Search

Your search keyword '"Hibar, Derrek P"' showing total 47 results
Start Over Author "Hibar, Derrek P" Topic magnetic resonance imaging
47 results on '"Hibar, Derrek P"'

1. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

Author

Sønderby IE, Ching CRK, Thomopoulos SI, van der Meer D, Sun D, Villalon-Reina JE, Agartz I, Amunts K, Arango C, Armstrong NJ, Ayesa-Arriola R, Bakker G, Bassett AS, Boomsma DI, Bülow R, Butcher NJ, Calhoun VD, Caspers S, Chow EWC, Cichon S, Ciufolini S, Craig MC, Crespo-Facorro B, Cunningham AC, Dale AM, Dazzan P, de Zubicaray GI, Djurovic S, Doherty JL, Donohoe G, Draganski B, Durdle CA, Ehrlich S, Emanuel BS, Espeseth T, Fisher SE, Ge T, Glahn DC, Grabe HJ, Gur RE, Gutman BA, Haavik J, Håberg AK, Hansen LA, Hashimoto R, Hibar DP, Holmes AJ, Hottenga JJ, Hulshoff Pol HE, Jalbrzikowski M, Knowles EEM, Kushan L, Linden DEJ, Liu J, Lundervold AJ, Martin-Brevet S, Martínez K, Mather KA, Mathias SR, McDonald-McGinn DM, McRae AF, Medland SE, Moberget T, Modenato C, Monereo Sánchez J, Moreau CA, Mühleisen TW, Paus T, Pausova Z, Prieto C, Ragothaman A, Reinbold CS, Reis Marques T, Repetto GM, Reymond A, Roalf DR, Rodriguez-Herreros B, Rucker JJ, Sachdev PS, Schmitt JE, Schofield PR, Silva AI, Stefansson H, Stein DJ, Tamnes CK, Tordesillas-Gutiérrez D, Ulfarsson MO, Vajdi A, van 't Ent D, van den Bree MBM, Vassos E, Vázquez-Bourgon J, Vila-Rodriguez F, Walters GB, Wen W, Westlye LT, Wittfeld K, Zackai EH, Stefánsson K, Jacquemont S, Thompson PM, Bearden CE, and Andreassen OA

Subjects
Humans, Multicenter Studies as Topic, Brain diagnostic imaging, Brain growth & development, Brain pathology, DNA Copy Number Variations, Magnetic Resonance Imaging, Mental Disorders diagnostic imaging, Mental Disorders genetics, Mental Disorders pathology, Neurodevelopmental Disorders diagnostic imaging, Neurodevelopmental Disorders genetics, Neurodevelopmental Disorders pathology, Neuroimaging
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2022
Full Text
View/download PDF

2. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group.

Author

Ching CRK, Hibar DP, Gurholt TP, Nunes A, Thomopoulos SI, Abé C, Agartz I, Brouwer RM, Cannon DM, de Zwarte SMC, Eyler LT, Favre P, Hajek T, Haukvik UK, Houenou J, Landén M, Lett TA, McDonald C, Nabulsi L, Patel Y, Pauling ME, Paus T, Radua J, Soeiro-de-Souza MG, Tronchin G, van Haren NEM, Vieta E, Walter H, Zeng LL, Alda M, Almeida J, Alnaes D, Alonso-Lana S, Altimus C, Bauer M, Baune BT, Bearden CE, Bellani M, Benedetti F, Berk M, Bilderbeck AC, Blumberg HP, Bøen E, Bollettini I, Del Mar Bonnin C, Brambilla P, Canales-Rodríguez EJ, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, Dima D, Duchesnay É, Elvsåshagen T, Fears SC, Frangou S, Fullerton JM, Glahn DC, Goikolea JM, Green MJ, Grotegerd D, Gruber O, Haarman BCM, Henry C, Howells FM, Ives-Deliperi V, Jansen A, Kircher TTJ, Knöchel C, Kramer B, Lafer B, López-Jaramillo C, Machado-Vieira R, MacIntosh BJ, Melloni EMT, Mitchell PB, Nenadic I, Nery F, Nugent AC, Oertel V, Ophoff RA, Ota M, Overs BJ, Pham DL, Phillips ML, Pineda-Zapata JA, Poletti S, Polosan M, Pomarol-Clotet E, Pouchon A, Quidé Y, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Schene AH, Sim K, Soares JC, Stäblein M, Stein DJ, Tamnes CK, Thomaidis GV, Upegui CV, Veltman DJ, Wessa M, Westlye LT, Whalley HC, Wolf DH, Wu MJ, Yatham LN, Zarate CA, Thompson PM, and Andreassen OA

Subjects
Humans, Meta-Analysis as Topic, Multicenter Studies as Topic, Bipolar Disorder diagnostic imaging, Bipolar Disorder pathology, Cerebral Cortex diagnostic imaging, Cerebral Cortex pathology, Magnetic Resonance Imaging, Neuroimaging
Abstract

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2022
Full Text
View/download PDF

3. Cortical Abnormalities Associated With Pediatric and Adult Obsessive-Compulsive Disorder: Findings From the ENIGMA Obsessive-Compulsive Disorder Working Group.

Author

Boedhoe PSW, Schmaal L, Abe Y, Alonso P, Ameis SH, Anticevic A, Arnold PD, Batistuzzo MC, Benedetti F, Beucke JC, Bollettini I, Bose A, Brem S, Calvo A, Calvo R, Cheng Y, Cho KIK, Ciullo V, Dallaspezia S, Denys D, Feusner JD, Fitzgerald KD, Fouche JP, Fridgeirsson EA, Gruner P, Hanna GL, Hibar DP, Hoexter MQ, Hu H, Huyser C, Jahanshad N, James A, Kathmann N, Kaufmann C, Koch K, Kwon JS, Lazaro L, Lochner C, Marsh R, Martínez-Zalacaín I, Mataix-Cols D, Menchón JM, Minuzzi L, Morer A, Nakamae T, Nakao T, Narayanaswamy JC, Nishida S, Nurmi E, O'Neill J, Piacentini J, Piras F, Piras F, Reddy YCJ, Reess TJ, Sakai Y, Sato JR, Simpson HB, Soreni N, Soriano-Mas C, Spalletta G, Stevens MC, Szeszko PR, Tolin DF, van Wingen GA, Venkatasubramanian G, Walitza S, Wang Z, Yun JY, Thompson PM, Stein DJ, and van den Heuvel OA

Subjects
Adolescent, Adult, Age of Onset, Cerebral Cortex drug effects, Child, Frontal Lobe abnormalities, Frontal Lobe diagnostic imaging, Frontal Lobe drug effects, Humans, Obsessive-Compulsive Disorder drug therapy, Parietal Lobe abnormalities, Parietal Lobe diagnostic imaging, Parietal Lobe drug effects, Reference Values, Temporal Lobe abnormalities, Temporal Lobe diagnostic imaging, Temporal Lobe drug effects, Young Adult, Cerebral Cortex abnormalities, Cerebral Cortex diagnostic imaging, Magnetic Resonance Imaging, Obsessive-Compulsive Disorder diagnostic imaging
Abstract

Objective: Brain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken., Method: T 1 -weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using FreeSurfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume., Results: In adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortex and a thinner inferior parietal cortex. Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showed significant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from -0.10 to -0.33., Conclusions: The parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were found in medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication.

Published
2018
Full Text
View/download PDF

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

Author

Hoogman M, Bralten J, Hibar DP, Mennes M, Zwiers MP, Schweren LSJ, van Hulzen KJE, Medland SE, Shumskaya E, Jahanshad N, Zeeuw P, Szekely E, Sudre G, Wolfers T, Onnink AMH, Dammers JT, Mostert JC, Vives-Gilabert Y, Kohls G, Oberwelland E, Seitz J, Schulte-Rüther M, Ambrosino S, Doyle AE, Høvik MF, Dramsdahl M, Tamm L, van Erp TGM, Dale A, Schork A, Conzelmann A, Zierhut K, Baur R, McCarthy H, Yoncheva YN, Cubillo A, Chantiluke K, Mehta MA, Paloyelis Y, Hohmann S, Baumeister S, Bramati I, Mattos P, Tovar-Moll F, Douglas P, Banaschewski T, Brandeis D, Kuntsi J, Asherson P, Rubia K, Kelly C, Martino AD, Milham MP, Castellanos FX, Frodl T, Zentis M, Lesch KP, Reif A, Pauli P, Jernigan TL, Haavik J, Plessen KJ, Lundervold AJ, Hugdahl K, Seidman LJ, Biederman J, Rommelse N, Heslenfeld DJ, Hartman CA, Hoekstra PJ, Oosterlaan J, Polier GV, Konrad K, Vilarroya O, Ramos-Quiroga JA, Soliva JC, Durston S, Buitelaar JK, Faraone SV, Shaw P, Thompson PM, and Franke B

Subjects
Adolescent, Adult, Attention Deficit Disorder with Hyperactivity physiopathology, Brain physiopathology, Case-Control Studies, Child, Child, Preschool, Cross-Sectional Studies, Female, Humans, Linear Models, Longitudinal Studies, Male, Middle Aged, Neuroimaging, Young Adult, Attention Deficit Disorder with Hyperactivity pathology, Brain pathology, Magnetic Resonance Imaging
Abstract

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., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Published
2017
Full Text
View/download PDF

