by Science China Press

Functional gradient and network efficiency in individuals with early-onset schizophrenia (EOS), autism spectrum disorder (ASD), and normal controls (NCs). (A) Functional gradient maps of individuals with EOS, ASD, and NCs. The color of the nodes represents the functional network to which they belong. Gradient 1 indicates the primary-transmodal gradient axis, and Gradient 2 indicates the visual-sensorimotor gradient axis. (B) Pairwise group differences in the range of the two gradients. (C) Pairwise group differences in the positioning of brain nodes within the functional gradient coordinate system. Nodes without significant gradient differences are colored in gray, while those with significant gradient differences are colored according to the networks they are associated with. The direction of gradient changes in these nodes is indicated by black arrow lines. In addition, nodes that exhibit a decrease in efficiency are marked with blue circles. (D) The interrelationship of inclusivity between nodes exhibiting gradient abnormalities or efficiency abnormalities. (E) Spatial overlap of the nodes with abnormal gradient or efficiency. (F) Global network efficiency of individuals with EOS, ASD, and NCs. Global efficiency and local efficiency across a range of network sparsities (0.01–0.35) were presented, and the areas under the curve were compared among individuals with EOS, ASD, and NCs. *indicates corrected P <0.05. The light gray symbols indicate uncorrected significance. ANCOVA: analysis of covariance; ASD: autism spectrum disorder; AUC: area under the curve; DAN: dorsal attention network; DMN: default mode network; EOS: early-onset schizophrenia; FPN: frontoparietal network; IPS: intra-parietal sulcus; L: left; LN: limbic network; NC: normal control; R: right; SMN: sensorimotor network; SUB: subcortical nucleus; VAN: ventral attention network; VN: visual network. Credit: Science China Press

Schizophrenia (SCZ) and autism spectrum disorder (ASD) are two mental disorders with abnormal neurodevelopment that carry a high burden for families and society. The two disorders exhibit similar clinical symptoms in social interaction, emotional reciprocity, and cognitive deficits.

Therefore, using non-invasive and radiation-free functional MRI (fMRI) to examine the brain structure and functional abnormalities in children with early-onset schizophrenia (EOS) and ASD is of great significance for exploring the brain mechanisms of the diseases and the early diagnosis based on objective biomarkers.

A recent study published in the journal Medicine Plus and based on standardized functional magnetic resonance imaging (fMRI) data from 594 children at five sites, including children with EOS, children with ASD, and normal control, has depicted the neuroanatomic and functional connectomic profiles of EOS and ASD based on brain imaging.

The work has revealed similar yet distinct structural/functional brain abnormalities between the two disorders. From the perspective of similarities, both EOS and ASD exhibit significant reductions in cortical thickness and functional connectivity in the parietal and temporal lobes.

However, in terms of differences, EOS shows a greater reduction in cortical thickness than ASD and uniquely exhibits declines in several subcortical structures, such as the left thalamus, bilateral hippocampus, and amygdala. Conversely, ASD exhibits connectomic abnormalities that differ from EOS, which is manifested in a metric that characterizes the functional differentiation and hierarchical organization of different brain regions, known as the functional gradient.

ASD shows an overall decline in gradient range and a widespread trend of gradient compression across network nodes. This compression trend is spatially associated with a decline in brain network efficiency. Additionally, only ASD (not EOS) exhibits a decrease in functional connectivity at the level of large-scale networks.

In general, EOS exhibits more severe anatomical abnormalities, whereas ASD shows a more subtle trend in abnormalities concerning certain connectomic properties. The classification models utilizing neuroanatomic and connectomic profiles as features attained accuracy rates exceeding 80% and demonstrated adequate performance in rigorous cross-site validation, offering the potential for MRI to facilitate early diagnosis and intervention in mental disorders with abnormal neurodevelopment.

The researchers were led by Prof. Chao-Gan Yan from the Institute of Psychology, Chinese Academy of Sciences, Prof. Jing Liu from the Peking University Sixth Hospital, Prof. Xue-Rong Liu from the Second Xiangya Hospital of Central South University, and Prof. Ya-Song Du from the Shanghai Mental Health Center.

More information: Bin Lu et al, Same same but different: Neuroanatomic and connectomic profiles of early-onset schizophrenia and autism spectrum disorder, Medicine Plus (2024). DOI: 10.1016/j.medp.2024.100007

Provided by Science China Press