Centre for Human Psychopharmacology, Faculty of Heath, Arts and Design, Swinburne University of Technology, Melbourne, Victoria, Australia.
Department of Statistics, Data Science and Epidemiology, Faculty of Heath, Arts and Design, Swinburne University of Technology, Melbourne, Victoria, Australia.
Psychiatry Res. 2018 Jul;265:111-117. doi: 10.1016/j.psychres.2018.04.037. Epub 2018 Apr 14.
Autism and schizophrenia spectrum research is typically based on coarse diagnostic classification, which overlooks individual variation within clinical groups. This method limits the identification of underlying cognitive, genetic and neural correlates of specific symptom dimensions. This study, therefore, aimed to identify homogenous subclinical subgroups of specific autistic and schizotypal traits dimensions, that may be utilised to establish more effective diagnostic and treatment practices. Latent profile analysis of subscale scores derived from an autism-schizotypy questionnaire, completed by 1678 subclinical adults aged 18-40 years (1250 females), identified a local optimum of eight population clusters: High, Moderate and Low Psychosocial Difficulties; High, Moderate and Low Autism-Schizotypy; High Psychosis-Proneness; and Moderate Schizotypy. These subgroups represent the convergent and discriminant dimensions of autism and schizotypy in the subclinical population, and highlight the importance of examining subgroups of specific symptom characteristics across these spectra in order to identify the underlying genetic and neural correlates that can be utilised to advance diagnostic and treatment practices.
自闭症和精神分裂症谱系的研究通常基于粗略的诊断分类，这种方法忽略了临床群体内部的个体差异。这种方法限制了对特定症状维度的潜在认知、遗传和神经相关性的识别。因此，本研究旨在确定特定自闭症和精神分裂症特征维度的同质亚临床亚组，这些亚组可能被用于建立更有效的诊断和治疗实践。通过对 1678 名年龄在 18-40 岁的亚临床成年人（1250 名女性）完成的自闭症-精神分裂症问卷的子量表得分进行潜在剖面分析，确定了八个人群聚类的局部最优值：高、中、低心理社会困难；高、中、低自闭症-精神分裂症；高精神病易感性；和中等精神分裂症倾向。这些亚组代表了亚临床人群中自闭症和精神分裂症的收敛和区分维度，并强调了在这些谱系中检查特定症状特征亚组的重要性，以确定可以用于推进诊断和治疗实践的潜在遗传和神经相关性。
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