5. Genetic clustering on the hippocampal surface for genome-wide association studies.

Author

Hibar DP, Medland SE, Stein JL, Kim S, Shen L, Saykin AJ, de Zubicaray GI, McMahon KL, Montgomery GW, Martin NG, Wright MJ, Djurovic S, Agartz IA, Andreassen OA, and Thompson PM

Subjects
Adult, Aged, Female, Genetic Predisposition to Disease genetics, Humans, Image Interpretation, Computer-Assisted methods, Male, Reproducibility of Results, Sensitivity and Specificity, Cognitive Dysfunction genetics, Cognitive Dysfunction pathology, Genome-Wide Association Study methods, Hippocampus pathology, Hippocampus physiopathology, Magnetic Resonance Imaging methods, Multigene Family genetics
Abstract

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Published
2013
Full Text
View/download PDF

6. Exhaustive search of the SNP-sNP interactome identifies epistatic effects on brain volume in two cohorts.

Author

Hibar DP, Stein JL, Jahanshad N, Kohannim O, Toga AW, McMahon KL, de Zubicaray GI, Montgomery GW, Martin NG, Wright MJ, Weiner MW, and Thompson PM

Subjects
Algorithms, Cohort Studies, Epistasis, Genetic genetics, Genetic Predisposition to Disease genetics, Humans, Organ Size, Alzheimer Disease genetics, Alzheimer Disease pathology, Brain pathology, Chromosome Mapping methods, Connectome methods, Magnetic Resonance Imaging methods, Polymorphism, Single Nucleotide genetics
Abstract

The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

Published
2013
Full Text
View/download PDF

7. Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans.

Author

Hua X, Hibar DP, Lee S, Toga AW, Jack CR Jr, Weiner MW, and Thompson PM

Subjects
Age Factors, Aged, Aged, 80 and over, Atrophy, Female, Follow-Up Studies, Humans, Longitudinal Studies, Male, Middle Aged, Prospective Studies, Alzheimer Disease pathology, Cognition Disorders pathology, Disease Progression, Magnetic Resonance Imaging methods, Sex Characteristics
Abstract

We set out to determine factors that influence the rate of brain atrophy in 1-year longitudinal magnetic resonance imaging (MRI) data. With tensor-based morphometry (TBM), we mapped the 3-dimensional profile of progressive atrophy in 144 subjects with probable Alzheimer's disease (AD) (age: 76.5 +/- 7.4 years), 338 with amnestic mild cognitive impairment (MCI; 76.0 +/- 7.2), and 202 healthy controls (77.0 +/- 5.1), scanned twice, 1 year apart. Statistical maps revealed significant age and sex differences in atrophic rates. Brain atrophic rates were about 1%-1.5% faster in women than men. Atrophy was faster in younger than older subjects, most prominently in mild cognitive impairment, with a 1% increase in the rates of atrophy and 2% in ventricular expansion, for every 10-year decrease in age. TBM-derived atrophic rates correlated with reduced beta-amyloid and elevated tau levels (n = 363) at baseline, baseline and progressive deterioration in clinical measures, and increasing numbers of risk alleles for the ApoE4 gene. TBM is a sensitive, high-throughput biomarker for tracking disease progression in large imaging studies; sub-analyses focusing on women or younger subjects gave improved sample size requirements for clinical trials., (2010 Elsevier Inc. All rights reserved.)

Published
2010
Full Text
View/download PDF

8. Mapping Alzheimer's disease progression in 1309 MRI scans: power estimates for different inter-scan intervals.

Author

Hua X, Lee S, Hibar DP, Yanovsky I, Leow AD, Toga AW, Jack CR Jr, Bernstein MA, Reiman EM, Harvey DJ, Kornak J, Schuff N, Alexander GE, Weiner MW, and Thompson PM

Subjects
Aged, Cognition Disorders pathology, Databases, Factual, Female, Humans, Imaging, Three-Dimensional methods, Longitudinal Studies, Male, Temporal Lobe pathology, Time Factors, Alzheimer Disease pathology, Brain pathology, Brain Mapping methods, Disease Progression, Magnetic Resonance Imaging methods
Abstract

Neuroimaging centers and pharmaceutical companies are working together to evaluate treatments that might slow the progression of Alzheimer's disease (AD), a common but devastating late-life neuropathology. Recently, automated brain mapping methods, such as tensor-based morphometry (TBM) of structural MRI, have outperformed cognitive measures in their precision and power to track disease progression, greatly reducing sample size estimates for drug trials. In the largest TBM study to date, we studied how sample size estimates for tracking structural brain changes depend on the time interval between the scans (6-24 months). We analyzed 1309 brain scans from 91 probable AD patients (age at baseline: 75.4+/-7.5 years) and 189 individuals with mild cognitive impairment (MCI; 74.6+/-7.1 years), scanned at baseline, 6, 12, 18, and 24 months. Statistical maps revealed 3D patterns of brain atrophy at each follow-up scan relative to the baseline; numerical summaries were used to quantify temporal lobe atrophy within a statistically-defined region-of-interest. Power analyses revealed superior sample size estimates over traditional clinical measures. Only 80, 46, and 39 AD patients were required for a hypothetical clinical trial, at 6, 12, and 24 months respectively, to detect a 25% reduction in average change using a two-sided test (alpha=0.05, power=80%). Correspondingly, 106, 79, and 67 subjects were needed for an equivalent MCI trial aiming for earlier intervention. A 24-month trial provides most power, except when patient attrition exceeds 15-16%/year, in which case a 12-month trial is optimal. These statistics may facilitate clinical trial design using voxel-based brain mapping methods such as TBM., (Copyright (c) 2010 Elsevier Inc. All rights reserved.)

Published
2010
Full Text
View/download PDF

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

Author

Tilot, Amanda K, Khramtsova, Ekaterina A, Liang, Dan, Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Liu, Siyao, Brotman, Sarah M, Thompson, Paul M, Medland, Sarah E, Macciardi, Fabio, Stranger, Barbara E, Davis, Lea K, Fisher, Simon E, and Stein, Jason L

Subjects
Neurosciences, Pediatric, Genetics, Human Genome, Stem Cell Research, Underpinning research, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Biological Evolution, Cerebral Cortex, Genetic Testing, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Multifactorial Inheritance, Organ Size, Quantitative Trait Loci, cortical surface area, genome-wide association study, human gained enhancers, polygenic selection, Psychology, Cognitive Sciences, Experimental Psychology
Abstract

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.

Published
2021

10. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author

Nunes, Abraham, Schnack, Hugo G, Ching, Christopher RK, Agartz, Ingrid, Akudjedu, Theophilus N, Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Bauer, Jochen, Baune, Bernhard T, Bøen, Erlend, Bonnin, Caterina del Mar, Busatto, Geraldo F, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Chaim-Avancini, Tiffany M, Dannlowski, Udo, Díaz-Zuluaga, Ana M, Dietsche, Bruno, Doan, Nhat Trung, Duchesnay, Edouard, Elvsåshagen, Torbjørn, Emden, Daniel, Eyler, Lisa T, Fatjó-Vilas, Mar, Favre, Pauline, Foley, Sonya F, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Grotegerd, Dominik, Hahn, Tim, Henry, Chantal, Hibar, Derrek P, Houenou, Josselin, Howells, Fleur M, Jahanshad, Neda, Kaufmann, Tobias, Kenney, Joanne, Kircher, Tilo TJ, Krug, Axel, Lagerberg, Trine V, Lenroot, Rhoshel K, López-Jaramillo, Carlos, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Mwangi, Benson, Nabulsi, Leila, Opel, Nils, Overs, Bronwyn J, Pineda-Zapata, Julian A, Pomarol-Clotet, Edith, Redlich, Ronny, Roberts, Gloria, Rosa, Pedro G, Salvador, Raymond, Satterthwaite, Theodore D, Soares, Jair C, Stein, Dan J, Temmingh, Henk S, Trappenberg, Thomas, Uhlmann, Anne, van Haren, Neeltje EM, Vieta, Eduard, Westlye, Lars T, Wolf, Daniel H, Yüksel, Dilara, Zanetti, Marcus V, Andreassen, Ole A, Thompson, Paul M, and Hajek, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Biomedical Imaging, Neurosciences, Mental Health, Clinical Research, Mental health, Bipolar Disorder, Brain, Humans, Machine Learning, Magnetic Resonance Imaging, Neuroimaging, ENIGMA Bipolar Disorders Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

Published
2020

11. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort

Author

Tozzi, Leonardo, Garczarek, Lisa, Janowitz, Deborah, Stein, Dan J, Wittfeld, Katharina, Dobrowolny, Henrik, Lagopoulos, Jim, Hatton, Sean N, Hickie, Ian B, Carballedo, Angela, Brooks, Samantha J, Vuletic, Daniella, Uhlmann, Anne, Veer, Ilya M, Walter, Henrik, Bülow, Robin, Völzke, Henry, Klinger-König, Johanna, Schnell, Knut, Schoepf, Dieter, Grotegerd, Dominik, Opel, Nils, Dannlowski, Udo, Kugel, Harald, Schramm, Elisabeth, Konrad, Carsten, Kircher, Tilo, Jüksel, Dilara, Nenadić, Igor, Krug, Axel, Hahn, Tim, Steinsträter, Olaf, Redlich, Ronny, Zaremba, Dario, Zurowski, Bartosz, Fu, Cynthia HY, Dima, Danai, Cole, James, Grabe, Hans J, Connolly, Colm G, Yang, Tony T, Ho, Tiffany C, LeWinn, Kaja Z, Li, Meng, Groenewold, Nynke A, Salminen, Lauren E, Walter, Martin, Simmons, Alan N, van Erp, Theo GM, Jahanshad, Neda, Baune, Bernhard T, van der Wee, Nic JA, van Tol, Marie-Jose, Penninx, Brenda WJH, Hibar, Derrek P, Thompson, Paul M, Veltman, Dick J, Schmaal, Lianne, and Frodl, Thomas

