Publications by authors named "Janita Bralten"

46 Publications

Potential role for immune-related genes in autism spectrum disorders: Evidence from genome-wide association meta-analysis of autistic traits.

Autism 2021 Aug 4:13623613211019547. Epub 2021 Aug 4.

Radboud University Medical Center, The Netherlands.

Lay Abstract: Autism spectrum disorders are complex, with a strong genetic basis. Genetic research in autism spectrum disorders is limited by the fact that these disorders are largely heterogeneous so that patients are variable in their clinical presentations. To address this limitation, we investigated the genetics of individual dimensions of the autism spectrum disorder phenotypes, or autistic-like traits. These autistic-like traits are continuous variations in autistic behaviours that occur in the general population. Therefore, we meta-analysed data from four different population cohorts in which autistic-like traits were measured. We performed a set of genetic analyses to identify common variants for autistic-like traits, understand how these variants related to autism spectrum disorders, and how they contribute to neurobiological processes. Our results showed genetic associations with specific autistic-like traits and a link to the immune system. We offer an example of the potential to use a dimensional approach when dealing with heterogeneous, complex disorder like autism spectrum disorder. Decomposing the complex autism spectrum disorder phenotype in its core features can inform on the specific biology of these features which is likely to account to clinical variability in patients.
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http://dx.doi.org/10.1177/13623613211019547DOI Listing
August 2021

Genetic underpinnings of sociability in the general population.

Neuropsychopharmacology 2021 08 30;46(9):1627-1634. Epub 2021 May 30.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.
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http://dx.doi.org/10.1038/s41386-021-01044-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280100PMC
August 2021

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets.

J Child Psychol Psychiatry 2021 Oct 22;62(10):1202-1219. Epub 2021 Mar 22.

Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA.

Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
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http://dx.doi.org/10.1111/jcpp.13396DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455726PMC
October 2021

Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits.

Biol Psychiatry 2021 06 9;89(12):1127-1137. Epub 2021 Jan 9.

Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.

Background: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits.

Methods: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (r < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations.

Results: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although <1 for educational attainment and risk-taking behavior. We identified 4 genes with significant sex-differentiated effects across 3 traits. Several trait pairs shared sex-differentiated effects. The top genes with sex-differentiated effects were enriched for multiple gene sets, including neuron- and synapse-related sets. Most between-trait genetic correlation estimates were not significantly different between sexes, with exceptions (educational attainment and risk-taking behavior).

Conclusions: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.
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http://dx.doi.org/10.1016/j.biopsych.2020.12.024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163257PMC
June 2021

Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder.

Transl Psychiatry 2021 02 2;11(1):91. Epub 2021 Feb 2.

Genetics and Genome Biology Hospital for Sick Children, Toronto, Canada.

Using a novel trait-based measure, we examined genetic variants associated with obsessive-compulsive (OC) traits and tested whether OC traits and obsessive-compulsive disorder (OCD) shared genetic risk. We conducted a genome-wide association analysis (GWAS) of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of all currently available OCD cases. Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. A locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p = 2.48 × 10). rs7856850 was also associated with OCD in a meta-analysis of OCD case/control genome-wide datasets (p = 0.0069). The direction of effect was the same as in the community sample. Polygenic risk scores from OC traits were significantly associated with OCD in case/control datasets and vice versa (p's < 0.01). OC traits were highly, but not significantly, genetically correlated with OCD (r = 0.71, p = 0.062). We report the first validated genome-wide significant variant for OC traits in PTPRD, downstream of the most significant locus in a previous OCD GWAS. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the feasibility and power of using trait-based approaches in community samples for genetic discovery.
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http://dx.doi.org/10.1038/s41398-020-01121-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870035PMC
February 2021

Ten years of enhancing neuro-imaging genetics through meta-analysis: An overview from the ENIGMA Genetics Working Group.

Hum Brain Mapp 2020 Dec 10. Epub 2020 Dec 10.

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, California, USA.

Here we review the motivation for creating the enhancing neuroimaging genetics through meta-analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting "candidate gene" and genome-wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases.
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http://dx.doi.org/10.1002/hbm.25311DOI Listing
December 2020

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area.

Cereb Cortex 2021 03;31(4):1873-1887

Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.
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http://dx.doi.org/10.1093/cercor/bhaa327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945014PMC
March 2021

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
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http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups.

