Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder.

Patricia Segura, Marco Pagani, Somer L Bishop, Phoebe Thomson, Stanley Colcombe, Ting Xu, Zekiel Z Factor, Emily C Hector, So Hyun Kim, Michael V Lombardo, Alessandro Gozzi, Xavier F Castellanos, Catherine Lord, Michael P Milham, Adriana Di Martino
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Abstract

Clinical, neuroimaging and genomics evidence have increasingly underscored a degree of overlap between autism and attention-deficit/hyperactivity disorder (ADHD). This study explores the specific contribution of their core symptoms to shared biology in a sample of N=166 verbal children (6-12 years) with rigorously-established primary diagnoses of either autism or ADHD (without autism). We investigated the associations between inter-individual differences in clinician-based dimensional measures of autism and ADHD symptoms and whole-brain low motion intrinsic functional connectivity (iFC). Additionally, we explored their linked gene expression patterns in silico. Whole-brain multivariate distance matrix regression revealed a transdiagnostic association between autism severity and iFC of two nodes: the middle frontal gyrus of the frontoparietal network and posterior cingulate cortex of the default mode network. Across children, the greater the iFC between these nodes, the more severe the autism symptoms, even after controlling for ADHD symptoms. Results from segregation analyses were consistent with primary findings, underscoring the significance of internetwork iFC interactions for autism symptom severity across diagnoses. No statistically significant brain-behavior relationships were observed for ADHD symptoms. Genetic enrichment analyses of the iFC maps associated with autism symptoms implicated genes known to: (i) have greater rate of variance in autism and ADHD, and (ii) be involved in neuron projection, suggesting shared genetic mechanisms for this specific brain-clinical phenotype. Overall, these findings underscore the relevance of transdiagnostic dimensional approaches in linking clinically-defined phenomena to shared presentations at the macroscale circuit- and genomic-levels among children with diagnoses of autism and ADHD.

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自闭症和/或注意力缺陷/多动障碍儿童的基于连接体的症状定位和计算机相关基因表达
临床、神经影像学和基因组学证据越来越强调自闭症和注意力缺陷/多动障碍(ADHD)之间存在一定程度的重叠。本研究以N=166名语言儿童(6-12岁)为样本,探讨了他们的核心症状对共同生物学的具体贡献,这些儿童被严格确定为自闭症或ADHD(无自闭症)的初步诊断。我们研究了基于临床的自闭症和ADHD症状维度测量的个体差异与全脑低运动内在功能连接(iFC)之间的关联。此外,我们探索了它们在硅中的相关基因表达模式。全脑多元距离矩阵回归显示自闭症严重程度与前额顶叶网络中额回和默认模式网络后扣带回两个节点的iFC存在跨诊断相关性。在儿童中,这些节点之间的iFC越大,自闭症症状就越严重,即使在控制了ADHD症状之后也是如此。分离分析的结果与初步发现一致,强调了网络间iFC相互作用对自闭症症状严重程度的重要性。未观察到ADHD症状与脑行为之间有统计学意义的关系。对与自闭症症状相关的iFC图谱进行的遗传富集分析涉及以下已知基因:(i)在自闭症和多动症中具有更高的变异率,(ii)参与神经元投射,表明这种特定的脑临床表型具有共同的遗传机制。总的来说,这些发现强调了跨诊断维度方法的相关性,将临床定义的现象与诊断为自闭症和ADHD的儿童在宏观电路和基因组水平上的共同表现联系起来。
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