Personalized estimates of brain cortical structural variability in individuals with Autism spectrum disorder: the predictor of brain age and neurobiology relevance.
Yingying Xie, Jie Sun, Weiqi Man and 2 others
PMID 37507798WHAT IT FOUND
Children and adolescents with autism showed greater variability in brain structure than typical peers, and this variability decreased as they aged.
Those whose brains appeared to mature faster than their actual age had more severe communication difficulties.
Key findings
01Individuals with autism had lower person-based similarity index scores than controls, indicating greater heterogeneity in their brain structural profiles.
02Brain structural similarity scores were negatively correlated with age in both the autism and control groups.
03The subgroup with premature brain development showed significantly higher scores for abnormalities in verbal communication compared to the delayed development group.
STILL TO COME
What they foundWhat it means for SLPs
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What it does not show
The study is cross-sectional, so it describes associations at a single point in time rather than tracking individual brain development over years. Gene expression data came from postmortem adult brains, which creates a significant gap when trying to apply these findings to the living children and adolescents in the MRI dataset. The brain age model was trained on controls and applied to the autism group, which may introduce bias if the structural patterns in autism differ fundamentally from typical development. Site effects (differences in MRI scanners across data collection centers) were addressed with statistical harmonization, but residual biases may remain.
Declared interests
The authors declared no competing interests. The study was funded by various Chinese government and medical foundations, including the National Natural Science Foundation of China.
The easy way to misread this
Do not interpret the 'premature brain development' finding as a causal mechanism for communication difficulties. The study shows a correlation in a cross-sectional dataset; it does not prove that faster brain aging causes worse speech, nor that slowing it would improve language.