scholarly journals Dissecting the heterogeneous subcortical brain volume of autism spectrum disorder using community detection

2021 ◽  
Author(s):  
Ting Li ◽  
Martine Hoogman ◽  
Nina Roth Mota ◽  
Jan K. Buitelaar ◽  
Alejandro Arias Vasquez ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Community Detection ◽  
Brain Volume ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Subcortical Brain

scholarly journals Dissecting the heterogeneous subcortical brain volume of Autism spectrum disorder (ASD) using community detection

2020 ◽  
Author(s):  
Ting Li ◽  
Martine Hoogman ◽  
Nina Roth Mota ◽  
Jan K. Buitelaar ◽  
Alejandro Arias Vasquez ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Community Detection ◽  
Autism Spectrum ◽  
Case Control ◽  
Spectrum Disorder ◽  
Effect Sizes ◽  
Male Adolescents ◽  
Adult Men ◽  
Subcortical Brain ◽  
Subcortical Volumes

AbstractStructural brain alterations found in Autism Spectrum Disorder (ASD) have previously been very heterogeneous, with overall limited effect sizes for every region implicated. In this study, we aimed at exploring the existence of subgroups in ASD, based on neuroanatomic profiles; we hypothesized that effect sizes of case/control difference would be increased in defined subgroups. Using the dataset from the ENIGMA-ASD Working Group (n=2661), exploratory factor analysis (EFA) was applied on seven subcortical volumes of individuals with ASD and controls to uncover the underlying organization of subcortical structures. Based on earlier findings in ADHD patients and controls as well as data availability, we focused on three age groups: boys (aged 4-14 years), male adolescents (aged 14-22 years), and adult men (aged >=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 sample, with the factor structure in adult men differing from that in boys and male adolescents. From the patterns in these factors, CD uncovered four distinct communities in boys and three communities in adolescents and adult men, irrespective of ASD diagnostic status. The effect sizes of case/control comparisons appeared more pronounced than in the whole sample in some communities. Based on subcortical volumes, we succeeded in stratifying our participants into more homogeneous subgroups with similar brain structural patterns. The stratification enhanced our ability to observe case/control differences of subcortical brain volumes in ASD, and may help explain some of the heterogeneity of previous findings in ASD.

scholarly journals Regional brain volume differences between males with and without autism spectrum disorder are highly age-dependent

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Hsing-Chang Ni ◽  
Meng-Chuan Lai ◽  
Wen-Yih Isaac Tseng ◽  
Susan Shur-Fen Gau
Keyword(s):  
Autism Spectrum Disorder ◽  
Brain Volume ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Regional Brain ◽  
Age Dependent ◽  
Regional Brain Volume

scholarly journals Total Brain Volume and Corpus Callosum Size in Medication-Naïve Adolescents and Young Adults with Autism Spectrum Disorder

2009 ◽  
Vol 66 (4) ◽  
pp. 316-319 ◽  
Author(s):  
Christine M. Freitag ◽  
Eileen Luders ◽  
Hanneke E. Hulst ◽  
Katherine L. Narr ◽  
Paul M. Thompson ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Young Adults ◽  
Corpus Callosum ◽  
Brain Volume ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Adolescents And Young Adults ◽  
Adults With Autism ◽  
Total Brain Volume ◽  
Total Brain

Corpus Callosum Area and Brain Volume in Autism Spectrum Disorder: Quantitative Analysis of Structural MRI from the ABIDE Database

2015 ◽  
Vol 45 (10) ◽  
pp. 3107-3114 ◽  
Author(s):  
R. Kucharsky Hiess ◽  
R. Alter ◽  
S. Sojoudi ◽  
B. A. Ardekani ◽  
R. Kuzniecky ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Quantitative Analysis ◽  
Corpus Callosum ◽  
Brain Volume ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Spectrum Disorder

scholarly journals Magnitude and heterogeneity of brain structural abnormalities in 22q11.2 deletion syndrome: a meta-analysis

2020 ◽  
Vol 25 (8) ◽  
pp. 1704-1717 ◽  
Author(s):  
Maria Rogdaki ◽  
Maria Gudbrandsen ◽  
Robert A McCutcheon ◽  
Charlotte E Blackmore ◽  
Stefan Brugger ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
Brain Volume ◽  
Meta Analysis ◽  
22Q11.2 Deletion Syndrome ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Deletion Syndrome ◽  
22Q11.2 Deletion ◽  
Structural Abnormalities

