Individualized cortical thickness asymmetry in autism spectrum disorder and schizophrenia.

Researchers studied brain structure patterns in people with autism and schizophrenia, specifically looking at whether the left and right sides of the brain differ in thickness. They compared brain scans from 135 people with autism and 287 with schizophrenia to nearly 5,000 typical brains. The study found that brain asymmetry patterns were very similar between autism, schizophrenia, and typical brains, suggesting this measure isn't useful for diagnosing autism.

This large normative modeling study examined cortical thickness asymmetry as a potential biomarker for autism spectrum disorder (ASD) and schizophrenia. Using brain imaging data from 4,904 healthy controls to establish normative ranges, researchers analyzed 135 individuals with ASD and 287 with schizophrenia. The study found minimal evidence of atypical cortical thickness asymmetry patterns in either condition. While schizophrenia participants showed slightly more regions with significant deviations compared to controls, these differences had poor diagnostic accuracy (60% area under curve) and limited clinical utility.

Results were consistent across different analysis approaches, challenging the proposed use of cortical thickness asymmetry as a reliable biomarker for autism or schizophrenia.

Results challenge the clinical utility of cortical thickness asymmetry as a diagnostic biomarker for autism. Clinicians should not rely on brain asymmetry patterns for autism diagnosis. Findings suggest need to explore alternative neurobiological markers and emphasize continued reliance on behavioral diagnostic criteria.

Study design unclear from abstract. Results may not generalize beyond the specific imaging protocols used. Male predominance in autism and schizophrenia groups could affect generalizability. Cross-sectional design limits understanding of developmental patterns.

Cortical thickness asymmetry has been proposed as a latent biomarker for autism spectrum disorder (ASD) and schizophrenia (SZ). However, the degree of abnormal asymmetry at the individual level in ASD and SZ remains unclear. To investigate this, we employed a normative modeling approach. Normative ranges for the whole brain and regional (160 cortical parcels) cortical thickness asymmetry index (AI) were established using a training set of healthy subjects (n = 4904, 45.15% male, age range: 6-95 years), controlling for age, sex, image quality, and scanner.

We calculated z-scores to quantify individual deviations from the normative median in a test set consisting of healthy controls (HC, n = 526, 40% male), participants with ASD (n = 135, 83% male), and SZ (n = 287, 81% male). Regional deviance was assessed by counting the number of individuals with significant deviations below (infra-normal, z-score ≤ -1.96) or above (supra-normal, z-score ≥ 1.96) the normative median in each parcel. We also evaluated individual deviance by counting the number of regions with significant deviations for each participant. A multivariate approach was employed to determine whether regional deviance could separate the three groups.

There were no differences for deviance of whole brain AI between any of the groups. Distributions of individual deviances overlapped across all 160 regions, with one superior temporal region in which SZ individuals showed a higher proportion of supra-normal AI values compared to HC(HC= 1.14%, SZ = 5.92%, χ = 15.45, P < 0.05, ω = 0.14). The SZ group had a higher average number of regions with significant deviations than HC(infra-normal: z = 4.21, p < 0.01; supra-normal: z = 4.33, p < 0.01) but this group difference had limited predictive diagnostic accuracy at the individual level (Area Under the Curve≅60%). The multivariate analysis showed no association between regional deviance and diagnosis.

Results were consistent when using a different parcellation, alternative asymmetry calculations, analysis restricted to males, and after controlling for handedness and IQ. Normative modelling revealed little to no evidence of atypical individualized cortical thickness asymmetry in ASD and SZ. The results of this study challenge the utility of cortical thickness asymmetry as a biomarker for ASD and SZ.