Showing papers by "Tonya White published in 2018"

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Abstract: Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways.

Abstract: Neuroticism is an important risk factor for psychiatric traits, including depression1, anxiety2,3, and schizophrenia4-6. At the time of analysis, previous genome-wide association studies7-12 (GWAS) reported 16 genomic loci associated to neuroticism10-12. Here we conducted a large GWAS meta-analysis (n = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts (P = 3.49 × 10-8), medium spiny neurons (P = 4.23 × 10-8), and serotonergic neurons (P = 1.37 × 10-7). Gene set analyses implicated three specific pathways: neurogenesis (P = 4.43 × 10-9), behavioral response to cocaine processes (P = 1.84 × 10-7), and axon part (P = 5.26 × 10-8). We show that neuroticism's genetic signal partly originates in two genetically distinguishable subclusters13 ('depressed affect' and 'worry'), suggesting distinct causal mechanisms for subtypes of individuals. Mendelian randomization analysis showed unidirectional and bidirectional effects between neuroticism and multiple psychiatric traits. These results enhance neurobiological understanding of neuroticism and provide specific leads for functional follow-up experiments.

Widespread white matter microstructural differences in schizophrenia across 4322 individuals : results from the ENIGMA Schizophrenia DTI Working Group

Abstract: The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity.

Abstract: Prevalence of certain forms of psychopathology, such as autism and depression, differs between genders and understanding gender differences of the neurotypical brain may provide insights into risk and protective factors. In recent research, resting state functional magnetic resonance imaging (rfMRI) is widely used to map the inherent functional networks of the brain. Although previous studies have reported gender differences in rfMRI, the robustness of gender differences is not well characterized. In this study, we use a large data set to test whether rfMRI functional connectivity (FC) can be used to predict gender and identify FC features that are most predictive of gender. We utilized rfMRI data from 820 healthy controls from the Human Connectome Project. By applying a predefined functional template and partial least squares regression modeling, we achieved a gender prediction accuracy of 87% when multi-run rfMRI was used. Permutation tests confirmed that gender prediction was reliable ( p<.001). Effects of motion, age, handedness, blood pressure, weight, and brain volume on gender prediction are discussed. Further, we found that FC features within the default mode (DMN), fronto-parietal and sensorimotor networks contributed most to gender prediction. In the DMN, right fusiform gyrus and right ventromedial prefrontal cortex were important contributors. The above regions have been previously implicated in aspects of social functioning and this suggests potential gender differences in social cognition mediated by the DMN. Our findings demonstrate that gender can be reliably predicted using rfMRI data and highlight the importance of controlling for gender in brain imaging studies.

Paediatric population neuroimaging and the Generation R Study: the second wave

Abstract: Paediatric population neuroimaging is an emerging field that falls at the intersection between developmental neuroscience and epidemiology. A key feature of population neuroimaging studies involves large-scale recruitment that is representative of the general population. One successful approach for population neuroimaging is to embed neuroimaging studies within large epidemiological cohorts. The Generation R Study is a large, prospective population-based birth-cohort in which nearly 10,000 pregnant mothers were recruited between 2002 and 2006 with repeated measurements in the children and their parents over time. Magnetic resonance imaging was included in 2009 with the scanning of 1070 6-to-9-year-old children. The second neuroimaging wave was initiated in April 2013 with a total of 4245 visiting the MRI suite and 4087 9-to-11-year-old children being scanned. The sequences included high-resolution structural MRI, 35-direction diffusion weighted imaging, and a 6 min and 2 s resting-state functional MRI scan. The goal of this paper is to provide an overview of the imaging protocol and the overlap between the neuroimaging data and metadata. We conclude by providing a brief overview of results from our first wave of neuroimaging, which highlights a diverse array of questions that can be addressed by merging the fields of developmental neuroscience and epidemiology.

