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      Reduced gray matter volume and cortical thickness associated with traffic-related air pollution in a longitudinally studied pediatric cohort

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          Abstract

          Early life exposure to air pollution poses a significant risk to brain development from direct exposure to toxicants or via indirect mechanisms involving the circulatory, pulmonary or gastrointestinal systems. In children, exposure to traffic related air pollution has been associated with adverse effects on cognitive, behavioral and psychomotor development. We aimed to determine whether childhood exposure to traffic related air pollution is associated with regional differences in brain volume and cortical thickness among children enrolled in a longitudinal cohort study of traffic related air pollution and child health. We used magnetic resonance imaging to obtain anatomical brain images from a nested subset of 12 year old participants characterized with either high or low levels of traffic related air pollution exposure during their first year of life. We employed voxel-based morphometry to examine group differences in regional brain volume, and with separate analyses, changes in cortical thickness. Smaller regional gray matter volumes were determined in the left pre- and post-central gyri, the cerebellum, and inferior parietal lobe of participants in the high traffic related air pollution exposure group relative to participants with low exposure. Reduced cortical thickness was observed in participants with high exposure relative to those with low exposure, primarily in sensorimotor regions of the brain including the pre- and post-central gyri and the paracentral lobule, but also within the frontal and limbic regions. These results suggest that significant childhood exposure to traffic related air pollution is associated with structural alterations in brain.

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          Specification of cerebral cortical areas.

          P Rakic (1988)
          How the immense population of neurons that constitute the human cerebral neocortex is generated from progenitors lining the cerebral ventricle and then distributed to appropriate layers of distinctive cytoarchitectonic areas can be explained by the radial unit hypothesis. According to this hypothesis, the ependymal layer of the embryonic cerebral ventricle consists of proliferative units that provide a proto-map of prospective cytoarchitectonic areas. The output of the proliferative units is translated via glial guides to the expanding cortex in the form of ontogenetic columns, whose final number for each area can be modified through interaction with afferent input. Data obtained through various advanced neurobiological techniques, including electron microscopy, immunocytochemistry, [3H]thymidine and receptor autoradiography, retrovirus gene transfer, neural transplants, and surgical or genetic manipulation of cortical development, furnish new details about the kinetics of cell proliferation, their lineage relationships, and phenotypic expression that favor this hypothesis. The radial unit model provides a framework for understanding cerebral evolution, epigenetic regulation of the parcellation of cytoarchitectonic areas, and insight into the pathogenesis of certain cortical disorders in humans.
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            Distinct genetic influences on cortical surface area and cortical thickness.

            Neuroimaging studies examining the effects of aging and neuropsychiatric disorders on the cerebral cortex have largely been based on measures of cortical volume. Given that cortical volume is a product of thickness and surface area, it is plausible that measures of volume capture at least 2 distinct sets of genetic influences. The present study aims to examine the genetic relationships between measures of cortical surface area and thickness. Participants were men in the Vietnam Era Twin Study of Aging (110 monozygotic pairs and 92 dizygotic pairs). Mean age was 55.8 years (range: 51-59). Bivariate twin analyses were utilized in order to estimate the heritability of cortical surface area and thickness, as well as their degree of genetic overlap. Total cortical surface area and average cortical thickness were both highly heritable (0.89 and 0.81, respectively) but were essentially unrelated genetically (genetic correlation = 0.08). This pattern was similar at the lobar and regional levels of analysis. These results demonstrate that cortical volume measures combine at least 2 distinct sources of genetic influences. We conclude that using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.
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              Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation.

              There is controversy over the nature of the disturbance in brain development that underpins attention-deficit/hyperactivity disorder (ADHD). In particular, it is unclear whether the disorder results from a delay in brain maturation or whether it represents a complete deviation from the template of typical development. Using computational neuroanatomic techniques, we estimated cortical thickness at >40,000 cerebral points from 824 magnetic resonance scans acquired prospectively on 223 children with ADHD and 223 typically developing controls. With this sample size, we could define the growth trajectory of each cortical point, delineating a phase of childhood increase followed by adolescent decrease in cortical thickness (a quadratic growth model). From these trajectories, the age of attaining peak cortical thickness was derived and used as an index of cortical maturation. We found maturation to progress in a similar manner regionally in both children with and without ADHD, with primary sensory areas attaining peak cortical thickness before polymodal, high-order association areas. However, there was a marked delay in ADHD in attaining peak thickness throughout most of the cerebrum: the median age by which 50% of the cortical points attained peak thickness for this group was 10.5 years (SE 0.01), which was significantly later than the median age of 7.5 years (SE 0.02) for typically developing controls (log rank test chi(1)(2) = 5,609, P < 1.0 x 10(-20)). The delay was most prominent in prefrontal regions important for control of cognitive processes including attention and motor planning. Neuroanatomic documentation of a delay in regional cortical maturation in ADHD has not been previously reported.
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                Author and article information

                Contributors
                Role: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Validation
                Role: Data curationRole: InvestigationRole: Project administration
                Role: Data curationRole: InvestigationRole: Project administration
                Role: Data curationRole: InvestigationRole: Project administration
                Role: Formal analysisRole: Methodology
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: Supervision
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Methodology
                Role: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 January 2020
                2020
                : 15
                : 1
                : e0228092
                Affiliations
                [1 ] Molecular Epidemiology in Children’s Environmental Health Training Program, Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
                [2 ] Imaging Research Center, Department of Radiology, Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
                [3 ] Division of Biostatistics and Epidemiology, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
                [4 ] Department of Psychology, Western Kentucky University, Bowling Green, Kentucky, United States of America
                [5 ] Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
                [6 ] Division of General and Community Pediatrics, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
                Nuovo Ospedale Prato (NOP) Santo Stefano, USL Toscana Centro, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-6128-8464
                Article
                PONE-D-19-27642
                10.1371/journal.pone.0228092
                6980590
                31978108
                41ae1942-b1a3-4b28-b7e7-27bb69867bcf
                © 2020 Beckwith et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 October 2019
                : 7 January 2020
                Page count
                Figures: 2, Tables: 4, Pages: 19
                Funding
                Funded by: National Institute for Environmental Health Sciences
                Award ID: R01 ES019890
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000066, National Institute of Environmental Health Sciences;
                Award ID: R01 ES027224
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000066, National Institute of Environmental Health Sciences;
                Award ID: R01 ES026446
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1 TR001425
                Funded by: funder-id http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: T32 ES10957
                This work was funded by the National Institute for Environmental Health Sciences (NIEHS; https://www.niehs.nih.gov/), award numbers R01 ES019890 (P.R), R01 ES027224 (K.Y.), and R01 ES026446 (K.C.); the National Center for Advancing Translational Sciences of the National Institutes of Health (NCATS; https://ncats.nih.gov/), award number UL1 TR001425; and a National Institutes of Health (NIH; https://www.nih.gov/; https://researchtraining.nih.gov/programs/training-grants/T32) training grant awarded to the Molecular Epidemiology in Children’s Environmental Health Training Program (MECEH), award number T32-ES10957. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Central Nervous System
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                Nervous System
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                The data and code used in the study are not available in the public domain. Data usage is currently governed by the Institutional Review Board at Cincinnati Children’s Hospital Medical Center. The data contains sensitive information and is confidential. De-identified data will be provided following CCHMC IRB approval. Please contact the corresponding author for data requests. The CCHMC IRB may be reached via email at irb@ 123456cchmc.org or ORCRA@ 123456cchmc.org , or by phone at 513.636.8039.

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