AbstractThe 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder associated with a number of volumetric brain abnormalities. The syndrome is also associated with an increased risk for neuropsychiatric disorders including schizophrenia and autism spectrum disorder. An earlier meta-analysis showed reduced grey and white matter volumes in individuals with 22q11.2DS. Since this analysis was conducted, the number of studies has increased markedly, permitting more precise estimates of effects and more regions to be examined. Although 22q11.2DS is clinically heterogeneous, it is not known to what extent this heterogeneity is mirrored in neuroanatomy. The aim of this study was thus to investigate differences in mean brain volume and structural variability within regions, between 22q11.2DS and typically developing controls. We examined studies that reported measures of brain volume using MRI in PubMed, Web of Science, Scopus and PsycINFO from inception to 1 May 2019. Data were extracted from studies in order to calculate effect sizes representing case–control difference in mean volume, and in the variability of volume (as measured using the log variability ratio (lnVR) and coefficient of variation ratio (CVR)). We found significant overall decreases in mean volume in 22q11.2DS compared with control for: total brain (g = −0.96; p < 0.001); total grey matter (g = −0.81, p < 0.001); and total white matter (g = −0.81; p < 0.001). There was also a significant overall reduction of mean volume in 22q11.2DS subjects compared with controls in frontal lobe (g = −0.47; p < 0.001), temporal lobe (g = −0.84; p < 0.001), parietal lobe (g = −0.73; p = 0.053), cerebellum (g = −1.25; p < 0.001) and hippocampus (g = −0.90; p < 0.001). Significantly increased variability in 22q11.2DS individuals compared with controls was found only for the hippocampus (VR, 1.14; p = 0.036; CVR, 1.30; p < 0.001), and lateral ventricles (VR, 1.56; p = 0.004). The results support the notion that structural abnormalities in 22q11.2DS and schizophrenia are convergent, and also to some degree with findings in autism spectrum disorder. Finally, the increased variability seen in the hippocampus in 22q11.2DS may underlie some of the heterogeneity observed in the neuropsychiatric phenotype.

scholarly journals Brain Volume Analysis with T1-MRI Data in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Neda Ghobadi Samian ◽  
Keivan Maghooli ◽  
Fardad Farokhi
Keyword(s):  
Autism Spectrum Disorder ◽  
Early Detection ◽  
Brain Volume ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Brain Areas ◽  
Adults With Autism ◽  
Left Hand ◽  
The Brain

Purpose: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is characterized by impaired social interactions. Early detection can prevent the progression of the disease. So far, much research has been done to better diagnose autism. Investigation of brain structure using Magnetic Resonance Imaging (MRI) provides valuable information on the evolution of the brain of patients with autism.   Materials and Methods: In this study, we equally selected T1-MRI data from 20 control subjects and 20 patients, aged under 13 years (male and female, right hand and left hand). MRI research has shown that the brain of autistic children has grown locally and globally. In this paper, for the brain volumetric evaluation of autistic patients, the MRI data was segmented and then analyzed with a statistical method, which has been investigated more generally, in both the cortical and subcortical areas. Results: We extracted 110 cortical and subcortical brain areas. The statistical analysis show which areas are important in discriminant between ASD and healthy control groups. According to the results of MRI, an increase in overall growth is seen in the subcortical areas of the brain (amygdala and hippocampus) as well as the cerebellum, but in adults with autism, a decrease in brain volume is seen. Conclusion: In this study, we analyze the T1-MRI data of ASD subjects for early detection of Autism disorder. Our results were shown in the 6 brain areas that have P-values under 0.005. These areas are important in the early detestation and treatment of ASD.

scholarly journals Cortical and Subcortical Brain Morphometry Differences Between Patients With Autism Spectrum Disorder and Healthy Individuals Across the Lifespan: Results From the ENIGMA ASD Working Group

2018 ◽  
Vol 175 (4) ◽  
pp. 359-369 ◽  
Author(s):  
Daan van Rooij ◽  
Evdokia Anagnostou ◽  
Celso Arango ◽  
Guillaume Auzias ◽  
Marlene Behrmann ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Working Group ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Healthy Individuals ◽  
Brain Morphometry ◽  
Subcortical Brain
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