Abstract

The neurobiology of heterogeneous neurodevelopmental disorders such as Autism Spectrum Disorders (ASD) is still unknown. We hypothesized that differences in subject-level properties of intrinsic brain networks were important features that could predict individual variation in ASD symptom severity. We matched cases and controls from a large multicohort ASD dataset (ABIDE-II) on age, sex, IQ, and image acquisition site. Subjects were matched at the individual level (rather than at group level) to improve homogeneity within matched case–control pairs (ASD: n = 100, mean age = 11.43 years, IQ = 110.58; controls: n = 100, mean age = 11.43 years, IQ = 110.70). Using task-free functional magnetic resonance imaging, we extracted intrinsic functional brain networks using projective non-negative matrix factorization. Intrapair differences in strength in subnetworks related to the salience network (SN) and the occipital-temporal face perception network were robustly associated with individual differences in social impairment severity (T = 2.206, P = 0.0301). Findings were further replicated and validated in an independent validation cohort of monozygotic twins (n = 12; 3 pairs concordant and 3 pairs discordant for ASD). Individual differences in the SN and face-perception network are centrally implicated in the neural mechanisms of social deficits related to ASD.

中文翻译：

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内在脑网络的个体差异预测自闭症谱系障碍的症状严重程度。

摘要

自闭症谱系障碍 (ASD) 等异质性神经发育障碍的神经生物学仍然未知。我们假设内在大脑网络的受试者水平属性的差异是可以预测 ASD 症状严重程度个体差异的重要特征。我们匹配了来自大型多队列 ASD 数据集 (ABIDE-II) 的年龄、性别、智商和图像采集站点的病例和对照。受试者在个体水平（而不是在组水平）进行匹配，以提高匹配病例-对照对内的同质性（ASD：n  = 100，平均年龄 = 11.43 岁，智商 = 110.58；对照组：n = 100，平均年龄 = 11.43 岁，智商 = 110.70）。使用无任务功能磁共振成像，我们使用投影非负矩阵分解提取内在功能性脑网络。与显着网络 (SN) 和枕颞面部感知网络相关的子网络中强度的对内差异与社会障碍严重程度的个体差异密切相关 ( T  = 2.206, P  = 0.0301)。在单卵双胞胎的独立验证队列（n  = 12；3 对一致和 3 对不一致的 ASD）中进一步复制和验证了研究结果。SN 和面部感知网络中的个体差异主要涉及与 ASD 相关的社会缺陷的神经机制。