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Pediatric, Neurosciences, Clinical Research, Mental Health, Brain Disorders, Depression, Child Abuse and Neglect Research, Behavioral and Social Science, Violence Research, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Brain Cortical Thickness, Case-Control Studies, Cerebral Cortex, Child, Child Abuse, Cohort Studies, Depressive Disorder, Major, Female, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Parietal Lobe, Prefrontal Cortex, Temporal Lobe, Young Adult, Childhood maltreatment, cortical thickness, ENIGMA, major depressive disorder, ‘for the ENIGMA-MDD Consortium’, Public Health and Health Services, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

BackgroundChildhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

Published
2020

12. The genetic architecture of the human cerebral cortex

Author

Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie N, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Pizzagalli, Fabrizio, Ching, Christopher RK, McMahon, Mary Agnes B, Shatokhina, Natalia, Zsembik, Leo CP, Thomopoulos, Sophia I, Zhu, Alyssa H, Strike, Lachlan T, Agartz, Ingrid, Alhusaini, Saud, Almeida, Marcio AA, Alnæs, Dag, Amlien, Inge K, Andersson, Micael, Ard, Tyler, Armstrong, Nicola J, Ashley-Koch, Allison, Atkins, Joshua R, Bernard, Manon, Brouwer, Rachel M, Buimer, Elizabeth EL, Bülow, Robin, Bürger, Christian, Cannon, Dara M, Chakravarty, Mallar, Chen, Qiang, Cheung, Joshua W, Couvy-Duchesne, Baptiste, Dale, Anders M, Dalvie, Shareefa, de Araujo, Tânia K, de Zubicaray, Greig I, de Zwarte, Sonja MC, Braber, Anouk den, Doan, Nhat Trung, Dohm, Katharina, Ehrlich, Stefan, Engelbrecht, Hannah-Ruth, Erk, Susanne, Fan, Chun Chieh, Fedko, Iryna O, Foley, Sonya F, Ford, Judith M, Fukunaga, Masaki, Garrett, Melanie E, Ge, Tian, Giddaluru, Sudheer, Goldman, Aaron L, Green, Melissa J, Groenewold, Nynke A, Grotegerd, Dominik, Gurholt, Tiril P, Gutman, Boris A, Hansell, Narelle K, Harris, Mathew A, Harrison, Marc B, Haswell, Courtney C, Hauser, Michael, Herms, Stefan, Heslenfeld, Dirk J, Ho, New Fei, Hoehn, David, Hoffmann, Per, Holleran, Laurena, Hoogman, Martine, Hottenga, Jouke-Jan, Ikeda, Masashi, Janowitz, Deborah, Jansen, Iris E, Jia, Tianye, Jockwitz, Christiane, Kanai, Ryota, Karama, Sherif, Kasperaviciute, Dalia, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Klein, Marieke, Knapp, Michael, Knodt, Annchen R, Krämer, Bernd, Lam, Max, Lancaster, Thomas M, Lee, Phil H, Lett, Tristram A, Lewis, Lindsay B, Lopes-Cendes, Iscia, Luciano, Michelle, Macciardi, Fabio, Marquand, Andre F, Mathias, Samuel R, Melzer, Tracy R, and Milaneschi, Yuri

Subjects
Biological Sciences, Genetics, Neurosciences, Mental Health, Brain Disorders, Stem Cell Research, 2.1 Biological and endogenous factors, Aetiology, Neurological, Attention Deficit Disorder with Hyperactivity, Brain Mapping, Cerebral Cortex, Cognition, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Organ Size, Parkinson Disease, Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group, General Science & Technology
Abstract

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.

Published
2020

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

Author

Sønderby, Ida E, Gústafsson, Ómar, Doan, Nhat Trung, Hibar, Derrek P, Martin-Brevet, Sandra, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Michael, Armstrong, Nicola J, Bernard, Manon, Blackburn, Nicholas, Blangero, John, Boomsma, Dorret I, Bralten, Janita, Brattbak, Hans-Richard, Brodaty, Henry, Brouwer, Rachel M, Bülow, Robin, Calhoun, Vince, Caspers, Svenja, Cavalleri, Gianpiero, Chen, Chi-Hua, Cichon, Sven, Ciufolini, Simone, Corvin, Aiden, Crespo-Facorro, Benedicto, Curran, Joanne E, Dale, Anders M, Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, Delanty, Norman, den Braber, Anouk, Desrivières, Sylvane, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Espeseth, Thomas, Fisher, Simon E, Franke, Barbara, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Glahn, David C, Grabe, Hans, Groenewold, Nynke A, Haavik, Jan, Håberg, Asta, Hashimoto, Ryota, Hehir-Kwa, Jayne Y, Heinz, Andreas, Hillegers, Manon HJ, Hoffmann, Per, Holleran, Laurena, Hottenga, Jouke-Jan, Hulshoff, Hilleke E, Ikeda, Masashi, Jahanshad, Neda, Jernigan, Terry, Jockwitz, Christiane, Johansson, Stefan, Jonsdottir, Gudrun A, Jönsson, Erik G, Kahn, Rene, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Knowles, Emma EM, Kolskår, Knut K, Kwok, John B, Hellard, Stephanie Le, Leu, Costin, Liu, Jingyu, Lundervold, Astri J, Lundervold, Arvid, Martin, Nicholas G, Mather, Karen, Mathias, Samuel R, McCormack, Mark, McMahon, Katie L, McRae, Allan, Milaneschi, Yuri, Moreau, Clara, Morris, Derek, Mothersill, David, Mühleisen, Thomas W, Murray, Robin, Nordvik, Jan E, Nyberg, Lars, Olde Loohuis, Loes M, Ophoff, Roel, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda, Peralta, Juan M, Pike, Bruce, and Prieto, Carlos

Subjects
Intellectual and Developmental Disabilities (IDD), Neurosciences, Brain Disorders, Autism, Biomedical Imaging, Mental Health, Mental health, Adult, Autism Spectrum Disorder, Autistic Disorder, Basal Ganglia, Brain, Chromosome Deletion, Chromosome Disorders, Chromosome Duplication, Chromosomes, Human, Pair 16, DNA Copy Number Variations, Databases, Factual, Female, Globus Pallidus, Humans, Image Processing, Computer-Assisted, Intellectual Disability, Magnetic Resonance Imaging, Male, Middle Aged, Neurodevelopmental Disorders, Organ Size, Putamen, Schizophrenia, 16p11.2 European Consortium, for the ENIGMA-CNV working group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

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

Published
2020

14. Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Author

Yun, Je-Yeon, Boedhoe, Premika SW, Vriend, Chris, Jahanshad, Neda, Abe, Yoshinari, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fouche, Jean-Paul, Giménez, Mònica, Gruner, Patricia, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Ikari, Keisuke, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Lazaro, Luisa, Lochner, Christine, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morgado, Pedro, Moreira, Pedro, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O’Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, van Wingen, Guido A, Xu, Jian, Xu, Xiufeng, Zhao, Qing, van den Heuvel, Odile3 A, Stein, Dan J, Thompson, Paul M, Ik, Kang, and Cho, K

Subjects
Mental Health, Brain Disorders, Serious Mental Illness, Clinical Research, Neurosciences, Neurological, Mental health, Adult, Brain, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Obsessive-Compulsive Disorder, brain structural covariance network, graph theory, obsessive-compulsive disorder, pharmacotherapy, illness duration, ENIGMA-OCD working group, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P

Published
2020

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

Author

Satizabal, Claudia L, Adams, Hieab HH, Hibar, Derrek P, White, Charles C, Knol, Maria J, Stein, Jason L, Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V, Smith, Albert V, Bis, Joshua C, Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J, Yang, Jingyun, Yanek, Lisa R, Lee, Tom V, Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D, Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E, Kim, Sungeun, Hoehn, David, Armstrong, Nicola J, Chen, Qiang, Holmes, Avram J, den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K, Jones, Hannah J, Pike, G Bruce, Stein, Dan J, Stevens, Allison, Bralten, Janita, Vernooij, Meike W, Harris, Tamara B, Filippi, Irina, Witte, A Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H, Becker, James T, Doan, Nhat Trung, Hagenaars, Saskia P, Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M, Ames, David, Goldman, Aaron L, Lee, Phil H, Boomsma, Dorret I, Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M, Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M, Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E, Shin, Jean, Ipser, Jonathan C, Vinke, Louis N, Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K, Aribisala, Benjamin S, and Schmidt, Helena

Subjects
Biological Sciences, Genetics, Brain Disorders, Mental Health, Neurosciences, Human Genome, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Animals, Brain, Cohort Studies, Drosophila melanogaster, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Middle Aged, Neurodevelopmental Disorders, Organ Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

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.