Am J Psychiatry 2020 09 16;177(9):834-843. Epub 2020 Jun 16.

The full list of authors in the ENIGMA working groups, author affiliations, author disclosures, and acknowledgments are provided in online supplements.

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

Methods: Structural T-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).

Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.

Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
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http://dx.doi.org/10.1176/appi.ajp.2020.19030331DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296070PMC
September 2020

Shared genetic etiology between obsessive-compulsive disorder, obsessive-compulsive symptoms in the population, and insulin signaling.

Transl Psychiatry 2020 04 27;10(1):121. Epub 2020 Apr 27.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Obsessive-compulsive symptoms (OCS) in the population have been linked to obsessive-compulsive disorder (OCD) in genetic and epidemiological studies. Insulin signaling has been implicated in OCD. We extend previous work by assessing genetic overlap between OCD, population-based OCS, and central nervous system (CNS) and peripheral insulin signaling. We conducted genome-wide association studies (GWASs) in the population-based Philadelphia Neurodevelopmental Cohort (PNC, 650 children and adolescents) of the total OCS score and six OCS factors from an exploratory factor analysis of 22 questions. Subsequently, we performed polygenic risk score (PRS)-based analysis to assess shared genetic etiologies between clinical OCD (using GWAS data from the Psychiatric Genomics Consortium), the total OCS score and OCS factors. We then performed gene-set analyses with a set of OCD-linked genes centered around CNS insulin-regulated synaptic function and PRS-based analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5,047 children and adolescents). In the PNC, we found a significant shared genetic etiology between OCD and 'guilty taboo thoughts'. In the Spit for Science cohort, we additionally observed genetic sharing between 'symmetry/counting/ordering' and 'contamination/cleaning'. The CNS insulin-linked gene-set also associated with 'symmetry/counting/ordering' in the PNC. Further, we identified genetic sharing between peripheral insulin signaling-related traits: type 2 diabetes with 'aggressive taboo thoughts', and levels of fasting insulin and 2 h glucose with OCD. In conclusion, OCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.
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http://dx.doi.org/10.1038/s41398-020-0793-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186226PMC
April 2020

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Transl Psychiatry 2020 03 20;10(1):100. Epub 2020 Mar 20.

Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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http://dx.doi.org/10.1038/s41398-020-0705-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083923PMC
March 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Social and non-social autism symptoms and trait domains are genetically dissociable.

Commun Biol 2019 3;2:328. Epub 2019 Sep 3.

1Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK.

The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, though this hypothesis has not yet been tested using molecular genetics. We test this using a genome-wide association study ( = 51,564) of a non-social trait related to autism, systemising, defined as the drive to analyse and build systems. We demonstrate that systemising is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemising. Supporting this, polygenic scores for systemising are significantly and positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
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http://dx.doi.org/10.1038/s42003-019-0558-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722082PMC
April 2020

ADHD symptoms in the adult general population are associated with factors linked to ADHD in adult patients.

Eur Neuropsychopharmacol 2019 10 1;29(10):1117-1126. Epub 2019 Aug 1.

Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands. Electronic address:

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder in children and adults. It is characterized by inappropriate levels of inattention (IA) and/or hyperactivity and impulsivity (HI). The ADHD diagnosis is hypothesized to represent the extreme of a continuous distribution of ADHD symptoms in the general population. In this study, we investigated whether factors linked to adult ADHD as a disorder are associated with adult ADHD symptoms in the general population. Our population-based sample included 4987 adults (mean age 56.1 years; 53.8% female) recruited by the Nijmegen Biomedical Study (NBS). Participants completed the Dutch ADHD DSM-IV Rating Scale for current and childhood ADHD symptoms, the Symptom Check List-90-R (SCL-90-R) anxiety subscale, and the Eysenk Personality Questionnaire (EPQR-S). Partial Spearman correlation and Hurdle negative binomial regression analysis were used to assess how age, sex, childhood ADHD symptoms, anxiety symptoms, and personality traits (neuroticism, extraversion, and psychoticism) are associated with current IA and HI symptoms. Increasing age was associated with a lower proportion of participants reporting HI symptoms and with reduced levels of HI; IA levels remained fairly stable over the age-range, but the probability of reporting IA symptoms increased throughout middle/late adulthood. Females were more likely to report IA symptoms than males. Childhood ADHD symptoms, neuroticism, and psychoticism were positively associated with current IA and HI symptoms, while extraversion had an opposite association with these symptom domains. Anxiety symptoms affected HI symptoms in females. Our results indicate that factors associated with categorical ADHD are also correlated with ADHD symptoms in the adult population.
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http://dx.doi.org/10.1016/j.euroneuro.2019.07.136DOI Listing
October 2019

Linked anatomical and functional brain alterations in children with attention-deficit/hyperactivity disorder.

