Department of Neuroradiology, University of Utah, 1A71 School of Medicine, Salt Lake City, UT 84132, USA.
Brain. 2011 Dec;134(Pt 12):3742-54. doi: 10.1093/brain/awr263. Epub 2011 Oct 17.
Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.
自闭症个体与典型发育对照者在静息状态功能磁共振成像连接方面的群体差异已广泛复制出少数离散脑区,但自闭症的全脑连接异常分布情况尚不清楚。也不清楚功能连接是否足够稳健,可以作为自闭症个体患者的诊断或预后指标。我们从一组特征明确的 40 名男性青少年和成年自闭症患者和 40 名年龄、性别和智商匹配的典型发育对照者的整个灰质中获得了 7266 个感兴趣区的成对功能连接测量值(2640 万个连接)。在每个被试中,使用 8 分钟的静息状态血氧水平依赖扫描进行分类。在 40 名被试中,使用留一法分类器成功区分了自闭症和对照组,敏感性为 83%,特异性为 75%,总准确率为 79%(P = 1.1×10(-7))。在年龄<20 岁的被试中,分类器的准确率为 89%(P = 5.4×10(-7))。在由六个家庭的 21 名自闭症患者和未受影响的同胞组成的复制数据集中,分类器的准确率为 71%(年龄<20 岁的被试准确率为 91%)。自闭症患者的分类评分与社会反应量表(P = 0.05)、言语智商(P = 0.02)和自闭症诊断观察量表-通用版的综合社会和交流分量表(P = 0.05)显著相关。信息连接分析表明,相关性最强的感兴趣区对在自闭症中最异常。负相关的感兴趣区对在自闭症中相关性更高(相关性降低),可能代表较弱的抑制连接,尤其是长连接(欧几里得距离>10cm)。显示最大差异的脑区包括默认模式网络、顶叶上回、梭状回和前岛叶的脑区。总体而言,年轻被试的分类准确率更好,自闭症和对照组之间的差异在 19 岁后逐渐缩小。自闭症患者未受影响的同胞的分类评分与对照组更相似,而与自闭症患者的分类评分不相似。这些发现表明自闭症的功能连接磁共振成像诊断检测具有可行性。
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