Published
2019

16. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes

Author

van der Lee, Sven J, Knol, Maria J, Chauhan, Ganesh, Satizabal, Claudia L, Smith, Albert Vernon, Hofer, Edith, Bis, Joshua C, Hibar, Derrek P, Hilal, Saima, van den Akker, Erik B, Arfanakis, Konstantinos, Bernard, Manon, Yanek, Lisa R, Amin, Najaf, Crivello, Fabrice, Cheung, Josh W, Harris, Tamara B, Saba, Yasaman, Lopez, Oscar L, Li, Shuo, van der Grond, Jeroen, Yu, Lei, Paus, Tomas, Roshchupkin, Gennady V, Amouyel, Philippe, Jahanshad, Neda, Taylor, Kent D, Yang, Qiong, Mathias, Rasika A, Boehringer, Stefan, Mazoyer, Bernard, Rice, Ken, Cheng, Ching Yu, Maillard, Pauline, van Heemst, Diana, Wong, Tien Yin, Niessen, Wiro J, Beiser, Alexa S, Beekman, Marian, Zhao, Wanting, Nyquist, Paul A, Chen, Christopher, Launer, Lenore J, Psaty, Bruce M, Ikram, M Kamran, Vernooij, Meike W, Schmidt, Helena, Pausova, Zdenka, Becker, Diane M, De Jager, Philip L, Thompson, Paul M, van Duijn, Cornelia M, Bennett, David A, Slagboom, P Eline, Schmidt, Reinhold, Longstreth, WT, Ikram, M Arfan, Seshadri, Sudha, Debette, Stéphanie, Gudnason, Vilmundur, Adams, Hieab HH, and DeCarli, Charles

Subjects
Biological Sciences, Genetics, Neurosciences, Mental Health, Brain Disorders, Human Genome, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Frontal Lobe, Gene Expression Regulation, Developmental, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Genotype, Heredity, Humans, Magnetic Resonance Imaging, Occipital Lobe, Organ Size, Parietal Lobe, Phenotype, Temporal Lobe, United Kingdom, Biomarkers, Genome-wide association studies, Neurology, Biological sciences, Biomedical and clinical sciences
Abstract

Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.

Published
2019

17. Concordance of genetic variation that increases risk for Tourette Syndrome and that influences its underlying neurocircuitry

Author

Mufford, Mary, Cheung, Josh, Jahanshad, Neda, van der Merwe, Celia, Ding, Linda, Groenewold, Nynke, Koen, Nastassja, Chimusa, Emile R, Dalvie, Shareefa, Ramesar, Raj, Knowles, James A, Lochner, Christine, Hibar, Derrek P, Paschou, Peristera, van den Heuvel, Odile A, Medland, Sarah E, Scharf, Jeremiah M, Mathews, Carol A, Thompson, Paul M, and Stein, Dan J

Subjects
Biological Psychology, Psychology, Tourette Syndrome, Neurodegenerative, Genetics, Brain Disorders, Serious Mental Illness, Mental Health, Neurosciences, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Mental health, Case-Control Studies, DNA Mutational Analysis, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Hippocampus, Humans, Linkage Disequilibrium, Magnetic Resonance Imaging, Neural Pathways, Polymorphism, Single Nucleotide, Putamen, Psychiatric Genomics Consortium - Tourette Syndrome working group, Clinical Sciences, Public Health and Health Services, Clinical sciences, Biological psychology
Abstract

There have been considerable recent advances in understanding the genetic architecture of Tourette syndrome (TS) as well as its underlying neurocircuitry. However, the mechanisms by which genetic variation that increases risk for TS-and its main symptom dimensions-influence relevant brain regions are poorly understood. Here we undertook a genome-wide investigation of the overlap between TS genetic risk and genetic influences on the volume of specific subcortical brain structures that have been implicated in TS. We obtained summary statistics for the most recent TS genome-wide association study (GWAS) from the TS Psychiatric Genomics Consortium Working Group (4644 cases and 8695 controls) and GWAS of subcortical volumes from the ENIGMA consortium (30,717 individuals). We also undertook analyses using GWAS summary statistics of key symptom factors in TS, namely social disinhibition and symmetry behaviour. SNP effect concordance analysis (SECA) was used to examine genetic pleiotropy-the same SNP affecting two traits-and concordance-the agreement in single nucelotide polymorphism (SNP) effect directions across these two traits. In addition, a conditional false discovery rate (FDR) analysis was performed, conditioning the TS risk variants on each of the seven subcortical and the intracranial brain volume GWAS. Linkage disequilibrium score regression (LDSR) was used as validation of the SECA method. SECA revealed significant pleiotropy between TS and putamen (p = 2 × 10-4) and caudate (p = 4 × 10-4) volumes, independent of direction of effect, and significant concordance between TS and lower thalamic volume (p = 1 × 10-3). LDSR lent additional support for the association between TS and thalamus volume (p = 5.85 × 10-2). Furthermore, SECA revealed significant evidence of concordance between the social disinhibition symptom dimension and lower thalamus volume (p = 1 × 10-3), as well as concordance between symmetry behaviour and greater putamen volume (p = 7 × 10-4). Conditional FDR analysis further revealed novel variants significantly associated with TS (p

Published
2019

18. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium.

Author

van Erp, Theo GM, Walton, Esther, Hibar, Derrek P, Schmaal, Lianne, Jiang, Wenhao, Glahn, David C, Pearlson, Godfrey D, Yao, Nailin, Fukunaga, Masaki, Hashimoto, Ryota, Okada, Naohiro, Yamamori, Hidenaga, Bustillo, Juan R, Clark, Vincent P, Agartz, Ingrid, Mueller, Bryon A, Cahn, Wiepke, de Zwarte, Sonja MC, Hulshoff Pol, Hilleke E, Kahn, René S, Ophoff, Roel A, van Haren, Neeltje EM, Andreassen, Ole A, Dale, Anders M, Doan, Nhat Trung, Gurholt, Tiril P, Hartberg, Cecilie B, Haukvik, Unn K, Jørgensen, Kjetil N, Lagerberg, Trine V, Melle, Ingrid, Westlye, Lars T, Gruber, Oliver, Kraemer, Bernd, Richter, Anja, Zilles, David, Calhoun, Vince D, Crespo-Facorro, Benedicto, Roiz-Santiañez, Roberto, Tordesillas-Gutiérrez, Diana, Loughland, Carmel, Carr, Vaughan J, Catts, Stanley, Cropley, Vanessa L, Fullerton, Janice M, Green, Melissa J, Henskens, Frans A, Jablensky, Assen, Lenroot, Rhoshel K, Mowry, Bryan J, Michie, Patricia T, Pantelis, Christos, Quidé, Yann, Schall, Ulrich, Scott, Rodney J, Cairns, Murray J, Seal, Marc, Tooney, Paul A, Rasser, Paul E, Cooper, Gavin, Shannon Weickert, Cynthia, Weickert, Thomas W, Morris, Derek W, Hong, Elliot, Kochunov, Peter, Beard, Lauren M, Gur, Raquel E, Gur, Ruben C, Satterthwaite, Theodore D, Wolf, Daniel H, Belger, Aysenil, Brown, Gregory G, Ford, Judith M, Macciardi, Fabio, Mathalon, Daniel H, O'Leary, Daniel S, Potkin, Steven G, Preda, Adrian, Voyvodic, James, Lim, Kelvin O, McEwen, Sarah, Yang, Fude, Tan, Yunlong, Tan, Shuping, Wang, Zhiren, Fan, Fengmei, Chen, Jingxu, Xiang, Hong, Tang, Shiyou, Guo, Hua, Wan, Ping, Wei, Dong, Bockholt, Henry J, Ehrlich, Stefan, Wolthusen, Rick PF, King, Margaret D, Shoemaker, Jody M, Sponheim, Scott R, De Haan, Lieuwe, and Koenders, Laura

Subjects
Karolinska Schizophrenia Project, Brain, Frontal Lobe, Prefrontal Cortex, Temporal Lobe, Humans, Magnetic Resonance Imaging, Severity of Illness Index, Linear Models, Case-Control Studies, Schizophrenia, Age of Onset, Adolescent, Adult, Aged, Middle Aged, Child, Female, Male, Young Adult, Neuroimaging, Cortical, Imaging, Meta-analysis, Surface area, Thickness, Serious Mental Illness, Biomedical Imaging, Mental Health, Clinical Research, Neurosciences, Brain Disorders, Mental health, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

BackgroundThe profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.MethodsThe study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.ResultsCompared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.ConclusionsThe findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Published
2018

19. Genetic Overlap Between Schizophrenia and Volumes of Hippocampus, Putamen, and Intracranial Volume Indicates Shared Molecular Genetic Mechanisms.

Author

Smeland, Olav B, Wang, Yunpeng, Frei, Oleksandr, Li, Wen, Hibar, Derrek P, Franke, Barbara, Bettella, Francesco, Witoelar, Aree, Djurovic, Srdjan, Chen, Chi-Hua, Thompson, Paul M, Dale, Anders M, and Andreassen, Ole A

Subjects
Neurosciences, Schizophrenia, Genetics, Human Genome, Mental Health, Brain Disorders, Serious Mental Illness, Aetiology, 2.1 Biological and endogenous factors, Mental health, Brain, Genetic Loci, Genetic Pleiotropy, Genome-Wide Association Study, Hippocampus, Humans, Magnetic Resonance Imaging, Putamen, pleiotropy, genome-wide association study, conditional false discovery rate, subcortical brain structures, common genetic variants, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent.

Published
2018

20. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex.