Neuroimage Clin 2019 4;23:101851. Epub 2019 May 4.

Peking University Sixth Hospital, Institute of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing 100191, China. Electronic address:

Objectives: Neuroimaging studies have independently demonstrated brain anatomical and functional impairments in participants with ADHD. The aim of the current study was to explore the relationship between structural and functional brain alterations in ADHD through an integrated analysis of multimodal neuroimaging data.

Methods: We performed a multimodal analysis to integrate resting-state functional magnetic resonance imaging (MRI), structural MRI, and diffusion-weighted imaging data in a large, single-site sample of children with and without diagnosis for ADHD. The inferred subject contributions were fed into regression models to investigate the relationships between diagnosis, symptom severity, gender, and age.

Results: Compared with controls, children with ADHD diagnosis showed altered white matter microstructure in widespread white matter fiber tracts as well as greater gray matter volume (GMV) in bilateral frontal regions, smaller GMV in posterior regions, and altered functional connectivity (FC) in default mode and fronto-parietal networks. Age-related growth of GMV of bilateral occipital lobe, FC in frontal regions as well as age-related decline of GMV in medial regions seen in controls appeared reversed in children with ADHD. In the whole group, higher symptom severity was related to smaller GMV in widespread regions in bilateral frontal, parietal, and temporal lobes, as well as greater GMV in intracalcarine and temporal cortices.

Conclusions: Through a multimodal analysis approach we show that structural and functional alterations in brain regions known to be altered in subjects with ADHD from unimodal studies are linked across modalities. The brain alterations were related to clinical features of ADHD, including disorder status, age, and symptom severity.
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http://dx.doi.org/10.1016/j.nicl.2019.101851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514365PMC
March 2020

Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples.

Am J Psychiatry 2019 07 24;176(7):531-542. Epub 2019 Apr 24.

The Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands (Hoogman, Guimaraes, Shumskaya, Wolfers, Bralten, Franke); the Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Hoogman, Shumskaya, Mennes, Wolfers, Buitelaar, Bralten, Franke); the Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (Muetzel, El Marroun, White, Tiemeier); the Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (Muetzel); the Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition, and Behavior, Nijmegen, the Netherlands (Guimaraes, Zwiers, Buitelaar); the Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Calif. (Jahanshad, Thompson); National Human Genome Research Institute, Bethesda, Md. (Sudre, Shaw); the Department of Behavioral Neuroscience, Oregon Health and Science University, Portland (Earl, Fair, Nigg); the Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Cerdanyola del Vallès, Spain (Soliva Vila, Ramos-Quiroga, Vilarroya); Instituto ITACA, Polytechnic University of Valencia, Valencia, Spain (Vives-Gilabert); the Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, Conn. (Khadka, Novotny, Stevens); University of Groningen, University Medical Center Groningen (UMCG), Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, the Netherlands (Hartman, Schweren); Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam (Heslenfeld); the Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, the Netherlands (Hoekstra); NICHE Lab, Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, the Netherlands (Ambrosino, Oranje, de Zeeuw, Durston); Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil (Chaim-Avancini, Rosa, Zanetti, Busatto); the Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, São Paulo, Brazil (Chaim-Avancini, Rosa, Zanetti, Busatto); the Developmental Imaging Group, Murdoch Children's Research Institute, Melbourne, Australia (Malpas); the Clinical Outcomes Research Unit (CORe), Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia (Malpas); the Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia (Malpas); the Child Neuropsychology Section, University Hospital RWTH Aachen, Aachen, Germany (Kohls, Konrad; Child and Adolescent Psychiatry, University Hospital RWTH Aachen, Aachen, Germany (Polier, Seitz); Institute of Neuroscience and Medicine-Brain and Behavior (INM-7), Research Center Jülich, Jülich, Germany (Polier); the Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Department of Psychiatry, Massachusetts General Hospital, Boston (Biederman); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston (Biederman, Doyle); the Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston (Doyle); the Departments of Neurosciences, Radiology, and Psychiatry and the Center for Multimodal Imaging and Genetics, University of California San Diego (Dale); the Clinical and Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine (van Erp); the Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children's Hospital Medical Center, and the Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati (Epstein, Tamm); the Center for Human Development, University of California San Diego, San Diego (Jernigan); the Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany (Ziegler, Lesch); the Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam (Schrantee, Reneman); the Department of Clinical Medicine, University of Bergen, Bergen, Norway (Høvik); the Division of Psychiatry, Haukeland University Hospital, Bergen, Norway (Høvik, Haavik); the Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway (Lundervold); the K.G. Jebsen Center for Neuropsychiatric Disorders, Department of Biomedicine, University of Bergen, Bergen, Norway (Lundervold, Haavik); the School of Psychology and the Department of Psychiatry, School of Medicine, and the Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland (Kelly); the Department of Child and Adolescent Psychiatry, NYU Langone Medical Center, New York (Kelly, Castellanos, Yoncheva); the Department of Psychiatry, Trinity College Dublin, Ireland (McCarthy, Skokauskas, Frodl); the Centre for Advanced Medical Imaging, St. James's Hospital, Dublin, Ireland (McCarthy); the Center for Child and Adolescent Mental Health, NTNU, Norway, Norwegian University of Science and Technology, Norway (Skokauskas); the Center for MR Research, University Children's Hospital, and the Zurich Center for Integrative Human Physiology, Zurich (O'Gorman Tuura); Magnetic Resonance Image Core Facility, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain (Calvo, Lazaro); the Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain (Lera-Miguel, Nicolau, Lazaro); the Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Chantiluke, Christakou, Cubillo, Rubia); the School of Psychology and Clinical Language Sciences, Centre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, U.K. (Christakou); the Department of Paediatrics, University of Melbourne, Australia (Vance, Coghill, Silk); the Department of Neuroscience, Brighton and Sussex Medical School, Falmer, Brighton, U.K. (Cercignani, Gabel, Harrison); the Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Asherson, Kuntsi); the Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany (Baumeister, Brandeis, Hohmann, Banaschewski); the Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich (Brandeis, Brem, Walitza); the Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich (Brandeis, Brem, Walitza); the D'Or Institute for Research and Education, Rio de Janeiro (Bramati, Tovar-Moll, Mattos); the Morphological Sciences Program, Federal University of Rio de Janeiro, Rio de Janeiro (Tovar-Moll); the Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany (Fallgatter, Schwarz, Ethofer); LEAD Graduate School, University of Tübingen, Germany (Fallgatter); the Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany (Kardatzki, Ethofer); the National Medical Research Center for Children's Health, Department of Magnetic Resonance Imaging and Densitometry, Moscow (Anikin); the National Medical Research Center for Children's Health, Moscow (Baranov, Solovieva); Russian National Research Medical University, Ministry of Health and Social Development of the Russian Federation, Central Clinical Hospital MSHE, Moscow (Namazova-Baranova); the National Medical Research Center for Children's Health, Laboratory of Neurology and Cognitive Health, Moscow (Gogberashvili, Karkashadze); the National Medical Research Center for Children's Health, Department of Information Technologies, Moscow (Kapilushniy); the Department of Pediatrics, Erasmus MC-Sophia, Rotterdam, the Netherlands (El Marroun); the Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands (El Marroun); the Department of Radiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (White); Federal University of Rio de Janeiro, Rio de Janeiro (Mattos); the Department of Psychiatry, University of Melbourne, Melbourne, Australia (Coghill); the Murdoch Children's Research Institute, Melbourne, Australia (Coghill, Silk); the Division of Neuroscience, University of Dundee, Dundee, U.K. (Coghill); the Child and Adolescent Mental Health Center, Capital Region Copenhagen (Plessen); the Division of Child and Adolescent Psychiatry, Department of Psychiatry, University Hospital Lausanne, Switzerland (Plessen); the Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Mehta, Paloyelis); Sussex Partnership NHS Foundation Trust, Swandean, East Sussex, U.K. (Harrison); the Monash Institute for Cognitive and Clinical Neurosciences (MICCN) and the School of Psychological Sciences, Monash University, Melbourne, Australia (Bellgrove); Deakin University, School of Psychology, Geelong, Australia (Silk); the Department of Medicine, University of Barcelona, Barcelona, Spain (Lazaro); the Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Germany (Frodl); the German Center for Neurodegenerative Diseases (DZNE), Germany (Frodl); Bezirksklinikum Regensburg, Germany (Zentis); the Nathan Kline Institute for Psychiatric Research, Orangeburg, N.Y. (Castellanos); the Brain Imaging Center, Amsterdam University Medical Centers, Amsterdam (Reneman); the Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Tübingen, Germany (Conzelmann); the Department of Psychology, Biological Psychology, Clinical Psychology, and Psychotherapy, University of Würzburg, Würzburg, Germany (Conzelmann, Pauli, Baur-Streubel, Zierhut); the Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine, I.M. Sechenov First Moscow State Medical University, Moscow (Lesch); the Department of Neuroscience, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, the Netherlands (Lesch); the Department of Psychiatry, Psychosomatic Medicine, and Psychotherapy, University Hospital Frankfurt, Frankfurt, Germany (Reif); JARA Institute Molecular Neuroscience and Neuroimaging (INM-11), Institute for Neuroscience and Medicine, Research Center Jülich, Germany (Konrad); Translational Neuroscience, Child and Adolescent Psychiatry, University Hospital RWTH Aachen, Aachen, Germany (Oberwelland Weiss); Cognitive Neuroscience (INM-3), Institute for Neuroscience and Medicine, Research Center Jülich, Germany (Oberwelland Weiss); the Department of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil (Busatto, Louza); the Clinical Neuropsychology Section, Vrije Universiteit Amsterdam, Amsterdam (Oosterlaan); Emma Children's Hospital Amsterdam Medical Center, Amsterdam (Oosterlaan); the Department of Pediatrics, VU Medical Center, Amsterdam (Oosterlaan); the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Stevens); the Department of Psychiatry, Vall d'Hebron University Hospital, Barcelona, Spain (Ramos-Quiroga); Biomedical Network Research Center on Mental Health (CIBERSAM), Barcelona, Spain (Lazaro, Ramos-Quiroga); Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain (Vilarroya); the Department of Psychiatry, Oregon Health and Science University, Portland (Fair, Nigg); Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands (Buitelaar); Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York (Faraone); NIHM, Bethesda, Md. (Shaw); the Department of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston (Tiemeier).

