The Section on Neurobehavioral Clinical Research was established in the Social and Behavioral Research Branch of the NHGRI in October 2011. This report details progress towards its aim of understanding the interplay between behavioral, social, genetic and brain factors in development. The initial focus is on attention deficit hyperactivity disorder (ADHD), the most common psychiatric disorder of childhood that often persists into adulthood. In 2015-2016, our group has focused on families affected by ADHD, as this may prove a strategy for detecting the genes that may contribute to ADHD. In 2015, we assessed a total of 442 individuals, who came to the clinical center at NIH to complete clinical, behavioral, neuropsychological assessments along with brain imaging (using a magnetic resonance scanner). Research accomplishments. 1) The heritability of brain connectivity in families affected by ADHD. There has been limited progress in identifying the specific genes contributing to the established high heritability of ADHD. The use of heritable brain-based phenotypes pertinent to the disorder might accelerate progress in part as they lie closer to genes than the more distal clinical phenotype. Our group has thus been focusing on myriad structural and functional connections within the brain that support multiple cognitive, motor and affective processes. We do so as ADHD is increasingly viewed as the product of anomalous connectivity or miswiring that results in disruption to large-scale brain systems, producing symptoms. Imaging of the brains structural and functional connectivity provides a multitude of phenotypes and it is important to prioritize these for future genomic study. We take the strategy of first identifying the subset of phenotypes that is highly heritable. Such highly heritable phenotypes boost the chances of detecting underlying genes. Further prioritization can then be made on the strength of association with ADHD symptoms. To attain this goal we have completed multi-modal imaging on over 200 relatives from 24 extended, multigenerational families, in addition to 132 relatives from nuclear families. Using these data, we are now identifying the connections in the brain that are most highly heritable and strongly associated with ADHD. 2) Brain and behavior: problems with the control of movement and ADHD (Shaw, Weingart et al. 2016) One of the most fascinating aspects of problems with inattention, hyperactivity and impulsivity is the frequent overlap with problems with motor coordination or clumsiness. Indeed around half of children with clinically significant motor dyscoordination (Developmental Coordination Disorder) also have ADHD, and vice versa. Indeed, it has even been argued that this combination defines a distinct diagnostic group, which has underlying genetics and clinical outcomes that differ from either ADHD or DCD alone. We sought the neuroanatomic substrate of motor coordination in childhood and ask whether this substrate differs in the context of concurrent symptoms of ADHD. Participants were 226 children, who had DSM-5 based assessment of ADHD symptoms and standardized tests of motor coordination skills assessing aiming/catching, manual dexterity and balance. The presence of Developmental Coordination Disorder (DCD) was determined using a parent-completed questionnaire. Using magnetic resonance data acquired at 3 Tesla, four latent neuroanatomic variables (for the cerebral cortex, cerebellum, basal ganglia and thalamus) were extracted and mapped onto each motor coordination skill. We found that the motor coordination skill of aiming/catching was significantly linked to latent variables for both the cerebral cortex and the cerebellum. This effect was driven by the by the premotor/motor cortical regions and the superior cerebellar lobules. These links were not moderated by the severity of symptoms of inattention, hyperactivity and impulsivity. Using diagnostic categories, motor coordination regions showed atypical reduction in the clinical groups. However, these regions did not further differ between those with DCD alone and those with combined DCD/ADHD. This finding argues against seeing the combination of ADHD and DCD as a distinct category; rather the brain regions supporting motor coordination regions did not differ significantly between those who had probable DCD with or without comorbid ADHD. 3) The genetics of brain growth (Shaw 2015, Shaw 2016). In earlier work, our group demonstrated atypical anatomic development of interconnected brain structures in childhood ADHD- specifically, a lower velocity of growth of the prefrontal cortex (lateral prefrontal and paralimbic regions) and the (ventral) striatum. These