Author

Guadalupe, Tulio, Mathias, Samuel R, vanErp, Theo GM, Whelan, Christopher D, Zwiers, Marcel P, Abe, Yoshinari, Abramovic, Lucija, Agartz, Ingrid, Andreassen, Ole A, Arias-Vásquez, Alejandro, Aribisala, Benjamin S, Armstrong, Nicola J, Arolt, Volker, Artiges, Eric, Ayesa-Arriola, Rosa, Baboyan, Vatche G, Banaschewski, Tobias, Barker, Gareth, Bastin, Mark E, Baune, Bernhard T, Blangero, John, Bokde, Arun LW, Boedhoe, Premika SW, Bose, Anushree, Brem, Silvia, Brodaty, Henry, Bromberg, Uli, Brooks, Samantha, Büchel, Christian, Buitelaar, Jan, Calhoun, Vince D, Cannon, Dara M, Cattrell, Anna, Cheng, Yuqi, Conrod, Patricia J, Conzelmann, Annette, Corvin, Aiden, Crespo-Facorro, Benedicto, Crivello, Fabrice, Dannlowski, Udo, de Zubicaray, Greig I, de Zwarte, Sonja MC, Deary, Ian J, Desrivières, Sylvane, Doan, Nhat Trung, Donohoe, Gary, Dørum, Erlend S, Ehrlich, Stefan, Espeseth, Thomas, Fernández, Guillén, Flor, Herta, Fouche, Jean-Paul, Frouin, Vincent, Fukunaga, Masaki, Gallinat, Jürgen, Garavan, Hugh, Gill, Michael, Suarez, Andrea Gonzalez, Gowland, Penny, Grabe, Hans J, Grotegerd, Dominik, Gruber, Oliver, Hagenaars, Saskia, Hashimoto, Ryota, Hauser, Tobias U, Heinz, Andreas, Hibar, Derrek P, Hoekstra, Pieter J, Hoogman, Martine, Howells, Fleur M, Hu, Hao, Hulshoff Pol, Hilleke E, Huyser, Chaim, Ittermann, Bernd, Jahanshad, Neda, Jönsson, Erik G, Jurk, Sarah, Kahn, Rene S, Kelly, Sinead, Kraemer, Bernd, Kugel, Harald, Kwon, Jun Soo, Lemaitre, Herve, Lesch, Klaus-Peter, Lochner, Christine, Luciano, Michelle, Marquand, Andre F, Martin, Nicholas G, Martínez-Zalacaín, Ignacio, Martinot, Jean-Luc, Mataix-Cols, David, Mather, Karen, McDonald, Colm, McMahon, Katie L, Medland, Sarah E, Menchón, José M, Morris, Derek W, Mothersill, Omar, Maniega, Susana Munoz, and Mwangi, Benson

Subjects
Brain, Humans, Magnetic Resonance Imaging, Organ Size, Aging, Sex Characteristics, Quantitative Trait, Heritable, Adolescent, Adult, Aged, Middle Aged, Female, Male, Functional Laterality, Meta-Analysis as Topic, Young Adult, Age, Enigma, Handedness, Heritability, Meta-analysis, Sex, Subcortical brain asymmetry, Quantitative Trait, Heritable, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology
Abstract

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.

Published
2017

21. Childhood adversity impacts on brain subcortical structures relevant to depression

Author

Frodl, Thomas, Janowitz, Deborah, Schmaal, Lianne, Tozzi, Leonardo, Dobrowolny, Henrik, Stein, Dan J, Veltman, Dick J, Wittfeld, Katharina, van Erp, Theo GM, Jahanshad, Neda, Block, Andrea, Hegenscheid, Katrin, Völzke, Henry, Lagopoulos, Jim, Hatton, Sean N, Hickie, Ian B, Frey, Eva Maria, Carballedo, Angela, Brooks, Samantha J, Vuletic, Daniella, Uhlmann, Anne, Veer, Ilya M, Walter, Henrik, Schnell, Knut, Grotegerd, Dominik, Arolt, Volker, Kugel, Harald, Schramm, Elisabeth, Konrad, Carsten, Zurowski, Bartosz, Baune, Bernhard T, van der Wee, Nic JA, van Tol, Marie-Jose, Penninx, Brenda WJH, Thompson, Paul M, Hibar, Derrek P, Dannlowski, Udo, and Grabe, Hans J

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Mental Health, Violence Research, Serious Mental Illness, Behavioral and Social Science, Depression, Major Depressive Disorder, Brain Disorders, Pediatric, Neurosciences, Aetiology, 2.3 Psychological, social and economic factors, Mental health, Adult, Adult Survivors of Child Adverse Events, Antidepressive Agents, Brain, Depressive Disorder, Major, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Psychiatric Status Rating Scales, Sex Characteristics, Software, Surveys and Questionnaires, Childhood adversity, MRI, Caudate, Hippocampus, ENIGMA, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

Childhood adversity plays an important role for development of major depressive disorder (MDD). There are differences in subcortical brain structures between patients with MDD and healthy controls, but the specific impact of childhood adversity on such structures in MDD remains unclear. Thus, aim of the present study was to investigate whether childhood adversity is associated with subcortical volumes and how it interacts with a diagnosis of MDD and sex. Within the ENIGMA-MDD network, nine university partner sites, which assessed childhood adversity and magnetic resonance imaging in patients with MDD and controls, took part in the current joint mega-analysis. In this largest effort world-wide to identify subcortical brain structure differences related to childhood adversity, 3036 participants were analyzed for subcortical brain volumes using FreeSurfer. A significant interaction was evident between childhood adversity, MDD diagnosis, sex, and region. Increased exposure to childhood adversity was associated with smaller caudate volumes in females independent of MDD. All subcategories of childhood adversity were negatively associated with caudate volumes in females - in particular emotional neglect and physical neglect (independently from age, ICV, imaging site and MDD diagnosis). There was no interaction effect between childhood adversity and MDD diagnosis on subcortical brain volumes. Childhood adversity is one of the contributors to brain structural abnormalities. It is associated with subcortical brain abnormalities that are relevant to psychiatric disorders such as depression.

Published
2017

22. The effect of increased genetic risk for Alzheimer's disease on hippocampal and amygdala volume

Author

Lupton, Michelle K, Strike, Lachlan, Hansell, Narelle K, Wen, Wei, Mather, Karen A, Armstrong, Nicola J, Thalamuthu, Anbupalam, McMahon, Katie L, de Zubicaray, Greig I, Assareh, Amelia A, Simmons, Andrew, Proitsi, Petroula, Powell, John F, Montgomery, Grant W, Hibar, Derrek P, Westman, Eric, Tsolaki, Magda, Kloszewska, Iwona, Soininen, Hilkka, Mecocci, Patrizia, Velas, Bruno, Lovestone, Simon, Initiative, the Alzheimer's Disease Neuroimaging, Brodaty, Henry, Ames, David, Trollor, Julian N, Martin, Nicholas G, Thompson, Paul M, Sachdev, Perminder S, and Wright, Margaret J

Subjects
Biological Psychology, Psychology, Genetic Testing, Dementia, Neurosciences, Aging, Clinical Research, Alzheimer's Disease, Genetics, Brain Disorders, Neurodegenerative, Prevention, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Aetiology, Neurological, Adolescent, Adult, Aged, Aged, 80 and over, Alzheimer Disease, Amygdala, Apolipoproteins E, Case-Control Studies, Cognitive Dysfunction, Cohort Studies, Female, Genetic Association Studies, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Membrane Glycoproteins, Middle Aged, Receptors, Immunologic, Risk, Young Adult, Alzheimer's disease, Polygenic risk score, APOE, TREM2, Alzheimer's Disease Neuroimaging Initiative, Clinical Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Reduction in hippocampal and amygdala volume measured via structural magnetic resonance imaging is an early marker of Alzheimer's disease (AD). Whether genetic risk factors for AD exert an effect on these subcortical structures independent of clinical status has not been fully investigated. We examine whether increased genetic risk for AD influences hippocampal and amygdala volumes in case-control and population cohorts at different ages, in 1674 older (aged >53 years; 17% AD, 39% mild cognitive impairment [MCI]) and 467 young (16-30 years) adults. An AD polygenic risk score combining common risk variants excluding apolipoprotein E (APOE), and a single nucleotide polymorphism in TREM2, were both associated with reduced hippocampal volume in healthy older adults and those with MCI. APOE ε4 was associated with hippocampal and amygdala volume in those with AD and MCI but was not associated in healthy older adults. No associations were found in young adults. Genetic risk for AD affects the hippocampus before the clinical symptoms of AD, reflecting a neurodegenerative effect before clinical manifestations in older adults.

Published
2016

23. Heritability and reliability of automatically segmented human hippocampal formation subregions

Author

Whelan, Christopher D, Hibar, Derrek P, van Velzen, Laura S, Zannas, Anthony S, Carrillo-Roa, Tania, McMahon, Katie, Prasad, Gautam, Kelly, Sinéad, Faskowitz, Joshua, deZubiracay, Greig, Iglesias, Juan E, van Erp, Theo GM, Frodl, Thomas, Martin, Nicholas G, Wright, Margaret J, Jahanshad, Neda, Schmaal, Lianne, Sämann, Philipp G, Thompson, Paul M, and Initiative, for the Alzheimer's Disease Neuroimaging

Subjects
Biomedical and Clinical Sciences, Health Sciences, Acquired Cognitive Impairment, Clinical Research, Neurosciences, Brain Disorders, Mental Health, Biomedical Imaging, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Algorithms, Alzheimer Disease, Anxiety Disorders, Depressive Disorder, Female, Hippocampus, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Phenotype, Software, Alzheimer's Disease Neuroimaging Initiative, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5T versus 3T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4T QTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5T and 3T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium.

