Dataset Information

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study.

ABSTRACT: There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta-analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients.

SUBMITTER: Cauda F

PROVIDER: S-EPMC6869166 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study.

Cauda Franco F Costa Tommaso T Palermo Sara S D'Agata Federico F Diano Matteo M Bianco Francesca F Duca Sergio S Keller Roberto R

Human brain mapping 20130726 5

There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups o ...[more]

PMID: 23894001

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Project description:Purpose: This study aimed to identify consistent gray matter volume (GMV) changes in the two subtypes of multiple system atrophy (MSA), including parkinsonism subtype (MSA-P), and cerebellar subtype (MSA-C), by conducting a voxel-wise meta-analysis of whole brain voxel-based morphometry (VBM) studies. Method: VBM studies comparing MSA-P or MSA-C and healthy controls (HCs) were systematically searched in the PubMed, Embase, and Web of Science published from 1974 to 20 October 2020. A quantitative meta-analysis of VBM studies on MSA-P or MSA-C was performed using the effect size-based signed differential mapping (ES-SDM) method separately. A complementary analysis was conducted using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) method, which allows a familywise error rate (FWE) correction for multiple comparisons of the results, for further validation of the results. Results: Ten studies were included in the meta-analysis of MSA-P subtype, comprising 136 MSA-P patients and 211 HCs. Five studies were included in the meta-analysis of MSA-C subtype, comprising 89 MSA-C patients and 134 HCs. Cerebellum atrophy was detected in both MSA-P and MSA-C, whereas basal ganglia atrophy was only detected in MSA-P. Cerebral cortex atrophy was detected in both subtypes, with predominant impairment of the superior temporal gyrus, inferior frontal gyrus, temporal pole, insula, and amygdala in MSA-P and predominant impairment of the superior temporal gyrus, middle temporal gyrus, fusiform gyrus, and lingual gyrus in MSA-C. Most of these results survived the FWE correction in the complementary analysis, except for the bilateral amygdala and the left caudate nucleus in MSA-P, and the right superior temporal gyrus and the right middle temporal gyrus in MSA-C. These findings remained robust in the jackknife sensitivity analysis, and no significant heterogeneity was detected. Conclusion: A different pattern of brain atrophy between MSA-P and MSA-C detected in the current study was in line with clinical manifestations and provided the evidence of the pathophysiology of the two subtypes of MSA.

Dataset Information

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study.

Publications

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study.

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