This work is conducted under protocol 89-M-0006 (NCT00001246), and falls into two broad research themes: Theme 1: Studies of behavior and brain organization in typically-developing groups Work in this theme uses large-scale neuroimaging studies in health to advance our basic understanding of human brain organization, and guide the selection and application of imaging phenotypes for disease studies. We have emphasized structural magnetic resonance imaging (sMRI) because it offers intermediate in vivo phenotypes that can be reliably measured at scale, and are highly heritable, developmentally dynamic, sensitive to disease states, and amenable to translational study in mice. During the last year, we have published work in three main areas. First, we have sought to distill the large space of modern sMRI phenotypes by combining information from several distinct features of cortical anatomy. We have shown that the resulting individual-level brain networks (which are derived from conventional sMRI) can: capture cortical microarchitecture, predict >40% normative variance in IQ and provide a validated means of decoding neuroimaging maps from patients. Second, we have modeled major sources of variance in human brain anatomy, with a focus on total brain size. By detailing the scaling norms that couple size and shape in human brain, we have (i) improved detection and interpretation of changes associated with sex and neurodevelopmental disorders and (ii) defined a high-cost integrative brain system that is hyperexpanded in larger brains and vulnerable to neurodevelopmental disorders. Finally, we have developed new analytic methods for quantifying the degree of spatial convergence between different cortical maps. These new tools will make it easier to integrate different views of cortical organization. Theme 2: Deep phenotypic studies of participants with sex chromosome aneuploidy syndromes (SCAs) Work in this theme seeks to understand brain and behavioral changes in patients with genetically defined neurodevelopmental disorders focusing on sex chromosome aneuploidy syndromes (SCAs) in particular. Collectively, these studies are designed to expand on past work in SCA by gathering more comprehensive measures of brain structure and function, as well as providing more fine-grained information regarding the cognitive and behavioral variations that can be seen in SCA. These data will ultimately help to better define the developmental risks and resiliencies associated with X- and Y-chromosome dosage variation in humans and identify neurobiological systems that might underpin these associations. We hope these insights will (i) improve accurate public and professional awareness of SCAs, (ii) help clinicians provide more targeted assessment and counseling to patients and families with SCA, and (iii) begin to identify biological markers with the potential to ultimately improve assessment, prediction and treatment of neurodevelopmental issues in SCA. More broadly, this work in the specific case of SCA will shed light on (i) the principles that organize genetic influences on brain and behavior in the context of neuropsychiatric impairment, and (ii) sex chromosome contributions to sex differences in the brain, which are relevant for understanding the well-documented male bias in risk for neurodevelopmental disorders more generally. During the last year, we have published work in two main areas. First, we have used in vivo structural neuroimaging to detail how variations in X- and Y-chromosome dosage can shape folding of the cortical sheet a process that provides critical insight into very early phases of human brain development. Together with our other clinical neuroimaging studies, these findings help to pinpoint when and where genetic causes of neurodevelopmental difficulties can impact brain development. Second, to identify potential molecular bases for observed SCA effects, we have published the first study to systematically examine how X- and Y-chromosome dosage shape genome structure and function in humans. By modeling these effects in tissue from patients, we hope to identify root causes for the changes in brain and behavior that accompany different genetic forms of neurodevelopmental difficulties.

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U.S. National Institute of Mental Health
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Park, Min Tae M; Raznahan, Armin; Shaw, Philip et al. (2018) Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia. J Psychiatry Neurosci 43:170094
Raznahan, Armin; Parikshak, Neelroop N; Chandran, Vijay et al. (2018) Sex-chromosome dosage effects on gene expression in humans. Proc Natl Acad Sci U S A 115:7398-7403
Tissier, Cloélia; Linzarini, Adriano; Allaire-Duquette, Geneviève et al. (2018) Sulcal Polymorphisms of the IFC and ACC Contribute to Inhibitory Control Variability in Children and Adults. eNeuro 5:
Schmitt, J Eric; Giedd, Jay N; Raznahan, Armin et al. (2018) The Genetic Contributions to Maturational Coupling in the Human Cerebrum: A Longitudinal Pediatric Twin Imaging Study. Cereb Cortex 28:3184-3191
Park, Min Tae M; Raznahan, Armin; Shaw, Philip et al. (2018) Neuroanatomical phenotypes in mental illness: identifying convergent and divergent cortical phenotypes across autism, ADHD and schizophrenia. J Psychiatry Neurosci 43:201-212
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Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan et al. (2018) On testing for spatial correspondence between maps of human brain structure and function. Neuroimage 178:540-551
Seidlitz, Jakob; Váša, František; Shinn, Maxwell et al. (2018) Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation. Neuron 97:231-247.e7
Jowhar, Ziad; Gudla, Prabhakar R; Shachar, Sigal et al. (2018) HiCTMap: Detection and analysis of chromosome territory structure and position by high-throughput imaging. Methods 142:30-38
Tamnes, Christian K; Herting, Megan M; Goddings, Anne-Lise et al. (2017) Development of the Cerebral Cortex across Adolescence: A Multisample Study of Inter-Related Longitudinal Changes in Cortical Volume, Surface Area, and Thickness. J Neurosci 37:3402-3412

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