Objective: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies.

Methods: Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707).

Results: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample.

Conclusions: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.
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http://dx.doi.org/10.1176/appi.ajp.2019.18091033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6879185PMC
July 2019

Genetic Markers of ADHD-Related Variations in Intracranial Volume.

Am J Psychiatry 2019 03;176(3):228-238

The Department of Human Genetics, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Klein, Bralten, Roth Mota, Arias-Vasquez, Franke); University Medical Center Utrecht, UMC Utrecht Brain Center, Department of Psychiatry, Utrecht, the Netherlands (Klein); the Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston (Walters, Neale); Program in Medical and Population Genetics (Walters) and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Mass (Walters, Neale); the Department of Biomedicine and the Center for Integrative Sequencing, Aarhus University, Aarhus, Denmark (Demontis, Mattheisen, Børglum); the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Denmark (Demontis, Børglum); the Department of Genetics and the Neuroscience Center, University of North Carolina, Chapel Hill (Stein); the Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles (Hibar, Thompson); the Department of Epidemiology and the Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands (Adams); the Department of Psychiatry and the Research Institute, Hospital for Sick Children, University of Toronto, Toronto (Schachar); the Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London (Sonuga-Barke); the Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany (Mattheisen); the Department of Clinical Neuroscience, Center for Psychiatric Research, Karolinska Institute, Stockholm (Mattheisen); Stockholm Health Care Services, Stockholm County Council, Stockholm (Mattheisen); the Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles (Thompson); the Quantitative Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia (Medland); the Department of Psychiatry and the Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, N.Y. (Faraone); the K.G. Jebsen Center for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway (Faraone); and the Department of Psychiatry, Donders Institute for Brain, Cognition, and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands (Roth Mota, Arias-Vasquez, Franke).

Objective: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology. Intracranial volume (ICV) and volumes of the nucleus accumbens, amygdala, caudate nucleus, hippocampus, and putamen are smaller in people with ADHD compared with healthy individuals. The authors investigated the overlap between common genetic variation associated with ADHD risk and these brain volume measures to identify underlying biological processes contributing to the disorder.

Methods: The authors combined genome-wide association results from the largest available studies of ADHD (N=55,374) and brain volumes (N=11,221-24,704), using a set of complementary methods to investigate overlap at the level of global common variant genetic architecture and at the single variant level.

