Shirley Jane, John James Rufus, Montgomery Alicia, Whitehouse Andrew, Eapen Valsamma
School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia.
Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia.
J Autism Dev Disord. 2024 Jun 6. doi: 10.1007/s10803-024-06421-3.
The heterogeneity of autism spectrum disorder (ASD) clinically and aetiologically hinders intervention matching and prediction of outcomes. This study investigated if the behavioural, sensory, and perinatal factor profiles of autistic children could be used to identify distinct subgroups. Participants on the autism spectrum aged 2 to 17 years and their families were sourced via the Australian Autism Biobank (AAB). Latent class analysis was used to identify subgroups within this cohort, utilising twenty-six latent variables representing child's behavioural and sensory features and perinatal factors. Four distinct subgroups within the sample (n = 1168) distinguished by sensory and behavioural autism traits and exposure to perinatal determinants were identified. Class 2 and Class 4, which displayed the greatest behavioural and sensory impairment respectively, were associated with the highest perinatal factor exposure. Class 1, labelled "Most behavioural concerns and moderate sensory and behavioural skills concerns" had mixed exposure to perinatal determinants while Class 3, named "Least sensory and behavioural skills concerns" had the least perinatal determinant exposure, indicating a directly proportional correlation between severity of clinical features and perinatal factor exposure. Additionally, association between specific exposures such as maternal mental illness in Class 1 and significant behavioural concerns was recognised. Identifying distinct subgroups among autistic children can lead to development of targeted interventions and supports. Close monitoring of children exposed to specific perinatal determinants for developmental differences could assist early intervention and supports.
自闭症谱系障碍(ASD)在临床和病因学上的异质性阻碍了干预匹配和结果预测。本研究调查了自闭症儿童的行为、感觉和围产期因素特征是否可用于识别不同的亚组。通过澳大利亚自闭症生物样本库(AAB)招募了年龄在2至17岁的自闭症谱系参与者及其家庭。使用潜在类别分析来识别该队列中的亚组,利用代表儿童行为、感觉特征和围产期因素的26个潜在变量。在样本(n = 1168)中识别出四个不同的亚组,这些亚组由感觉和行为自闭症特征以及围产期决定因素的暴露情况区分。分别表现出最大行为和感觉障碍的第2类和第4类与最高的围产期因素暴露相关。第1类标记为“行为问题最多且感觉和行为技能有中度问题”,其围产期决定因素暴露情况不一,而第3类命名为“感觉和行为技能问题最少”,其围产期决定因素暴露最少,这表明临床特征的严重程度与围产期因素暴露之间存在正比关系。此外,还认识到第1类中特定暴露(如母亲精神疾病)与显著行为问题之间的关联。识别自闭症儿童中的不同亚组可导致制定有针对性的干预措施和支持。密切监测暴露于特定围产期决定因素的儿童的发育差异有助于早期干预和支持。