brain regions form neural circuits supporting many of the behavioral characteristics of ADHD. We further demonstrated that these developmental trajectories are dimensional, that is quantitative traits that characterize the entire childhood population. Thus, as behavioral problems with impulse and motor control increase in typically developing children, the growth trajectories of key fronto-striatal regions more closely resemble those seen in children with the full syndrome of ADHD. My Section is now looking for genetic variants that influence the growth of these structures, mapping genetic variation throughout the entire genome. This could throw light onto the biological mechanisms underlying dysregulated control of impulses and attention. 4) Ongoing social scientific projects (Szekely, Pappa et al. 2015, Verlinden, Jansen et al. 2015, O'Connor 2016). Children who have ADHD are embedded in an array of social contexts that include the family, schools and the larger community. While the family has attracted a great deal of research interest in ADHD, there has been less study of relationships with peers. Relationships with peers are important for childrens mental health, yet little is known of their etiological underpinnings. We thus explored the genetic influences on childhood peer network characteristics in three different networksdefined by rejection, acceptance, and prosocial behavior. We further define the impact of early life mental health trajectories on these same peer network characteristics. Specifically, we ask if the developmental trajectories of preschool externalizing and internalizing behavior are uniquely linked to a childs later role within peer networks. Participants were 1,288 children from a Dutch birth cohort (the Generation R Study). At age 7, we mapped out childrens classroom peer networks for peer rejection, acceptance, and prosocial behavior using mutual peer nominations. Genetic influences on childrens peer network characteristics were estimated from DNA using genome-wide complex trait analysis. Developmental trajectories of preschool externalizing and internalizing behavior were computed using parental ratings at ages 1.5, 3 and 5 years. Of the three network properties examined, closeness centrality emerged as significantly heritable across all networks. Preschool externalizing problems predicted unfavorable positions within peer rejection networks and having fewer mutual friendships. In contrast, children with preschool internalizing problems were not actively rejected by their peers but were less well connected within their social support network. Recent methodological advances in genomics can orient us to the role of genes in shaping a childs position within peer networks; while network perspectives offer rich insights into how early externalizing and internalizing problems impact a childs later functioning within peer networks.

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Shaw, Philip; Ishii-Takahashi, Ayaka; Park, Min Tae et al. (2018) A multicohort, longitudinal study of cerebellar development in attention deficit hyperactivity disorder. J Child Psychol Psychiatry 59:1114-1123
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
White, Tonya; Jansen, Philip R; Muetzel, Ryan L et al. (2018) Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface-based reconstruction. Hum Brain Mapp 39:1218-1231
Kong, Xiang-Zhen; Mathias, Samuel R; Guadalupe, Tulio et al. (2018) Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proc Natl Acad Sci U S A 115:E5154-E5163
Chen, Y-C; Sudre, G; Sharp, W et al. (2018) Neuroanatomic, epigenetic and genetic differences in monozygotic twins discordant for attention deficit hyperactivity disorder. Mol Psychiatry 23:683-690
Szekely, Eszter; Sudre, Gustavo P; Sharp, Wendy et al. (2017) Defining the Neural Substrate of the Adult Outcome of Childhood ADHD: A Multimodal Neuroimaging Study of Response Inhibition. Am J Psychiatry 174:867-876
Shaw, Philip; Ahn, Kwangmi; Rapoport, Judith L (2017) Good News for Screening for Adult Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry 74:527
Sudre, Gustavo; Choudhuri, Saadia; Szekely, Eszter et al. (2017) Estimating the Heritability of Structural and Functional Brain Connectivity in Families Affected by Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry 74:76-84
Hoogman, Martine; Bralten, Janita; Hibar, Derrek P et al. (2017) Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis. Lancet Psychiatry 4:310-319
Shaw, Philip (2016) Quantifying the Benefits and Risks of Methylphenidate as Treatment for Childhood Attention-Deficit/Hyperactivity Disorder. JAMA 315:1953-5

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