Results: Analyses revealed a significant negative genetic correlation between ADHD and ICV (r=-0.22). Meta-analysis of single variants revealed two significant loci of interest associated with both ADHD risk and ICV; four additional loci were identified for ADHD and volumes of the amygdala, caudate nucleus, and putamen. Exploratory gene-based and gene-set analyses in the ADHD-ICV meta-analytic data showed association with variation in neurite outgrowth-related genes.

Conclusions: This is the first genome-wide study to show significant genetic overlap between brain volume measures and ADHD, both on the global and the single variant level. Variants linked to smaller ICV were associated with increased ADHD risk. These findings can help us develop new hypotheses about biological mechanisms by which brain structure alterations may be involved in ADHD disease etiology.
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http://dx.doi.org/10.1176/appi.ajp.2018.18020149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780894PMC
March 2019

Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Mol Psychiatry 2020 Mar;25(3):692-695

Department of Psychiatry and Mental Health, Anzio Road, 7925, Cape Town, South Africa.

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.
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http://dx.doi.org/10.1038/s41380-019-0358-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608381PMC
March 2020

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Mol Psychiatry 2020 03 3;25(3):584-602. Epub 2018 Oct 3.

Department of Psychiatry and Mental Health, Anzio Road, 7925, Cape Town, South Africa.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10, 1.7 × 10, 3.5 × 10 and 1.0 × 10, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.
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http://dx.doi.org/10.1038/s41380-018-0118-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042770PMC
March 2020

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes.

Mol Psychiatry 2020 11 2;25(11):3053-3065. Epub 2018 Oct 2.

NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.
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http://dx.doi.org/10.1038/s41380-018-0262-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445783PMC
November 2020

Pleiotropic Contribution of and to Aggression and Subcortical Brain Volumes.

Front Behav Neurosci 2018 3;12:61. Epub 2018 Apr 3.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands.

Reactive and proactive subtypes of aggression have been recognized to help parse etiological heterogeneity of this complex phenotype. With a heritability of about 50%, genetic factors play a role in the development of aggressive behavior. Imaging studies implicate brain structures related to social behavior in aggression etiology, most notably the amygdala and striatum. This study aimed to gain more insight into the pathways from genetic risk factors for aggression to aggression phenotypes. To this end, we conducted genome-wide gene-based cross-trait meta-analyses of aggression with the volumes of amygdala, nucleus accumbens and caudate nucleus to identify genes influencing both aggression and aggression-related brain volumes. We used data of large-scale genome-wide association studies (GWAS) of: (a) aggressive behavior in children and adolescents (EAGLE, = 18,988); and (b) Magnetic Resonance Imaging (MRI)-based volume measures of aggression-relevant subcortical brain regions (ENIGMA2, = 13,171). Second, the identified genes were further investigated in a sample of healthy adults (mean age (SD) = 25.28 (4.62) years; 43% male) who had genome-wide genotyping data and questionnaire data on aggression subtypes available (Brain Imaging Genetics, BIG, = 501) to study their effect on reactive and proactive subtypes of aggression. Our meta-analysis identified two genes, and , significantly associated with both aggression risk and nucleus accumbens and amygdala brain volume. Subsequent in-depth analysis of these genes in healthy adults (BIG), including sex as an interaction term in the model, revealed no significant subtype-specific gene-wide associations. Using cross-trait meta-analysis of brain measures and psychiatric phenotypes, this study generated new hypotheses about specific links between genes, the brain and behavior. Results indicate that and may exert an effect on aggression through mechanisms involving nucleus accumbens and amygdala volumes, respectively.
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http://dx.doi.org/10.3389/fnbeh.2018.00061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891600PMC
April 2018

Monoamine and neuroendocrine gene-sets associate with frustration-based aggression in a gender-specific manner.

Eur Neuropsychopharmacol 2020 01 27;30:75-86. Epub 2017 Nov 27.

Radboud university medical center, Department of Human Genetics (855); PO Box 9101, 6500 HB Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands; Department of Psychiatry, Radboud university medical center, Nijmegen, The Netherlands.