Tracking Brain Development and Dimensional Psychiatric Symptoms in Children: A Longitudinal Population-Based Neuroimaging Study.

Abstract: Objective:Psychiatric symptomatology during childhood predicts persistent mental illness later in life. While neuroimaging methodologies are routinely applied cross-sectionally to the study of child and adolescent psychopathology, the nature of the relationship between childhood symptoms and the underlying neurodevelopmental processes remains unclear. The authors used a prospective population-based cohort to delineate the longitudinal relationship between childhood psychiatric problems and brain development.Method:A total of 845 children participated in the study. Psychiatric symptoms were measured with the parent-rated Child Behavior Checklist at ages 6 and 10. MRI data were collected at ages 8 and 10. Cross-lagged panel models and linear mixed-effects models were used to determine the associations between psychiatric symptom ratings and quantitative anatomic and white matter microstructural measures over time.Results:Higher ratings for externalizing and internalizing symptoms at baseline predicted small...

Connectivity dynamics in typical development and its relationship to autistic traits and autism spectrum disorder.

Abstract: Recent advances in neuroimaging techniques have provided significant insights into developmental trajectories of human brain function. Characterizations of typical neurodevelopment provide a framework for understanding altered neurodevelopment, including differences in brain function related to developmental disorders and psychopathology. Historically, most functional connectivity studies of typical and atypical development operate under the assumption that connectivity remains static over time. We hypothesized that relaxing stationarity assumptions would reveal novel features of both typical brain development related to children on the autism spectrum. We employed a "chronnectomic" (recurring, time-varying patterns of connectivity) approach to evaluate transient states of connectivity using resting-state functional MRI in a population-based sample of 774 6- to 10-year-old children. Dynamic connectivity was evaluated using a sliding-window approach, and revealed four transient states. Internetwork connectivity increased with age in modularized dynamic states, illustrating an important pattern of connectivity in the developing brain. Furthermore, we demonstrated that higher levels of autistic traits and ASD diagnosis were associated with longer dwell times in a globally disconnected state. These results provide a roadmap to the chronnectomic organization of the developing brain and suggest that characteristics of functional brain connectivity are related to children on the autism spectrum.

The bidirectional association between sleep problems and autism spectrum disorder: a population-based cohort study.

Abstract: Sleep difficulties are prevalent in children with autism spectrum disorder (ASD). The temporal nature of the association between sleep problems and ASD is unclear because longitudinal studies are lacking. Our aim is to clarify whether sleep problems precede and worsen autistic traits and ASD or occur as a consequence of the disorder. Repeated sleep measures were available at 1.5, 3, 6, and 9 years of age in 5151 children participating in the Generation R Study, a large prospective birth cohort in the Netherlands. Autistic traits were determined with the Pervasive Developmental Problems score (PDP) of the Child Behavior Checklist (CBCL) at 1.5 and 3 years and the Social Responsiveness Scale (SRS) at 6 years. This cohort included 81 children diagnosed with ASD. Sleep problems in early childhood were prospectively associated with a higher SRS score, but not when correcting for baseline PDP score. By contrast, a higher SRS score and an ASD diagnosis were associated with more sleep problems at later ages, even when adjusting for baseline sleep problems. Likewise, a trajectory of increasing sleep problems was associated with ASD. Sleep problems and ASD are not bidirectionally associated. Sleep problems do not precede and worsen autistic behavior but rather co-occur with autistic traits in early childhood. Over time, children with ASD have an increase in sleep problems, whereas typically developing children have a decrease in sleep problems. Our findings suggest that sleep problems are part of the construct ASD.

Polygenic scores for schizophrenia and educational attainment are associated with behavioural problems in early childhood in the general population.

