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Cortical signatures in behaviorally clustered autistic traits subgroups: a population-based study.
Translational Psychiatry ( IF 5.8 ) Pub Date : 2020-06-27 , DOI: 10.1038/s41398-020-00894-3
Angeline Mihailov 1 , Cathy Philippe 1 , Arnaud Gloaguen 1, 2 , Antoine Grigis 1 , Charles Laidi 1, 3 , Camille Piguet 1, 4 , Josselin Houenou 1, 3 , Vincent Frouin 1
Affiliation  

Extensive heterogeneity in autism spectrum disorder (ASD) has hindered the characterization of consistent biomarkers, which has led to widespread negative results. Isolating homogenized subtypes could provide insight into underlying biological mechanisms and an overall better understanding of ASD. A total of 1093 participants from the population-based “Healthy Brain Network” cohort (Child Mind Institute in the New York City area, USA) were selected based on score availability in behaviors relevant to ASD, aged 6–18 and IQ >= 70. All participants underwent an unsupervised clustering analysis on behavioral dimensions to reveal subgroups with ASD traits, identified by the presence of social deficits. Analysis revealed three socially impaired ASD traits subgroups: (1) high in emotionally dysfunctional traits, (2) high in ADHD-like traits, and (3) high in anxiety and depressive symptoms. 527 subjects had good quality structural MRI T1 data. Site effects on cortical features were adjusted using the ComBat method. Neuroimaging analyses compared cortical thickness, gyrification, and surface area, and were controlled for age, gender, and IQ, and corrected for multiple comparisons. Structural neuroimaging analyses contrasting one combined heterogeneous ASD traits group against controls did not yield any significant differences. Unique cortical signatures, however, were observed within each of the three individual ASD traits subgroups versus controls. These observations provide evidence of ASD traits subtypes, and confirm the necessity of applying dimensional approaches to extract meaningful differences, thus reducing heterogeneity and paving the way to better understanding ASD traits.



中文翻译:

行为聚类自闭症特征亚组的皮层特征:一项基于人群的研究。

自闭症谱系障碍 (ASD) 的广泛异质性阻碍了一致生物标志物的表征,这导致了广泛的负面结果。分离同质化的亚型可以深入了解潜在的生物学机制并更好地理解 ASD。根据与 ASD 相关的行为得分可用性,从基于人群的“健康大脑网络”队列(美国纽约市地区的儿童心理研究所)中选择了 1093 名参与者,年龄在 6-18 岁,智商 >= 70 . 所有参与者都对行为维度进行了无监督聚类分析,以揭示具有 ASD 特征的亚组,这些特征由社会缺陷的存在确定。分析揭示了三个社交受损的 ASD 特征亚组:(1)情绪功能障碍特征高,(2)ADHD 样特征高,(3) 高度焦虑和抑郁症状。527 名受试者具有高质量的结构 MRI T1 数据。使用 ComBat 方法调整对皮质特征的站点影响。神经影像学分析比较了皮质厚度、脑回和表面积,并控制了年龄、性别和智商,并进行了多重比较校正。将一个组合的异质 ASD 性状组与对照组进行对比的结构神经影像分析没有产生任何显着差异。然而,在三个单独的 ASD 特征亚组与对照组的每一个中都观察到了独特的皮质特征。这些观察结果提供了 ASD 特征亚型的证据,并证实了应用维度方法来提取有意义差异的必要性,从而减少异质性并为更好地理解 ASD 特征铺平道路。

更新日期:2020-06-27
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