Published
2016

24. Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept

Author

Franke, Barbara, Stein, Jason L, Ripke, Stephan, Anttila, Verneri, Hibar, Derrek P, van Hulzen, Kimm JE, Arias-Vasquez, Alejandro, Smoller, Jordan W, Nichols, Thomas E, Neale, Michael C, McIntosh, Andrew M, Lee, Phil, McMahon, Francis J, Meyer-Lindenberg, Andreas, Mattheisen, Manuel, Andreassen, Ole A, Gruber, Oliver, Sachdev, Perminder S, Roiz-Santiañez, Roberto, Saykin, Andrew J, Ehrlich, Stefan, Mather, Karen A, Turner, Jessica A, Schwarz, Emanuel, Thalamuthu, Anbupalam, Yao, Yin, Ho, Yvonne YW, Martin, Nicholas G, Wright, Margaret J, O'Donovan, Michael C, Thompson, Paul M, Neale, Benjamin M, Medland, Sarah E, and Sullivan, Patrick F

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Schizophrenia, Neurosciences, Genetics, Serious Mental Illness, Mental Health, Brain Disorders, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Brain, Endophenotypes, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Magnetic Resonance Imaging, Neuroimaging, Organ Size, Polymorphism, Single Nucleotide, Schizophrenia Working Group of the Psychiatric Genomics Consortium, ENIGMA Consortium, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Published
2016

25. Carriers of a common variant in the dopamine transporter gene have greater dementia risk, cognitive decline, and faster ventricular expansion

Author

Roussotte, Florence F, Gutman, Boris A, Hibar, Derrek P, Madsen, Sarah K, Narr, Katherine L, Thompson, Paul M, and Initiative, Alzheimer's Disease Neuroimaging

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Clinical Research, Aging, Acquired Cognitive Impairment, Genetic Testing, Neurodegenerative, Alzheimer's Disease, Prevention, Brain Disorders, Genetics, Neurosciences, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, Aged, Aged, 80 and over, Alleles, Alzheimer Disease, Case-Control Studies, Cerebral Ventricles, Cognition, Cognitive Dysfunction, Dopamine Plasma Membrane Transport Proteins, Female, Genotype, Heterozygote, Humans, Magnetic Resonance Imaging, Male, Polymorphism, Genetic, Risk, Neuroimaging genetics, Ventricular expansion, Dopamine transporter, DAT1, Alzheimer's Disease Neuroimaging Initiative, Clinical Sciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionGenetic variants in DAT1, the gene encoding the dopamine transporter (DAT) protein, have been implicated in many brain disorders. In a recent case-control study of Alzheimer's disease (AD), a regulatory polymorphism in DAT1 showed a significant association with the clinical stages of dementia.MethodsWe tested whether this variant was associated with increased AD risk, and with measures of cognitive decline and longitudinal ventricular expansion, in a large sample of elderly participants with genetic, neurocognitive, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative.ResultsThe minor allele-previously linked with increased DAT expression in vitro-was more common in AD patients than in both individuals with mild cognitive impairment and healthy elderly controls. The same allele was also associated with poorer cognitive performance and faster ventricular expansion, independently of diagnosis.DiscussionThese results may be due to reduced dopaminergic transmission in carriers of the DAT1 mutation.

Published
2015

26. Common genetic variants influence human subcortical brain structures

Author

Hibar, Derrek P, Stein, Jason L, Renteria, Miguel E, Arias-Vasquez, Alejandro, Desrivières, Sylvane, Jahanshad, Neda, Toro, Roberto, Wittfeld, Katharina, Abramovic, Lucija, Andersson, Micael, Aribisala, Benjamin S, Armstrong, Nicola J, Bernard, Manon, Bohlken, Marc M, Boks, Marco P, Bralten, Janita, Brown, Andrew A, Mallar Chakravarty, M, Chen, Qiang, Ching, Christopher RK, Cuellar-Partida, Gabriel, den Braber, Anouk, Giddaluru, Sudheer, Goldman, Aaron L, Grimm, Oliver, Guadalupe, Tulio, Hass, Johanna, Woldehawariat, Girma, Holmes, Avram J, Hoogman, Martine, Janowitz, Deborah, Jia, Tianye, Kim, Sungeun, Klein, Marieke, Kraemer, Bernd, Lee, Phil H, Olde Loohuis, Loes M, Luciano, Michelle, Macare, Christine, Mather, Karen A, Mattheisen, Manuel, Milaneschi, Yuri, Nho, Kwangsik, Papmeyer, Martina, Ramasamy, Adaikalavan, Risacher, Shannon L, Roiz-Santiañez, Roberto, Rose, Emma J, Salami, Alireza, Sämann, Philipp G, Schmaal, Lianne, Schork, Andrew J, Shin, Jean, Strike, Lachlan T, Teumer, Alexander, van Donkelaar, Marjolein MJ, van Eijk, Kristel R, Walters, Raymond K, Westlye, Lars T, Whelan, Christopher D, Winkler, Anderson M, Zwiers, Marcel P, Alhusaini, Saud, Athanasiu, Lavinia, Ehrlich, Stefan, Hakobjan, Marina MH, Hartberg, Cecilie B, Haukvik, Unn K, Heister, Angelien JGAM, Hoehn, David, Kasperaviciute, Dalia, Liewald, David CM, Lopez, Lorna M, Makkinje, Remco RR, Matarin, Mar, Naber, Marlies AM, Reese McKay, D, Needham, Margaret, Nugent, Allison C, Pütz, Benno, Royle, Natalie A, Shen, Li, Sprooten, Emma, Trabzuni, Daniah, van der Marel, Saskia SL, van Hulzen, Kimm JE, Walton, Esther, Wolf, Christiane, Almasy, Laura, Ames, David, Arepalli, Sampath, Assareh, Amelia A, Bastin, Mark E, Brodaty, Henry, Bulayeva, Kazima B, Carless, Melanie A, Cichon, Sven, Corvin, Aiden, Curran, Joanne E, and Czisch, Michael

Subjects
Biological Psychology, Biological Sciences, Genetics, Psychology, Brain Disorders, Human Genome, Mental Health, Neurosciences, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Mental health, Adolescent, Adult, Aged, Aged, 80 and over, Aging, Apoptosis, Brain, Caudate Nucleus, Child, Female, Gene Expression Regulation, Developmental, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Membrane Proteins, Middle Aged, Organ Size, Putamen, Sex Characteristics, Skull, Young Adult, Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN, IMAGEN, SYS, General Science & Technology
Abstract

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Published
2015

27. Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

Author

Hibar, Derrek P, Stein, Jason L, Jahanshad, Neda, Kohannim, Omid, Hua, Xue, Toga, Arthur W, McMahon, Katie L, de Zubicaray, Greig I, Martin, Nicholas G, Wright, Margaret J, Initiative, Alzheimer's Disease Neuroimaging, Weiner, Michael W, and Thompson, Paul M

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Neurodegenerative, Dementia, Alzheimer's Disease, Genetics, Aging, Biomedical Imaging, Prevention, Brain Disorders, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Neurological, Aged, Aged, 80 and over, Alzheimer Disease, Epistasis, Genetic, Female, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Neuroimaging, Polymorphism, Single Nucleotide, Risk, Temporal Lobe, Twins, Epistasis, Interaction, Genome-wide, GWAS, GWIA, Sure independence screening, Tensor-based morphometry, Alzheimer's Disease Neuroimaging Initiative, Clinical Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

Published
2015

28. A commonly carried genetic variant in the delta opioid receptor gene, OPRD1, is associated with smaller regional brain volumes: Replication in elderly and young populations

Author

Roussotte, Florence F, Jahanshad, Neda, Hibar, Derrek P, Sowell, Elizabeth R, Kohannim, Omid, Barysheva, Marina, Hansell, Narelle K, McMahon, Katie L, de Zubicaray, Greig I, Montgomery, Grant W, Martin, Nicholas G, Wright, Margaret J, Toga, Arthur W, Jack, Clifford R, Weiner, Michael W, Thompson, Paul M, and ADNI, the

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Drug Abuse (NIDA only), Alzheimer's Disease, Opioids, Behavioral and Social Science, Basic Behavioral and Social Science, Acquired Cognitive Impairment, Substance Misuse, Neurodegenerative, Neurosciences, Genetics, Aging, Dementia, Biomedical Imaging, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Good Health and Well Being, Aged, Alzheimer Disease, Biomarkers, Brain, Cognitive Dysfunction, Databases, Factual, Female, Genotyping Techniques, Humans, Image Processing, Computer-Assisted, Linkage Disequilibrium, Magnetic Resonance Imaging, Male, Organ Size, Polymorphism, Single Nucleotide, Receptors, Opioid, delta, Twin Studies as Topic, Young Adult, neuroimaging, genetics, neurodegeneration, drug addiction, opiates, ADNI, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

Published
2014

29. Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity.