Abstract: Background: Genome-wide association studies in adults have identified numerous genetic variants related to psychiatric disorders and related traits, such as schizophrenia and educational attainment. However, the effects of these genetic variants on behaviour in the general population remain to be fully understood, particularly in younger populations. We investigated whether polygenic scores of five psychiatric disorders and educational attainment are related to emotional and behaviour problems during early childhood. Methods: From the Generation R Study, we included participants with available genotype data and behavioural problems measured with the Child Behavior Checklist (CBCL) at the age of 3 (n = 1,902), 6 (n = 2,202) and 10 years old (n = 1,843). Polygenic scores were calculated for five psychiatric disorders and educational attainment. These polygenic scores were tested for an association with the broadband internalizing and externalizing problem scales and the specific CBCL syndrome scale scores. Results: Analysis of the CBCL broadband scales showed that the schizophrenia polygenic score was associated with significantly higher internalizing scores at 3, 6 and 10 years and higher externalizing scores at age 3 and 6. The educational attainment polygenic score was associated with lower externalizing scores at all time points and lower internalizing scores at age 3. No associations were observed for the polygenic scores of bipolar disorder, major depressive disorder and autism spectrum disorder. Secondary analyses of specific syndrome scores showed that the schizophrenia polygenic score was strongly related to the Thought Problems scores. A negative association was observed between the educational attainment polygenic score and Attention Problems scores across all age groups. Conclusions: Polygenic scores for adult psychiatric disorders and educational attainment are associated with variation in emotional and behavioural problems already at a very early age.

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface-based reconstruction.

Abstract: Motion-related artifacts are one of the major challenges associated with pediatric neuroimaging. Recent studies have shown a relationship between visual quality ratings of T1 images and cortical reconstruction measures. Automated algorithms offer more precision in quantifying movement-related artifacts compared to visual inspection. Thus, the goal of this study was to test three different automated quality assessment algorithms for structural MRI scans. The three algorithms included a Fourier-, integral-, and a gradient-based approach which were run on raw T1-weighted imaging data collected from four different scanners. The four cohorts included a total of 6,662 MRI scans from two waves of the Generation R Study, the NIH NHGRI Study, and the GUSTO Study. Using receiver operating characteristics with visually inspected quality ratings of the T1 images, the area under the curve (AUC) for the gradient algorithm, which performed better than either the integral or Fourier approaches, was 0.95, 0.88, and 0.82 for the Generation R, NHGRI, and GUSTO studies, respectively. For scans of poor initial quality, repeating the scan often resulted in a better quality second image. Finally, we found that even minor differences in automated quality measurements were associated with FreeSurfer derived measures of cortical thickness and surface area, even in scans that were rated as good quality. Our findings suggest that the inclusion of automated quality assessment measures can augment visual inspection and may find use as a covariate in analyses or to identify thresholds to exclude poor quality data.

The genetic architecture of the human cerebral cortex

Abstract: The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 35,660 individuals with replication in 15,578 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 206 nominally significant loci (P ≤ 5 x 10 -8 ); 150 survived multiple testing correction (P ≤ 8.3 x 10 -10 ; 140 surface area; 10 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson9s disease, insomnia, depression and ADHD. NOTE: K.L.G. and N.J. contributed to this work as co-first authors for this preprint. J.N.P., L.C.-C., J.B., D.P.H., P.A.L., F.P. contributed to this work as co-second authors for this preprint. J.L.S., P.M.T., S.E.M. contributed to this work as co-last authors for this preprint.

Genome-wide Analysis of Insomnia (N=1,331,010) Identifies Novel Loci and Functional Pathways

