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

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          Abstract

          Background

          Neuroanatomical differences between individuals with and without autism spectrum disorder (ASD) were inconsistent in the literature. Such heterogeneity may substantially originate from age-differential effects.

          Methods

          Voxel-based morphometry was applied in 86 males with ASD and 90 typically developing control (TDC) males (aged 7 to 29 years). Three steps of statistical modeling (model 1, multiple regression with age as a covariate; model 2, multiple regression further considering diagnosis-by-age interaction; model 3, age-stratified analyses) were performed to dissect the moderating effects of age on diagnostic group differences in neuroanatomy.

          Results

          Across ages, males with and without ASD did not differ significantly in total gray matter (GM) or white matter (WM) volumes. For both groups, total GM volumes decreased and WM volumes increased with age. For regional volume, comparing with the model only held the age constant (model 1), the main effect of group altered when diagnosis-by-age interaction effects were considered (model 2). Here, participants with ASD had significantly greater relative regional GM volumes than TDC in the right inferior orbitofrontal cortex and bilateral thalamus; for WM, participants with ASD were larger than TDC in the bilateral splenium of corpus callosum and right anterior corona radiata. Importantly, significant diagnosis-by-age interactions were identified at the bilateral anterior prefrontal cortex, bilateral cuneus, bilateral caudate, and the left cerebellum Crus I for GM and left forceps minor for WM. Finally, age-stratified analyses (model 3) showed distinct patterns in GM and WM volumetric alterations in ASD among subsamples of children, adolescents, and adults.

          Conclusions

          Our findings suggest that the heterogeneous reports on the atypical neuroanatomy of ASD may substantially originate from age variation in the study samples. Age variation and its methodological and biological implications have to be carefully delineated in future studies of the neurobiology of ASD.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13229-015-0022-3) contains supplementary material, which is available to authorized users.

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          Most cited references77

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          Unusual brain growth patterns in early life in patients with autistic disorder: an MRI study.

          To quantify developmental abnormalities in cerebral and cerebellar volume in autism. The authors studied 60 autistic and 52 normal boys (age, 2 to 16 years) using MRI. Thirty autistic boys were diagnosed and scanned when 5 years or older. The other 30 were scanned when 2 through 4 years of age and then diagnosed with autism at least 2.5 years later, at an age when the diagnosis of autism is more reliable. Neonatal head circumferences from clinical records were available for 14 of 15 autistic 2- to 5-year-olds and, on average, were normal (35.1 +/- 1.3 cm versus clinical norms: 34.6 +/- 1.6 cm), indicative of normal overall brain volume at birth; one measure was above the 95th percentile. By ages 2 to 4 years, 90% of autistic boys had a brain volume larger than normal average, and 37% met criteria for developmental macrencephaly. Autistic 2- to 3-year-olds had more cerebral (18%) and cerebellar (39%) white matter, and more cerebral cortical gray matter (12%) than normal, whereas older autistic children and adolescents did not have such enlarged gray and white matter volumes. In the cerebellum, autistic boys had less gray matter, smaller ratio of gray to white matter, and smaller vermis lobules VI-VII than normal controls. Abnormal regulation of brain growth in autism results in early overgrowth followed by abnormally slowed growth. Hyperplasia was present in cerebral gray matter and cerebral and cerebellar white matter in early life in patients with autism.
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            Topography of the human corpus callosum revisited--comprehensive fiber tractography using diffusion tensor magnetic resonance imaging.

            Several tracing studies have established a topographical distribution of fiber connections to the cortex in midsagittal cross-sections of the corpus callosum (CC). The most prominent example is Witelson's scheme, which defines five vertical partitions mainly based on primate data. Conventional MRI of the human CC does not reveal morphologically discernable structures, although microscopy techniques identified myelinated axons with a relatively small diameter in the anterior and posterior third of the CC as opposed to thick fibers in the midbody and posterior splenium. Here, we applied diffusion tensor imaging (DTI) in conjunction with a tract-tracing algorithm to gain cortical connectivity information of the CC in individual subjects. With DTI-based tractography, we distinguished five vertical segments of the CC, containing fibers projecting into prefrontal, premotor (and supplementary motor), primary motor, and primary sensory areas as well as into parietal, temporal, and occipital cortical areas. Striking differences to Witelson's classification were recognized in the midbody and anterior third of the CC. In particular, callosal motor fiber bundles were found to cross the CC in a much more posterior location than previously indicated. Differences in water mobility were found to be in qualitative agreement with differences in the microstructure of transcallosal fibers yielding the highest anisotropy in posterior regions of the CC. The lowest anisotropy was observed in compartments assigned to motor and sensory cortical areas. In conclusion, DTI-based fiber tractography of healthy human subjects suggests a modification of the widely accepted Witelson scheme and a new classification of vertical CC partitions.
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              Neuron number and size in prefrontal cortex of children with autism.