Author

Jahanshad, Neda, Rajagopalan, Priya, Hua, Xue, Hibar, Derrek, Nir, Talia, Toga, Arthur, Jack, Clifford, Saykin, Andrew, Green, Robert, Weiner, Michael, Medland, Sarah, Montgomery, Grant, Hansell, Narelle, McMahon, Katie, de Zubicaray, Greig, Martin, Nicholas, Wright, Margaret, and Thompson, Paul

Subjects
Adult, Alzheimer Disease, Autistic Disorder, Brain, Chromosomes, Human, Pair 11, Endosomal Sorting Complexes Required for Transport, Extracellular Matrix Proteins, Female, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Nedd4 Ubiquitin Protein Ligases, Radiography, Severity of Illness Index, Twins, Dizygotic, Twins, Monozygotic, Ubiquitin-Conjugating Enzymes, Ubiquitin-Protein Ligases
Abstract

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimers disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brains connectivity pattern, allowing us to discover genetic variants that affect the human brains wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimers disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Published
2013

30. Exhaustive Search of the SNP-SNP Interactome Identifies Epistatic Effects on Brain Volume in Two Cohorts

Author

Hibar, Derrek P, Stein, Jason L, Jahanshad, Neda, Kohannim, Omid, Toga, Arthur W, McMahon, Katie L, de Zubicaray, Greig I, Montgomery, Grant W, Martin, Nicholas G, Wright, Margaret J, Weiner, Michael W, and Thompson, Paul M

Subjects
Information and Computing Sciences, Genetics, Bioengineering, Neurosciences, Human Genome, Neurological, Algorithms, Alzheimer Disease, Brain, Chromosome Mapping, Cohort Studies, Connectome, Epistasis, Genetic, Genetic Predisposition to Disease, Humans, Magnetic Resonance Imaging, Organ Size, Polymorphism, Single Nucleotide, epistasis, interaction, genome, sure independence, tensor-based morphometry, Artificial Intelligence & Image Processing, Information and computing sciences
Abstract

The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

Published
2013

31. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs

Author

Sønderby, Ida E, Ching, Christopher RK, Thomopoulos, Sophia I, van der Meer, Dennis, Sun, Daqiang, Villalon-Reina, Julio E, Agartz, Ingrid, Amunts, Katrin, Arango, Celso, Armstrong, Nicola J, Ayesa-Arriola, Rosa, Bakker, Geor, Bassett, Anne S, Boomsma, Dorret I, Bülow, Robin, Butcher, Nancy J, Calhoun, Vince D, Caspers, Svenja, Chow, Eva WC, Cichon, Sven, Ciufolini, Simone, Craig, Michael C, Crespo-Facorro, Benedicto, Cunningham, Adam C, Dale, Anders M, Dazzan, Paola, de Zubicaray, Greig I, Djurovic, Srdjan, Doherty, Joanne L, Donohoe, Gary, Draganski, Bogdan, Durdle, Courtney A, Ehrlich, Stefan, Emanuel, Beverly S, Espeseth, Thomas, Fisher, Simon E, Ge, Tian, Glahn, David C, Grabe, Hans J, Gur, Raquel E, Gutman, Boris A, Haavik, Jan, Håberg, Asta K, Hansen, Laura A, Hashimoto, Ryota, Hibar, Derrek P, Holmes, Avram J, Hottenga, Jouke-Jan, Hulshoff Pol, Hilleke E, Jalbrzikowski, Maria, Knowles, Emma EM, Kushan, Leila, Linden, David EJ, Liu, Jingyu, Lundervold, Astri J, Martin-Brevet, Sandra, Martínez, Kenia, Mather, Karen A, Mathias, Samuel R, McDonald-McGinn, Donna M, McRae, Allan F, Medland, Sarah E, Moberget, Torgeir, Modenato, Claudia, Monereo Sánchez, Jennifer, Moreau, Clara A, Mühleisen, Thomas W, Paus, Tomas, Pausova, Zdenka, Prieto, Carlos, Ragothaman, Anjanibhargavi, Reinbold, Céline S, Reis Marques, Tiago, Repetto, Gabriela M, Reymond, Alexandre, Roalf, David R, Rodriguez-Herreros, Borja, Rucker, James J, Sachdev, Perminder S, Schmitt, James E, Schofield, Peter R, Silva, Ana I, Stefansson, Hreinn, Stein, Dan J, Tamnes, Christian K, Tordesillas-Gutiérrez, Diana, Ulfarsson, Magnus O, Vajdi, Ariana, van 't Ent, Dennis, van den Bree, Marianne BM, Vassos, Evangelos, Vázquez-Bourgon, Javier, Vila-Rodriguez, Fidel, Walters, G Bragi, Wen, Wei, Westlye, Lars T, Wittfeld, Katharina, Zackai, Elaine H, Stefánsson, Kári, and Jacquemont, Sebastien

Subjects
DNA Copy Number Variations, ENIGMA 22q11.2 Deletion Syndrome Working Group, Neuroimaging, Basic Behavioral and Social Science, genetics-first approach, Clinical Research, evolution, Behavioral and Social Science, Genetics, ENIGMA-CNV Working Group, Humans, Multicenter Studies as Topic, 2.1 Biological and endogenous factors, copy number variant, Aetiology, Pediatric, brain structural imaging, Mental Disorders, neurodevelopmental disorders, Prevention, Human Genome, Neurosciences, Brain, Experimental Psychology, diffusion tensor imaging, Magnetic Resonance Imaging, Brain Disorders, psychiatric disorders, Mental Health, Neurological, Cognitive Sciences
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.

Published
2022

32. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author

Ching, Christopher RK, Hibar, Derrek P, Gurholt, Tiril P, Nunes, Abraham, Thomopoulos, Sophia I, Abé, Christoph, Agartz, Ingrid, Brouwer, Rachel M, Cannon, Dara M, de Zwarte, Sonja MC, Eyler, Lisa T, Favre, Pauline, Hajek, Tomas, Haukvik, Unn K, Houenou, Josselin, Landén, Mikael, Lett, Tristram A, McDonald, Colm, Nabulsi, Leila, Patel, Yash, Pauling, Melissa E, Paus, Tomas, Radua, Joaquim, Soeiro-de-Souza, Marcio G, Tronchin, Giulia, van Haren, Neeltje EM, Vieta, Eduard, Walter, Henrik, Zeng, Ling-Li, Alda, Martin, Almeida, Jorge, Alnaes, Dag, Alonso-Lana, Silvia, Altimus, Cara, Bauer, Michael, Baune, Bernhard T, Bearden, Carrie E, Bellani, Marcella, Benedetti, Francesco, Berk, Michael, Bilderbeck, Amy C, Blumberg, Hilary P, Bøen, Erlend, Bollettini, Irene, Del Mar Bonnin, Caterina, Brambilla, Paolo, Canales-Rodríguez, Erick J, Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Díaz-Zuluaga, Ana M, Dima, Danai, Duchesnay, Édouard, Elvsåshagen, Torbjørn, Fears, Scott C, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Green, Melissa J, Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus CM, Henry, Chantal, Howells, Fleur M, Ives-Deliperi, Victoria, Jansen, Andreas, Kircher, Tilo TJ, Knöchel, Christian, Kramer, Bernd, Lafer, Beny, López-Jaramillo, Carlos, Machado-Vieira, Rodrigo, MacIntosh, Bradley J, Melloni, Elisa MT, Mitchell, Philip B, Nenadic, Igor, Nery, Fabiano, Nugent, Allison C, Oertel, Viola, Ophoff, Roel A, Ota, Miho, Overs, Bronwyn J, Pham, Daniel L, Phillips, Mary L, Pineda-Zapata, Julian A, Poletti, Sara, Polosan, Mircea, Pomarol-Clotet, Edith, Pouchon, Arnaud, Quidé, Yann, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Schene, Aart H, and Sim, Kang

Subjects
mega-analysis, Bipolar Disorder, Neuroimaging, cortical surface area, Meta-Analysis as Topic, Clinical Research, Behavioral and Social Science, Humans, Multicenter Studies as Topic, Cerebral Cortex, volume, ENIGMA, Neurosciences, Experimental Psychology, ENIGMA Bipolar Disorder Working Group, cortical thickness, Serious Mental Illness, Magnetic Resonance Imaging, psychiatry, Brain Disorders, meta-analysis, Mental Health, Good Health and Well Being, Neurological, Biomedical Imaging, Cognitive Sciences, MRI
Abstract