Abstract: Insomnia is the second-most prevalent mental disorder, with no sufficient treatment available. Despite a substantial role of genetic factors, only a handful of genes have been implicated and insight into the associated neurobiological pathways remains limited. Here, we use an unprecedented large genetic association sample (N=1,331,010) to allow detection of a substantial number of genetic variants and gain insight into biological functions, cell types and tissues involved in insomnia. We identify 202 genome-wide significant loci implicating 956 genes through positional, eQTL and chromatin interaction mapping. We show involvement of the axonal part of neurons, of specific cortical and subcortical tissues, and of two specific cell-types in insomnia: striatal medium spiny neurons and hypothalamic neurons. These cell-types have been implicated previously in the regulation of reward processing, sleep and arousal in animal studies, but have never been genetically linked to insomnia in humans. We found weak genetic correlations with other sleep-related traits, but strong genetic correlations with psychiatric and metabolic traits. Mendelian randomization identified causal effects of insomnia on specific psychiatric and metabolic traits. Our findings reveal key brain areas and cells implicated in the neurobiology of insomnia and its related disorders, and provide novel targets for treatment.

Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume

Abstract: The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρgenetic = -0.59, p-value = 3.14 × 10-6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.

A multicohort, longitudinal study of cerebellar development in attention deficit hyperactivity disorder

Abstract: Background: The cerebellum supports many cognitive functions disrupted in attention deficit hyperactivity disorder (ADHD). Prior neuroanatomic studies have been often limited by small sample sizes, inconsistent findings, and a reliance on cross-sectional data, limiting inferences about cerebellar development. Here, we conduct a multicohort study using longitudinal data, to characterize cerebellar development. Methods: Growth trajectories of the cerebellar vermis, hemispheres and white matter were estimated using piecewise linear regression from 1,656 youth; of whom 63% had longitudinal data, totaling 2,914 scans. Four cohorts participated, all contained childhood data (age 4–12 years); two had adolescent data (12–25 years). Growth parameters were combined using random-effects meta-analysis. Results: Diagnostic differences in growth were confined to the corpus medullare (cerebellar white matter). Here, the ADHD group showed slower growth in early childhood compared to the typically developing group (left corpus medullare z = 2.49, p =.01; right z = 2.03, p =.04). This reversed in late childhood, with faster growth in ADHD in the left corpus medullare (z = 2.06, p =.04). Findings held when gender, intelligence, comorbidity, and psychostimulant medication were considered. Discussion: Across four independent cohorts, containing predominately longitudinal data, we found diagnostic differences in the growth of cerebellar white matter. In ADHD, slower white matter growth in early childhood was followed by faster growth in late childhood. The findings are consistent with the concept of ADHD as a disorder of the brain's structural connections, formed partly by developing cortico-cerebellar white matter tracts.

Prenatal exposure to maternal and paternal depressive symptoms and white matter microstructure in children.

Abstract: Background: Prenatal maternal depression has been associated with multiple problems in offspring involving affect, cognition, and neuroendocrine functioning. This suggests that prenatal depression influences neurodevelopment. However, the underlying neurodevelopmental mechanism remains unclear. We prospectively assessed whether maternal depressive symptoms during pregnancy and at the child's age 3 years are related to white matter microstructure in 690 children. The association of paternal depressive symptoms with childhood white matter microstructure was assessed to evaluate genetic or familial confounding. Methods: Parental depressive symptoms were measured using the Brief Symptom Inventory. In children aged 6-9 years, we used diffusion tensor imaging to assess white matter microstructure characteristics including fractional anisotropy (FA) and mean diffusivity (MD). Results: Exposure to maternal depressive symptoms during pregnancy was associated with higher MD in the uncinate fasciculus and to lower FA and higher MD in the cingulum bundle. No associations of maternal depressive symptoms at the child's age of 3 years with white matter characteristics were observed. Paternal depressive symptoms also showed a trend toward significance for a lower FA in the cingulum bundle. Conclusions: Prenatal maternal depressive symptoms were associated with higher MD in the uncinate fasciculus and the cingulum bundle. These structures are part of the limbic system, which is involved in motivation, emotion, learning, and memory. As paternal depressive symptoms were also related to lower FA in the cingulum, the observed effect may partly reflect a genetic predisposition and shared environmental family factors and to a lesser extent a specific intrauterine effect.

