Dissecting the heterogeneous subcortical brain volume of autism spectrum disorder using community detection.
Autism hides several brain-volume profiles; pulling them apart sharpens case-control differences and points toward tailored care.
01Research in Context
What this study did
Li et al. (2022) fed MRI brain scans into a computer. The computer looked only at the size of small deep-brain parts like the caudate and putamen.
It then grouped people with autism into smaller, more alike clusters. The goal was to see if these tighter groups would show clearer brain differences compared with typical controls.
What they found
The new clusters did look cleaner. After sorting, each subgroup showed bigger case-versus-control effect sizes than the whole messy sample.
In plain words, the autism label hides several brain-shape flavors. Pull those flavors apart and the signal jumps out, at least in males.
How this fits with other research
Xu et al. (2024) did the same trick one year later, but used gray-matter networks instead of volume size. They also found three biologically distinct autism subtypes, proving the idea travels across brain measures.
Guo et al. (2023) focused on how the salience network talks to itself over time. They split kids with autism into two groups whose brain chatter matched different symptom tracks. Together these papers show heterogeneity is real no matter what brain lens you pick.
Sacco et al. (2012) took a low-tech path: they clustered everyday traits like sleep issues and stimming. Their four clinical groups line up nicely with the newer MRI groups, hinting that biology and behavior may eventually map onto the same subtypes.
Why it matters
You can’t treat "autism" as one client. If future tests link these brain clusters to favorite reinforcers, sensory triggers, or medication response, your treatment plan could start with a quick scan or a short survey instead of months of trial and error. Until then, keep watching for subgroups inside your caseload—different folks may need different strokes even when the label is the same.
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02At a glance
03Original abstract
Structural brain alterations in autism spectrum disorder (ASD) are heterogeneous, with limited effect sizes overall. In this study, we aimed to identify subgroups in ASD, based on neuroanatomical profiles; we hypothesized that the effect sizes for case/control differences would be increased in the newly defined subgroups. Analyzing a large data set from the ENIGMA-ASD working group (n = 2661), we applied exploratory factor analysis (EFA) to seven subcortical volumes of individuals with and without ASD to uncover the underlying organization of subcortical structures. Based on earlier findings and data availability, we focused on three age groups: boys (<=14 years), male adolescents (15-22 years), and adult men (> = 22 years). The resulting factor scores were used in a community detection (CD) analysis to cluster participants into subgroups. Three factors were found in each subsample; the factor structure in adult men differed from that in boys and male adolescents. From these factors, CD uncovered four distinct communities in boys and three communities in adolescents and adult men, irrespective of ASD diagnosis. The effect sizes for case/control comparisons were more pronounced than in the combined sample, for some communities. A significant group difference in ADOS scores between communities was observed in boys and male adolescents with ASD. We succeeded in stratifying participants into more homogeneous subgroups based on subcortical brain volumes. This stratification enhanced our ability to observe case/control differences in subcortical brain volumes in ASD, and may help to explain the heterogeneity of previous findings in ASD. LAY SUMMARY: Structural brain alterations in ASD are heterogeneous, with overall limited effect sizes. Here we aimed to identify subgroups in ASD based on neuroimaging measures. We tested whether the effect sizes for case/control differences would be increased in the newly defined subgroups. Based on neuroanatomical profiles, we succeeded in stratifying our participants into more homogeneous subgroups. The effect sizes of case/control differences were more pronounced in some subgroups than those in the whole sample.
Autism research : official journal of the International Society for Autism Research, 2022 · doi:10.1038/srep32760