Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder. Issue 7 (23rd May 2019) - Yamagata, Bun
Abstract : Aim: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. Methods: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface‐based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. Results: A sparse logistic regression with a leave‐one‐pair‐out cross‐validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. Conclusion: This proof‐of‐concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.