Maternal depressive symptoms during pregnancy are associated with amygdala hyperresponsivity in children

Abstract: Depression during pregnancy is highly prevalent and has a multitude of potential risks of the offspring. Among confirmed consequences is a higher risk of psychopathology. However, it is unknown how maternal depression may impact the child’s brain to mediate this vulnerability. Here we studied amygdala functioning, using task-based functional MRI, in children aged 6–9 years as a function of prenatal maternal depressive symptoms selected from a prospective population-based sample (The Generation R Study). We show that children exposed to clinically relevant maternal depressive symptoms during pregnancy (N = 19) have increased amygdala responses to negative emotional faces compared to control children (N = 20) [F(1,36) 7.02, p = 0.022]. Strikingly, postnatal maternal depressive symptoms, obtained at 3 years after birth, did not explain this relation. Our findings are in line with a model in which prenatal depressive symptoms of the mother are associated with amygdala hyperresponsivity in her offspring, which may represent a risk factor for later-life psychopathology.

Socialization of prosocial behavior: Gender differences in the mediating role of child brain volume

Abstract: Evidence has been accumulating for the impact of normal variation in caregiving quality on brain morphology in children, but the question remains whether differences in brain volume related to early caregiving translate to behavioral implications. In this longitudinal population-based study (N = 162), moderated mediation was tested for the relation between parental sensitivity and child prosocial behavior via brain volume, in boys and girls. Both maternal and paternal sensitivity were repeatedly observed between 1 and 4 years of age. Brain volume was assessed using magnetic resonance imaging measurements at age 8, and self-reported prosocial behavior of children was assessed at 9 years of age. Parental sensitivity was positively related to child brain volume, and to child prosocial behavior at trend level. Child brain volume was negatively related to child prosocial behavior. A significant gender-by-brain interaction was found, illustrating that daughters of sensitive parents were more prosocial and that less prosocial behavior was reported for girls with a larger total brain volume. Child gender significantly moderated the indirect effect of parental sensitivity on prosocial behavior via total brain volume. A significant indirect pathway was found only in girls. The results warrant replication but indicate the importance of considering gender when studying the behavioral implications of differences in brain volume related to early caregiving experiences.

Association of Genetic Risk for Schizophrenia and Bipolar Disorder With Infant Neuromotor Development.

Abstract: Schizophrenia and bipolar disorder (BD) are heritable disorders with similarities in clinical symptoms and typical onset after puberty. While research shows that impaired motor coordination can have an associationwith schizophrenia, there are limited data on childhood development preceding BD. Murray et al proposed a developmental model for similarities and dissimilarities between schizophrenia and BD, but it remains unknown if dissimilarities exist in early infancy and if they covary with genetic liability for these disorders. Using polygenic risk scores (PRSs),we exploredwhether genetic risk for schizophrenia and genetic risk for BD are associated with neuromotor development in infancy.

A prospective study of fetal head growth, autistic traits and autism spectrum disorder

Abstract: Altered trajectories of brain growth are often reported in Autism Spectrum Disorder (ASD), particularly during the first year of life. However, less is known about prenatal head growth trajectories, and no study has examined the relation with postnatal autistic symptom severity. The current study prospectively examined the association between fetal head growth and the spectrum of autistic symptom severity in two large population-based cohorts, including a sample of individuals with clinically diagnosed ASD. This study included 3,820 children from two longitudinal prenatal cohorts in The Netherlands and Australia, comprising 60 individuals with a confirmed diagnosis of ASD. Latent growth curve models were used to examine the relationship between fetal head circumference measured at three different time points and autistic traits measured in postnatal life using either the Social Responsiveness Scale or the Autism-Spectrum Quotient. While lower initial prenatal HC was weakly associated with increasing autistic traits in the Dutch cohort, this relationship was not observed in the Australian cohort, nor when the two cohorts were analysed together. No differences in prenatal head growth were found between individuals with ASD and controls. This large population-based study identified no consistent association across two cohorts between prenatal head growth and postnatal autistic traits. Our mixed findings suggest that further research in this area is needed. Autism Res 2018, 11: 602-612. © 2018 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc. Lay summary It is not known whether different patterns of postnatal brain growth in Autism Spectrum Disorder (ASD) also occurs prenatally. We examined fetal head growth and autistic symptoms in two large groups from The Netherlands and Australia. Lower initial prenatal head circumference was associated with autistic traits in the Dutch, but not the Australian, group. No differences in head growth were found in individuals with ASD and controls when the data was combined. Our mixed findings suggest that more research in this area is needed.

