Autism spectrum disorder (ASD) is a heritable condition related to brain development that affects a person’s perception and socialization with others. Here, we examined variability in the brain morphology in ASD children and adolescent individuals at the level of brain cortical structural profiles and the level of each brain regional measure. We selected brain structural MRI data in 600 ASDs and 729 normal controls (NCs) from Autism Brain Imaging Data Exchange (ABIDE). The personalized estimate of similarity between gray matter volume (GMV) profiles of an individual to that of others in the same group was assessed by using the person-based similarity index (PBSI). Regional contributions to PBSI score were utilized for brain age gap estimation (BrainAGE) prediction model establishment, including support vector regression (SVR), relevance vector regression (RVR), and Gaussian process regression (GPR). The association between BrainAGE prediction in ASD and clinical performance was investigated. We further explored the related inter‐regional profiles of gene expression from the Allen Human Brain Atlas with variability differences in the brain morphology between groups. The PBSI score of GMV was negatively related to age regardless of the sample group, and the PBSI score was significantly lower in ASDs than in NCs. The regional contributions to the PBSI score of 126 brain regions in ASDs showed significant differences compared to NCs. RVR model achieved the best performance for predicting brain age. Higher inter-individual brain morphology variability was related to increased brain age, specific to communication symptoms. A total of 430 genes belonging to various pathways were identified as associated with brain cortical morphometric variation. The pathways, including short-term memory, regulation of system process, and regulation of nervous system process, were dominated mainly by gene sets for manno midbrain neurotypes. There is a sample mismatch between the gene expression data and brain imaging data from ABIDE. A larger sample size can contribute to the model training of BrainAGE and the validation of the results. ASD has personalized heterogeneity brain morphology. The brain age gap estimation and transcription-neuroimaging associations derived from this trait are replenished in an additional direction to boost the understanding of the ASD brain.

中文翻译：

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自闭症谱系障碍患者大脑皮层结构变异的个性化估计：大脑年龄和神经生物学相关性的预测因子

自闭症谱系障碍 (ASD) 是一种与大脑发育相关的遗传性疾病，会影响一个人的感知和与他人的社交。在这里，我们在大脑皮层结构剖面和每个大脑区域测量水平上检查了自闭症儿童和青少年个体的大脑形态的变异性。我们从自闭症脑成像数据交换 (ABIDE) 中选择了 600 个 ASD 和 729 个正常对照 (NC) 的脑结构 MRI 数据。通过使用基于人的相似性指数（PBSI）来评估个体的灰质体积（GMV）概况与同一组中其他人的灰质体积（GMV）概况之间的相似性的个性化估计。利用 PBSI 评分的区域贡献来建立大脑年龄差距估计 (BrainAGE) 预测模型，包括支持向量回归 (SVR)、相关向量回归 (RVR) 和高斯过程回归 (GPR)。研究了自闭症谱系障碍 (ASD) 中的 BrainAGE 预测与临床表现之间的关联。我们进一步探索了艾伦人脑图谱中基因表达的相关区域间概况，以及各组之间大脑形态的变异性差异。无论样本组如何，GMV 的 PBSI 评分均与年龄呈负相关，且 ASD 组的 PBSI 评分显着低于 NC 组。自闭症患者 126 个脑区的 PBSI 评分的区域贡献与非正常人相比显示出显着差异。RVR模型在预测大脑年龄方面取得了最佳性能。较高的个体间大脑形态变异性与大脑年龄的增加有关，特别是针对沟通症状。共有 430 个属于不同途径的基因被鉴定为与大脑皮层形态变化相关。这些通路，包括短期记忆、系统过程的调节和神经系统过程的调节，主要由甘露中脑神经类型的基因集主导。ABIDE 的基因表达数据和脑成像数据之间存在样本不匹配。更大的样本量有助于BrainAGE的模型训练和结果的验证。ASD 具有个性化的异质性大脑形态。源自这一特征的大脑年龄差距估计和转录-神经影像关联在另一个方向上得到补充，以促进对自闭症谱系障碍大脑的理解。