Investigating phenotypic heterogeneity in aggression and understanding the molecular biological basis of aggression subtypes may lead to new prevention and treatment options. In the current study, we evaluated the taxonomy of aggression and examined specific genetic mechanisms underlying aggression subtypes in healthy males and females. Confirmatory Factor Analysis (CFA) was used to replicate a recently reported three-factor model of the Reactive Proactive Questionnaire (RPQ) in healthy adults (n = 661; median age 24.0 years; 41% male). Gene-set association analysis, aggregating common genetic variants within (a combination of) three molecular pathways previously implicated in aggression, i.e. serotonergic, dopaminergic, and neuroendocrine signaling, was conducted with MAGMA software in males and females separately (total n = 395) for aggression subtypes. We replicate the three-factor CFA model of the RPQ, and found males to score significantly higher on one of these factors compared to females: proactive aggression. The genetic association analysis showed a female-specific association of genetic variation in the combined gene-set with a different factor of the RPQ; reactive aggression due to internal frustration. Both the neuroendocrine and serotonergic gene-sets contributed significantly to this association. Our genetic findings are subtype- and sex-specific, stressing the value of efforts to reduce heterogeneity in research of aggression etiology. Importantly, subtype- and sex-differences in the underlying pathophysiology of aggression suggest that optimal treatment options will have to be tailored to the individual patient. Male and female needs of intervention might differ, stressing the need for sex-specific further research of aggression. Our work highlights opportunities for sample size maximization offered by population-based studies of aggression.
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http://dx.doi.org/10.1016/j.euroneuro.2017.11.016DOI Listing
January 2020

Verbal working memory-related functional connectivity alterations in boys with attention-deficit/hyperactivity disorder and the effects of methylphenidate.

J Psychopharmacol 2017 08 28;31(8):1061-1069. Epub 2017 Jun 28.

1 Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.

Objective: Few studies have investigated verbal working memory-related functional connectivity patterns in participants with attention-deficit/hyperactivity disorder (ADHD). Thus, we aimed to compare working memory-related functional connectivity patterns in healthy children and those with ADHD, and study effects of methylphenidate (MPH).

Method: Twenty-two boys with ADHD were scanned twice, under either MPH (single dose, 10 mg) or placebo, in a randomised, cross-over, counterbalanced placebo-controlled design. Thirty healthy boys were scanned once. We used fMRI during a numerical n-back task to examine functional connectivity patterns in case-control and MPH-placebo comparisons, using independent component analysis.

Results: There was no significant difference in behavioural performance between children with ADHD, treated with MPH or placebo, and healthy controls. Compared with controls, participants with ADHD under placebo showed increased functional connectivity within fronto-parietal and auditory networks, and decreased functional connectivity within the executive control network. MPH normalized the altered functional connectivity pattern and significantly enhanced functional connectivity within the executive control network, though in non-overlapping areas.

Conclusion: Our study contributes to the identification of the neural substrates of working memory. Single dose of MPH normalized the altered brain functional connectivity network, but had no enhancing effect on (non-impaired) behavioural performance.
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http://dx.doi.org/10.1177/0269881117715607DOI Listing
August 2017

Female-specific association of NOS1 genotype with white matter microstructure in ADHD patients and controls.

J Child Psychol Psychiatry 2017 Aug 7;58(8):958-966. Epub 2017 Jun 7.

Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.

Background: The nitric oxide synthase gene (NOS1) exon 1f (ex1f) VNTR is a known genetic risk factor for Attention-Deficit/Hyperactivity Disorder (ADHD), particularly in females. NOS1 plays an important role in neurite outgrowth and may thus influence brain development, specifically white matter (WM) microstructure, which is known to be altered in ADHD. The current study aimed to investigate whether NOS1 is associated with WM microstructure in (female) individuals with and without ADHD.

Methods: Diffusion Tensor Imaging (DTI) scans were collected from 187 participants with ADHD (33% female) and 103 controls (50% female), aged 8-26 years, and NOS1-ex1f VNTR genotype was determined. Whole-brain analyses were conducted for fractional anisotropy (FA) and mean diffusivity (MD) to examine associations between NOS1 and WM microstructure, including possible interactions with gender and diagnosis.

Results: Consistent with previous literature, NOS1-ex1f was associated with total ADHD and hyperactivity-impulsivity symptoms, but not inattention; this effect was independent of gender. NOS1-ex1f was also associated with MD values in several major WM tracts in females, but not males. In females, homozygosity for the short allele was linked to higher MD values than carriership of the long allele. MD values in these regions did not correlate with ADHD symptoms. Results were similar for participants with and without ADHD.

