subjects with C9ORF72, tau and progranulin mutations and sporadic frontotemporal dementia. Our analysis suggested that imaging has the potential to be useful to help differentiate C9ORF72 from these other groups at the single-subject level.
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