Genetic associations with childhood brain growth, defined in two longitudinal cohorts

Abstract: Genome-wide association studies (GWASs) are unraveling the genetics of adult brain neuroanatomy as measured by cross-sectional anatomic magnetic resonance imaging (aMRI). However, the genetic mechanisms that shape childhood brain development are, as yet, largely unexplored. In this study we identify common genetic variants associated with childhood brain development as defined by longitudinal aMRI. Genome-wide single nucleotide polymorphism (SNP) data were determined in two cohorts: one enriched for attention-deficit/hyperactivity disorder (ADHD) (LONG cohort: 458 participants; 119 with ADHD) and the other from a population-based cohort (Generation R: 257 participants). The growth of the brain's major regions (cerebral cortex, white matter, basal ganglia, and cerebellum) and one region of interest (the right lateral prefrontal cortex) were defined on all individuals from two aMRIs, and a GWAS and a pathway analysis were performed. In addition, association between polygenic risk for ADHD and brain growth was determined for the LONG cohort. For white matter growth, GWAS meta-analysis identified a genome-wide significant intergenic SNP (rs12386571, P = 9.09 × 10−9), near AKR1B10. This gene is part of the aldo-keto reductase superfamily and shows neural expression. No enrichment of neural pathways was detected and polygenic risk for ADHD was not associated with the brain growth phenotypes in the LONG cohort that was enriched for the diagnosis of ADHD. The study illustrates the use of a novel brain growth phenotype defined in vivo for further study.

Working Memory Training Following Neonatal Critical Illness: A Randomized Controlled Trial

Abstract: Objectives:To test the immediate and long-term effectiveness of Cogmed Working Memory Training following extracorporeal membrane oxygenation and/or congenital diaphragmatic hernia.Design:A nationwide randomized controlled trial assessing neuropsychologic outcome immediately and 1 year post Cogmed Wo

Cerebellar Growth Impairment Characterizes School-Aged Children Born Preterm without Perinatal Brain Lesions.

Abstract: BACKGROUND AND PURPOSE: Infants born preterm are commonly diagnosed with structural brain lesions known to affect long-term neurodevelopment negatively. Yet, the effects of preterm birth on brain development in the absence of intracranial lesions remain to be studied in detail. In this study, we aim to quantify long term consequences of preterm birth on brain development in this specific group. MATERIALS AND METHODS: Neonatal cranial sonography and follow-up T1-weighted MR imaging and DTI were performed to evaluate whether the anatomic characteristics of the cerebrum and cerebellum in a cohort of school-aged children (6–12 years of age) were related to gestational age at birth in children free of brain lesions in the perinatal period. RESULTS: In the cohort consisting of 36 preterm (28–37 weeks9 gestational age) and 66 term-born infants, T1-weighted MR imaging and DTI at 6–12 years revealed a reduction of cerebellar white matter volume (β = 0.387, P P = .02), and a reduction of cerebellar gray and white matter surface area (β = 0.337, P P CONCLUSIONS: The results of our study show that perinatal influences that are not primarily neurologic are still able to disturb long-term neurodevelopment, particularly of the developing cerebellum. Including the cerebellum in future neuroprotective strategies seems therefore essential.

Differential patterns of age-related cortical and subcortical functional connectivity in 6-to-10 year old children: A connectome-wide association study.