Conclusions: NOS1-ex1f VNTR is associated with WM microstructure in females in a large sample of participants with ADHD and healthy controls. Whether this association is part of a neurodevelopmental pathway from NOS1 to ADHD symptoms should be further investigated in future studies.
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http://dx.doi.org/10.1111/jcpp.12742DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513773PMC
August 2017

Predicting brain structure in population-based samples with biologically informed genetic scores for schizophrenia.

Am J Med Genet B Neuropsychiatr Genet 2017 Apr;174(3):324-332

Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.

Schizophrenia is associated with brain structural abnormalities including gray and white matter volume reductions. Whether these alterations are caused by genetic risk variants for schizophrenia is unclear. Previous attempts to detect associations between polygenic factors for schizophrenia and structural brain phenotypes in healthy subjects have been negative or remain non-replicated. In this study, we used genetic risk scores that were based on the accumulated effect of selected risk variants for schizophrenia belonging to specific biological systems like synaptic function, neurodevelopment, calcium signaling, and glutamatergic neurotransmission. We hypothesized that this "biologically informed" approach would provide the missing link between genetic risk for schizophrenia and brain structural phenotypes. We applied whole-brain voxel-based morphometry (VBM) analyses in two population-based target samples and subsequent regions of interest (ROIs) analyses in an independent replication sample (total N = 2725). No consistent association between the genetic scores and brain volumes were observed in the investigated samples. These results suggest that in healthy subjects with a higher genetic risk for schizophrenia additional factors apart from common genetic variants (e.g., infection, trauma, rare genetic variants, or gene-gene interactions) are required to induce structural abnormalities of the brain. Further studies are recommended to test for possible gene-gene or gene-environment effects. © 2017 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/ajmg.b.32519DOI Listing
April 2017

Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis.

Lancet Psychiatry 2017 04 16;4(4):310-319. Epub 2017 Feb 16.

Department of Cognitive Science, UC San Diego, La Jolla, CA, USA.

Background: Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis.

Methods: In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156.

Findings: Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5).

Interpretation: With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes.

Funding: National Institutes of Health.
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http://dx.doi.org/10.1016/S2215-0366(17)30049-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5933934PMC
April 2017

Novel genetic loci associated with hippocampal volume.

Nat Commun 2017 01 18;8:13624. Epub 2017 Jan 18.

Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
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http://dx.doi.org/10.1038/ncomms13624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253632PMC
January 2017

Decreased Left Caudate Volume Is Associated with Increased Severity of Autistic-Like Symptoms in a Cohort of ADHD Patients and Their Unaffected Siblings.

PLoS One 2016 2;11(11):e0165620. Epub 2016 Nov 2.

Radboud UMC, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, The Netherlands.

Autism spectrum disorder (ASD) symptoms frequently occur in individuals with attention-deficit/hyperactivity disorder (ADHD). While there is evidence that both ADHD and ASD have differential structural brain correlates, knowledge of the structural brain profile of individuals with ADHD with raised ASD symptoms is limited. The presence of ASD-like symptoms was measured by the Children's Social Behavior Questionnaire (CSBQ) in a sample of typically developing controls (n = 154), participants with ADHD (n = 239), and their unaffected siblings (n = 144) between the ages of 8 and 29. Structural magnetic resonance imaging (MRI) correlates of ASD ratings were analysed by studying the relationship between ASD ratings and grey matter volumes using mixed effects models which controlled for ADHD symptom count and total brain volume. ASD ratings were significantly elevated in participants with ADHD relative to controls and unaffected siblings. For the entire group (participants with ADHD, unaffected siblings and TD controls), mixed effect models revealed that the left caudate nucleus volume was negatively correlated with ASD ratings (t = 2.83; P = 0.005). The current findings are consistent with the role of the caudate nucleus in executive function, including the selection of goals based on the evaluation of action outcomes and the use of social reward to update reward representations. There is a specific volumetric profile associated with subclinical ASD-like symptoms in participants with ADHD, unaffected siblings and controls with the caudate nucleus and globus pallidus being of critical importance in predicting the level of ASD-like symptoms in all three groups.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165620PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091763PMC
June 2017

Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Nat Neurosci 2016 12 3;19(12):1569-1582. Epub 2016 Oct 3.

Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht, the Netherlands.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.
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http://dx.doi.org/10.1038/nn.4398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227112PMC
December 2016
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