Abnormal imaging neuroanatomy in childhood autism spectrum disorder and schizophrenia
Poster No:
412
Submission Type:
Abstract Submission
Authors:
Bin Lu1, Chaogan Yan2
Institutions:
1Institute of Psychology, Beijing, Beijing, 2Chinese Academy of Sciences, Beijing, China
First Author:
Co-Author:
Introduction:
Autism spectrum disorder (ASD) and schizophrenia (SCZ) are neurodevelopmental disorders with high morbidity. They share some genetic risks, clinical symptoms and neuroanatomical architectures but also show divergence in these aspects. In the current study, we aim to disclose the consistent and inconsistent atypical imaging-based neuroanatomy of pediatric and adolescent ASD and SCZ patients.
The former morphological studies on SCZ consistently reported comprehensively decreased cortical grey matter. For ASD, a study based on large-scale data exchange project - ABIDE - announced lower cortical thickness in a wide-range age group of ASD participants (Haar et al., 2016), but the conflicted results are also frequently reported (see (Baribeau and Anagnostou, 2013) for review). In addition to structural neuroanatomy, resting-state fMRI can illustrate the in vivo functional organization of the brain using connection-based methods including connectome, functional gradient (Margulies et al., 2016), and graph-theoretical indices (Bullmore and Sporns, 2009), which are collectively termed as connectomic anatomy. However, a direct comparison of imaging-based neuroanatomy between pediatric ASD and SCZ was lacking.
The former morphological studies on SCZ consistently reported comprehensively decreased cortical grey matter. For ASD, a study based on large-scale data exchange project - ABIDE - announced lower cortical thickness in a wide-range age group of ASD participants (Haar et al., 2016), but the conflicted results are also frequently reported (see (Baribeau and Anagnostou, 2013) for review). In addition to structural neuroanatomy, resting-state fMRI can illustrate the in vivo functional organization of the brain using connection-based methods including connectome, functional gradient (Margulies et al., 2016), and graph-theoretical indices (Bullmore and Sporns, 2009), which are collectively termed as connectomic anatomy. However, a direct comparison of imaging-based neuroanatomy between pediatric ASD and SCZ was lacking.
Methods:
For our multi-center dataset, 229 high-functioning autism individuals, 186 schizophrenia individuals in acute phase under 18 years old, meeting DSM-IV criteria and 128 typical development participants were enrolled through the outpatient clinic and accepted T1-weighted and R-fMRI scans at 5 scanning sites. The procedure was approved by the Ethics Committee of Peking University Sixth Hospital. The MR images were preprocessed and quality controlled using DPABISurf (Yan et al., 2021). After that, surface-based metrics including cortical thickness, subcortical volume, connectome, functional gradient and graph-theoretical indices to depict the abnormal structural and connectomic neuroanatomy of ASD and SCZ.
Results:
In general, noteworthy differences exist in the direction and extent of the abnormal structural and connectomic neuroanatomy in ASD and SCZ. For structural neuroanatomy, both ASD and SCZ showed decreased cortical thickness and subcortical volume. However, compared to ASD, SCZ has a thinner bilateral intra-parietal sulcus, right temporo-parieto-occipital junction, and smaller hippocampal volume. For connectomic neuroanatomy, only ASD exhibits a decrease at the network-level in connectome and efficiency, which SCZ does not. Importantly, the decrease in brain network efficiency in ASD may be related to its gradient compression (e.g. decreased gradient range). Almost all (92.3%) brain regions with decreased nodal efficiency show a decline in the primary-to-transmodal gradient or the sensorimotor-to-visual gradient, and all (100%) nodes that decline on both gradients show a significant decrease in efficiency.
·Figure 1. The brain areas showing significant difference in cortical thickness, subcortical volume and anatomical-seed-based functional connection among ASD, SCZ and HC individuals.
·Figure 2. The abnormal functional gradient and network efficiency among ASD, SCZ and HC individuals.
Conclusions:
In sum, SCZ has greater structural variations, while ASD has more pronounced functional abnormalities. The structural and connectomic neuroanatomical profile of ASD and SCZ showed both shared and distinct brain characteristics.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Keywords:
Autism
Psychiatric Disorders
Schizophrenia
Other - Gradient
1|2Indicates the priority used for review
Provide references using author date format
Bullmore, E., Sporns, O., 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10, 186–198. https://doi.org/10.1038/nrn2575
Haar, S., Berman, S., Behrmann, M., Dinstein, I., 2016. Anatomical Abnormalities in Autism? Cereb. Cortex 26, 1440–1452. https://doi.org/10.1093/cercor/bhu242
Margulies, D.S., Ghosh, S.S., Goulas, A., Falkiewicz, M., Huntenburg, J.M., Langs, G., Bezgin, G., Eickhoff, S.B., Castellanos, F.X., Petrides, M., Jefferies, E., Smallwood, J., 2016. Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc. Natl. Acad. Sci. U.S.A. 113, 12574–12579. https://doi.org/10.1073/pnas.1608282113
Yan, C.-G., Wang, X.-D., Lu, B., 2021. DPABISurf: data processing & analysis for brain imaging on surface. Science Bulletin 66, 2453–2455. https://doi.org/10.1016/j.scib.2021.09.016