              Autism often involves early brain overgrowth, including the prefrontal cortex (PFC). Although prefrontal abnormality has been theorized to underlie some autistic symptoms, the cellular defects that cause abnormal overgrowth remain unknown. To investigate whether early brain overgrowth in children with autism involves excess neuron numbers in the PFC. DESIGN, SETTING, AND CASES: Postmortem prefrontal tissue from 7 autistic and 6 control male children aged 2 to 16 years was examined by expert anatomists who were blinded to diagnostic status. Number and size of neurons were quantified using stereological methods within the dorsolateral (DL-PFC) and mesial (M-PFC) subdivisions of the PFC. Cases were from the eastern and southeastern United States and died between 2000 and 2006. Mean neuron number and size in the DL-PFC and M-PFC were compared between autistic and control postmortem cases. Correlations of neuron number with deviation in brain weight from normative values for age were also performed. Children with autism had 67% more neurons in the PFC (mean, 1.94 billion; 95% CI, 1.57-2.31) compared with control children (1.16 billion; 95% CI, 0.90-1.42; P = .002), including 79% more in DL-PFC (1.57 billion; 95% CI, 1.20-1.94 in autism cases vs 0.88 billion; 95% CI, 0.66-1.10 in controls; P = .003) and 29% more in M-PFC (0.36 billion; 95% CI, 0.33-0.40 in autism cases vs 0.28 billion; 95% CI, 0.23-0.34 in controls; P = .009). Brain weight in the autistic cases differed from normative mean weight for age by a mean of 17.6% (95% CI, 10.2%-25.0%; P = .001), while brains in controls differed by a mean of 0.2% (95% CI, -8.7% to 9.1%; P = .96). Plots of counts by weight showed autistic children had both greater total prefrontal neuron counts and brain weight for age than control children. In this small preliminary study, brain overgrowth in males with autism involved an abnormal excess number of neurons in the PFC.
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                Author and article information

                Contributors
                louislin28@gmail.com
                alanni0918@yahoo.com.tw
                mcl45@cam.ac.uk
                wytseng@ntu.edu.tw
                gaushufe@ntu.edu.tw
                Journal
                Mol Autism
                Mol Autism
                Molecular Autism
                BioMed Central (London )
                2040-2392
                21 May 2015
                21 May 2015
                2015
                : 6
                : 29
                Affiliations
                [ ]Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7 Chung-Shan South Road, Taipei, 10002 Taiwan
                [ ]Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, No. 1, Jen-Ai Road Section 1, Taipei, 10051 Taiwan
                [ ]Department of Child Psychiatry, Chang Gung Memorial Hospital at Linkou, No. 5 Fu-Hsing St., Taoyuan, 33305 Taiwan
                [ ]Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge, CB2 8AH UK
                [ ]Centre for Addiction and Mental Health, Hospital for Sick Children, and Department of Psychiatry, University of Toronto, 250 College St., Toronto, M5T 1R8 Canada
                [ ]Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, No. 1, Jen-Ai Road Section 1, Taipei, 10051 Taiwan
                [ ]Center for Optoelectronic Medicine, National Taiwan University College of Medicine, No. 1, Jen-Ai Road Section 1, Taipei, 10051 Taiwan
                Article
                22
                10.1186/s13229-015-0022-3
                4455336
                26045942
                e71f1f15-b8e5-4395-9225-138e5198c1e0
                © Lin et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 October 2014
                : 21 April 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Neurosciences
                autism spectrum disorder,structural mri,age,voxel-based morphometry,regional brain volume,development

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