Biostatistics and Health Informatics Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Department of Psychology, University of Bath, Bath, UK.
Mol Autism. 2023 Feb 11;14(1):6. doi: 10.1186/s13229-023-00538-5.
There is emerging evidence that the neuroanatomy of autism forms a spectrum which extends into the general population. However, whilst several studies have identified cortical morphology correlates of autistic traits, it is not established whether morphological differences are present in the subcortical structures of the brain. Additionally, it is not clear to what extent previously reported structural associations may be confounded by co-occurring psychopathology. To address these questions, we utilised neuroimaging data from the Adolescent Brain Cognitive Development Study to assess whether a measure of autistic traits was associated with differences in child subcortical morphology, and if any observed differences persisted after adjustment for child internalising and externalising symptoms.
Our analyses included data from 7005 children aged 9-10 years (female: 47.19%) participating in the Adolescent Brain Cognitive Development Study. Autistic traits were assessed using scores from the Social Responsiveness Scale (SRS). Volumes of subcortical regions of interest were derived from structural magnetic resonance imaging data.
Overall, we did not find strong evidence for an association of autistic traits with differences in subcortical morphology in this sample of school-aged children. Whilst lower absolute volumes of the nucleus accumbens and putamen were associated with higher scores of autistic traits, these differences did not persist once a global measure of brain size was accounted for.
It is important to note that autistic traits were assessed using the SRS, of which higher scores are associated with general behavioural problems, and therefore may not be wholly indicative of autism-specific symptoms. In addition, individuals with a moderate or severe autism diagnosis were excluded from the ABCD study, and thus, the average level of autistic traits will be lower than in the general population which may bias findings towards the null.
These findings from our well-powered study suggest that other metrics of brain morphology, such as cortical morphology or shape-based phenotypes, may be stronger candidates to prioritise when attempting to identify robust neuromarkers of autistic traits.
越来越多的证据表明，自闭症的神经解剖结构呈连续谱分布，延伸至普通人群。然而，尽管有几项研究已经确定了自闭症特征与皮质形态学的相关性，但尚未确定大脑皮质下结构是否存在形态差异。此外，目前尚不清楚以前报告的结构关联在多大程度上可能受到并发精神病理学的影响。为了解决这些问题，我们利用青少年大脑认知发展研究的神经影像学数据来评估自闭症特征的测量值是否与儿童皮质下形态的差异相关，以及在调整儿童内化和外化症状后，任何观察到的差异是否仍然存在。
我们的分析包括来自青少年大脑认知发展研究的 7005 名 9-10 岁儿童（女性：47.19%）的数据。自闭症特征使用社交反应量表（SRS）的得分进行评估。皮质下感兴趣区的体积从结构磁共振成像数据中得出。
总的来说，我们在这个学龄儿童样本中没有发现自闭症特征与皮质下形态差异之间存在很强关联的有力证据。虽然核壳和纹状体的绝对体积较小与自闭症特征得分较高有关，但在考虑大脑总体积的全球指标后，这些差异就不再存在了。
重要的是要注意，自闭症特征是使用 SRS 进行评估的，而 SRS 得分较高与一般行为问题有关，因此可能不完全代表自闭症特异性症状。此外，中度或重度自闭症诊断的个体被排除在 ABCD 研究之外，因此，平均自闭症特征水平将低于普通人群，这可能会使研究结果偏向于零假设。
我们这项具有较大效力的研究结果表明，其他脑形态学指标，如皮质形态学或基于形状的表型，可能是更适合优先考虑的候选指标，以尝试确定自闭症特征的稳健神经标志物。
