A normative modelling approach reveals age-atypical cortical thickness in a subgroup of males with autism spectrum disorder
A normative modelling approach reveals age-atypical cortical thickness in a subgroup of males with autism spectrum disorder
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DOI：
10.1038/s42003-020-01212-9
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发表时间：
2020-09-04
影响因子：
5.9
通讯作者：
Lombardo, Michael V.
中科院分区：
文献类型：
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作者：
Bethlehem, Richard A. I.;Seidlitz, Jakob;Lombardo, Michael V.
了解异质性是自闭症谱系障碍（ASD）精准医学道路上的一个重要目标。我们研究了ASD中的皮质厚度（CT）如何被参数化为相对于典型发育（TD）年龄相关规范的个体化测量指标。在一个大样本（每组n=870）和广泛的年龄范围（5-40岁），我们应用规范化建模，导致ASD中年龄相关CT重复性的个体化全脑地图，并分离出一个具有高度年龄非典型CT的小亚组。标准化CT评分还强调了平均分化，以及与行为学的关联，这与从传统病例对照方法中收集的见解不同。这项工作展示了一种理解ASD异质性的个性化方法，这种方法可能会进一步优先考虑与年龄相关的CT重复性中所代表的皮质病理生理学个体子集的工作。只有一小部分ASD个体实际上相对于年龄规范是高度非典型的。平均病例对照差异较小。Richard Bethlehem等人在一个大型队列中使用规范建模方法确定了一个具有高度年龄非典型皮质厚度的自闭症谱系障碍（ASD）个体亚组。这项工作强调了个体化方法对了解ASD异质性的重要性。
Understanding heterogeneity is an important goal on the path to precision medicine for autism spectrum disorders (ASD). We examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of atypicality relative to typically-developing (TD) age-related norms. Across a large sample (n=870 per group) and wide age range (5-40 years), we applied normative modelling resulting in individualized whole-brain maps of age-related CT atypicality in ASD and isolating a small subgroup with highly age-atypical CT. Age-normed CT scores also highlights on-average differentiation, and associations with behavioural symptomatology that is separate from insights gleaned from traditional case-control approaches. This work showcases an individualized approach for understanding ASD heterogeneity that could potentially further prioritize work on a subset of individuals with cortical pathophysiology represented in age-related CT atypicality. Only a small subset of ASD individuals are actually highly atypical relative to age-norms. driving small on-average case-control differences. Richard Bethlehem et al. identify a subgroup of autism spectrum disorders (ASD) individuals with highly age-atypical cortical thickness using a normative modelling approach across a large cohort. This work highlights the importance of individualized approaches to gain insight into ASD heterogeneity.