Abstract: Introduction: Typical brain development is characterized by specific patterns of maturation of functional networks. Cortico-cortical connectivity generally increases, whereas subcortico-cortical connections often decrease. Little is known about connectivity changes amongst different subcortical regions in typical development. Methods: This study examined age- and gender-related differences in functional connectivity between and within cortical and subcortical regions using two different approaches. The participants included 411 six- to ten-year-old typically developing children sampled from the population-based Generation R study. Functional connectomes were defined in native space using regions of interest from subject-specific FreeSurfer segmentations. Connections were defined as: (a) the correlation between regional mean time-series; and (b) the focal maximum of voxel-wise correlations within FreeSurfer regions. The association of age and gender with each functional connection was determined using linear regression. The preprocessing included the exclusion of children with excessive head motion and scrubbing to reduce the influence of minor head motion during scanning. Results: Cortico-cortical associations echoed previous findings that connectivity shifts from short to long-range with age. Subcortico-cortical associations with age were primarily negative in the focal network approach but were both positive and negative in the mean time-series network approach. Between subcortical regions, age-related associations were negative in both network approaches. Few connections had significant associations with gender. Conclusions: The present study replicates previously reported age-related patterns of connectivity in a relatively narrow age-range of children. In addition, we extended these findings by demonstrating decreased connectivity within the subcortex with increasing age. Lastly, we show the utility of a more focal approach that challenges the spatial assumptions made by the traditional mean time series approach.

Neuroanatomical correlates of donating behavior in middle childhood.

Abstract: The neurobiological correlates of prosocial behavior are largely unknown. We examined brain structure and functional connectivity correlates of donating to a charity, a specific, costly, form of prosocial behavior. In 163 children, donating was measured using a promotional clip for a charity including a call for donations. Children could decide privately whether and how much they wanted to donate from money they had received earlier. Whole brain structural MRI scans were obtained to study associations between cortical thickness and donating behavior. In addition, resting state functional MRI scans were obtained to study whole brain functional connectivity and to examine functional connectivity between regions identified using structural MRI. In the lateral orbitofrontal cortex/pars orbitalis and pre-/postcentral cortex, a thicker cortex was associated with higher donations. Functional connectivity with these regions was not associated with donating behavior. These results suggest that donating behavior is not only situationally driven, but is also related brain morphology. The absence of functional connectivity correlates might imply that the associations with cortical thickness are involved in different underlying mechanisms of donating.

Tomboys Revisited: A Retrospective Comparison of Childhood Behavioral Patterns in Lesbians and Transmen

Abstract: In 1979, a study conducted by Ehrhardt et al. retrospectively examined childhood behavioral patterns of 30 adults; 15 identified as lesbian women and 15 identified as transmen. All 30 adults had been assigned female at birth, and, as children, all were regarded as “tomboys.” The study found several key factors that distinguished the two cohorts. The goal of this study was to replicate and extend the 1979 study, utilizing a larger sample size and including a reference group of heterosexual women. Given the major social, technological, medical, and legal paradigm shifts that have occurred over the past four decades, we sought to determine if the previous findings still differentiate the cohorts. In light of the exponential rise in the number of gender diverse and dysphoric youth who request treatment, providing optimal, affirmative care and education is paramount, especially since many of these young people seek social and/or medical transition. Exploration of the early behavioral indices of the diverse trajectories may help to inform best practices for optimal care for these young people and their families.

Study Registration: Encouraging the Practice of Hypothetical-Deductive Research in the Journal.

Abstract: Earlier this year, we shared with you our commitment to supporting the dissemination of research that is well designed, carefully conducted, and properly interpreted, and our belief that authors, reviewers, editors, publishers, and readers should jointly strive to ensure the integrity of the science that we publish.1 Toward this end, we are pleased to announce a new submission type beginning in 2019: Registered Reports.