Fractionating autism based on neuroanatomical normative modeling.
Fractionating autism based on neuroanatomical normative modeling.
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DOI：
10.1038/s41398-020-01057-0
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发表时间：
2020-11-06
影响因子：
6.8
通讯作者：
EU-AIMS LEAP Group
中科院分区：
文献类型：
--
作者：
Zabihi M;Floris DL;Kia SM;Wolfers T;Tillmann J;Arenas AL;Moessnang C;Banaschewski T;Holt R;Baron-Cohen S;Loth E;Charman T;Bourgeron T;Murphy D;Ecker C;Buitelaar JK;Beckmann CF;Marquand A;EU-AIMS LEAP Group
自闭症是一种复杂的神经发育疾病，具有显着的表型、生物学和病因学异质性。识别生物标志物以将自闭症分层为可复制的认知或生物亚型仍然是一个挑战。在这里，我们的目标是引入一种新的方法框架，用于解析一大群自闭症患者的神经解剖学亚型。我们使用了来自 EU-AIMS 多中心欧洲纵向自闭症项目六个地点的 316 名自闭症参与者（88 名女性，平均年龄：17.2±5.7）和 206 名神经发育正常者（79 名女性，平均年龄：17.5±6.1）年龄为 6-31 岁的大型且特征明确的样本的皮质厚度 (CT)。使用 CT 和谱聚类的规范模型得出五种基于生物学的假定亚型。其中三个簇显示相对广泛的 CT 下降，两个簇显示相对较高的 CT。这些亚型彼此之间表现出形态学差异，为自闭症病例对照结果不一致提供了潜在的解释，并且对症状和多基因风险的负载有差异且更强烈，表明异质队列中临床效果的稀释。我们的结果为解析自闭症的异质神经生物学提供了重要的一步。
Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6–31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case–control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.
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通讯作者：
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