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Published
2022

33. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs

Author

Sønderby, Ida E, Ching, Christopher R K, Ayesa-Arriola, Rosa, Thompson, Paul M, Bearden, Carrie E, Andreassen, Ole A, Group, ENIGMA-CNV Working, 2 Deletion Syndrome Working Group, ENIGMA 22q11., Bernard, Manon, Blackburn, Nicholas B, Bøen, Rune, de Geus, Eco, de Zwarte, Sonja M C, Bakker, Geor, Forti, Marta Di, Frei, Oleksandr, Fukunaga, Masaki, Hehir-Kwa, Jayne Y, Hillegers, Manon H J, Hoffmann, Per, Homuth, Georg, Jahanshad, Neda, Koops, Sanne, Kumar, Kuldeep, Bassett, Anne S, Kikuchi, Masataka, Le Hellard, Stephanie, Leu, Costin, Murray, Robin M, Naerland, Terje, Nyberg, Lars, Ophoff, Roel A, Pike, G Bruce, Sando, Sigrid B, Shin, Jean, Boomsma, Dorret I, Shumskaya, Elena, Sisodiya, Sanjay M, Steen, Vidar M, Teumer, Alexander, Uhlmann, Anne, Wright, Margaret J, Antshel, Kevin M, Campbell, Linda E, Crossley, Nicolas A, Crowley, T Blaine, Bülow, Robin, Daly, Eileen, Fiksinski, Ania M, Forsyth, Jennifer K, Fremont, Wanda, Goodrich-Hunsaker, Naomi J, Gudbrandsen, Maria, Jonas, Rachel K, Kates, Wendy R, Lin, Amy, McCabe, Kathryn L, Butcher, Nancy J, Moss, Hayley, Murphy, Declan G, Murphy, Kieran C, Owen, Michael J, Ruparel, Kosha, Simon, Tony J, van Amelsvoort, Therese, Vorstman, Jacob A S, Calhoun, Vince D, Caspers, Svenja, Chow, Eva W C, Cichon, Sven, Thomopoulos, Sophia I, Ciufolini, Simone, Craig, Michael C, Crespo-Facorro, Benedicto, Cunningham, Adam C, Dale, Anders M, Dazzan, Paola, de Zubicaray, Greig I, Djurovic, Srdjan, Doherty, Joanne L, Donohoe, Gary, van der Meer, Dennis, Draganski, Bogdan, Durdle, Courtney A, Ehrlich, Stefan, Emanuel, Beverly S, Espeseth, Thomas, Fisher, Simon E, Ge, Tian, Glahn, David C, Grabe, Hans J, Gur, Raquel E, Sun, Daqiang, Gutman, Boris A, Haavik, Jan, Håberg, Asta K, Hansen, Laura A, Hashimoto, Ryota, Hibar, Derrek P, Holmes, Avram J, Hottenga, Jouke-Jan, Hulshoff Pol, Hilleke E, Jalbrzikowski, Maria, Villalon-Reina, Julio E, Knowles, Emma E M, Kushan, Leila, Linden, David E J, Liu, Jingyu, Lundervold, Astri J, Martin-Brevet, Sandra, Martínez, Kenia, Mather, Karen A, Mathias, Samuel R, McDonald-McGinn, Donna M, Agartz, Ingrid, McRae, Allan F, Medland, Sarah E, Moberget, Torgeir, Modenato, Claudia, Monereo Sánchez, Jennifer, Moreau, Clara A, Mühleisen, Thomas W, Paus, Tomas, Pausova, Zdenka, Prieto, Carlos, Amunts, Katrin, Ragothaman, Anjanibhargavi, Reinbold, Céline S, Reis Marques, Tiago, Repetto, Gabriela M, Reymond, Alexandre, Roalf, David R, Rodriguez-Herreros, Borja, Rucker, James J, Sachdev, Perminder S, Schmitt, James E, Arango, Celso, Schofield, Peter R, Silva, Ana I, Stefansson, Hreinn, Stein, Dan J, Tamnes, Christian K, Tordesillas-Gutiérrez, Diana, Ulfarsson, Magnus O, Vajdi, Ariana, van 't Ent, Dennis, van den Bree, Marianne B M, Armstrong, Nicola J, Vassos, Evangelos, Vázquez-Bourgon, Javier, Vila-Rodriguez, Fidel, Walters, G Bragi, Wen, Wei, Westlye, Lars T, Wittfeld, Katharina, Zackai, Elaine H, Stefánsson, Kári, Jacquemont, Sebastien, the ENIGMA-CNV Working Group, the ENIGMA 22q11.2 Deletion Syndrome Working Group, Stochastics, Biological Psychology, APH - Mental Health, APH - Methodology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, ENIGMA-CNV Working Group, ENIGMA 22q11.2 Deletion Syndrome Working Group, and Universidad de Cantabria

Subjects
Review Article, genetics [Mental Disorders], 0302 clinical medicine, genetics-first approach, pathology [Brain], Multicenter Studies as Topic, Copy-number variation, Review Articles, education.field_of_study, brain structural imaging, Radiological and Ultrasound Technology, genetics [Neurodevelopmental Disorders], Mental Disorders, neurodevelopmental disorders, 05 social sciences, growth & development [Brain], Brain, pathology [Mental Disorders], Cognition, Human brain, diffusion tensor imaging, Magnetic Resonance Imaging, diagnostic imaging [Neurodevelopmental Disorders], medicine.anatomical_structure, psychiatric disorders, Neurology, Anatomy, medicine.medical_specialty, Brain development, DNA Copy Number Variations, Population, Neuroimaging, Biology, 050105 experimental psychology, 03 medical and health sciences, evolution, medicine, pathology [Neurodevelopmental Disorders], Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Deletion syndrome, copy number variant, ddc:610, genetics‐first approach, education, Psychiatry, diagnostic imaging [Brain], Neurology (clinical), Working group, 030217 neurology & neurosurgery, diagnostic imaging [Mental Disorders]
Abstract

The Enhancing NeuroImaging Genetics through Meta‐Analysis copy number variant (ENIGMA‐CNV) and 22q11.2 Deletion Syndrome Working Groups (22q‐ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA‐CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q‐ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest‐ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi‐site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene‐dosage effects on distinct brain regions also emerged, providing further insight into genotype–phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This “genotype‐first” approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior., The enhancing neuroimaging genetics through meta‐analysis (ENIGMA) copy number variant (CNV) and 22q11.2 Working Groups focus on gaining insight into how rare genetic variants affect human brain development, cognition, and behavior. The two ENIGMA working groups have collated CNV and brain‐imaging data from numerous individuals, gathered by numerous international research centers, and analyzed this data with standardized processing and analysis pipelines. Future directions for the ENIGMA CNV and 22q11.2 working groups are to analyze CNVs with larger sample sizes and more imaging modalities to better understand how rare genetic variants affect the brain, and their clinical and behavioral consequences.

Published
2021

34. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author

Committee, Writing, Disorder, Autism Spectrum, French, Leon, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Guerrero-Pedraza, Amalia, Gur, Raquel E, Gur, Ruben C, Haar, Shlomi, Haarman, Bartholomeus C M, Thomopoulos, Sophia I, Haavik, Jan, Hahn, Tim, Hajek, Tomas, Harrison, Benjamin J, Harrison, Neil A, Hartman, Catharina A, Whalley, Heather C, Heslenfeld, Dirk J, Hibar, Derrek P, Hilland, Eva, Pozzi, Elena, Hirano, Yoshiyuki, Ho, Tiffany C, Hoekstra, Pieter J, Hoekstra, Liesbeth, Hohmann, Sarah, Hong, L. E., Höschl, Cyril, Høvik, Marie F, Howells, Fleur M, Nenadic, Igor, Abe, Yoshinari, Jalbrzikowski, Maria, James, Anthony C, Janssen, Joost, Jaspers-Fayer, Fern, Xu, Jian, Jonassen, Rune, Karkashadze, Georgii, King, Joseph A, Kircher, Tilo, Kirschner, Matthias, Abé, Christoph, Koch, Kathrin, Kochunov, Peter, Kohls, Gregor, Konrad, Kerstin, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Kwon, Jun Soo, Landén, Mikael, Landrø, Nils I, Anticevic, Alan, Lazaro, Luisa, Lebedeva, Irina S, Leehr, Elisabeth J, Lera-Miguel, Sara, Lesch, Klaus-Peter, Lochner, Christine, Louza, Mario R, Luna, Beatriz, Lundervold, Astri J, MacMaster, Frank P, Alda, Martin, Maglanoc, Luigi A, Malpas, Charles B, Portella, Maria J, Marsh, Rachel, Martyn, Fiona M, Mataix-Cols, David, Mathalon, Daniel H, McCarthy, Hazel, McDonald, Colm, McPhilemy, Genevieve, Aleman, Andre, Meinert, Susanne, Menchón, José M, Minuzzi, Luciano, Mitchell, Philip B, Moreno, Carmen, Morgado, Pedro, Muratori, Filippo, Murphy, Clodagh M, Murphy, Declan, Mwangi, Benson, Alloza, Clara, Nabulsi, Leila, Nakagawa, Akiko, Nakamae, Takashi, Namazova, Leyla, Narayanaswamy, Janardhanan, Jahanshad, Neda, Nguyen, Danai D, Nicolau, Rosa, O'Gorman Tuura, Ruth L, O'Hearn, Kirsten, Alonso-Lana, Silvia, Oosterlaan, Jaap, Opel, Nils, Ophoff, Roel A, Oranje, Bob, García de la Foz, Victor Ortiz, Overs, Bronwyn J, Paloyelis, Yannis, Pantelis, Christos, Parellada, Mara, Pauli, Paul, Disorder, Bipolar, Ameis, Stephanie H, Picó-Pérez, Maria, Picon, Felipe A, Piras, Fabrizio, Piras, Federica, Plessen, Kerstin J, Pomarol-Clotet, Edith, Preda, Adrian, Puig, Olga, Quidé, Yann, Radua, Joaquim, Anagnostou, Evdokia, Ramos-Quiroga, J Antoni, Rasser, Paul E, Rauer, Lisa, Reddy, Janardhan, Redlich, Ronny, Reif, Andreas, Reneman, Liesbeth, Repple, Jonathan, Retico, Alessandra, Richarte, Vanesa, McIntosh, Andrew A, Richter, Anja, Rosa, Pedro G P, Rubia, Katya K, Hashimoto, Ryota, Sacchet, Matthew D, Salvador, Raymond, Santonja, Javier, Sarink, Kelvin, Sarró, Salvador, Satterthwaite, Theodore D, Arango, Celso, Sawa, Akira, Schall, Ulrich, Schofield, Peter R, Schrantee, Anouk, Seitz, Jochen, Serpa, Mauricio H, Setién-Suero, Esther, Shaw, Philip, Shook, Devon, Silk, Tim J, Arnold, Paul D, Sim, Kang, Simon, Schmitt, Simpson, Helen Blair, Singh, Aditya, Skoch, Antonin, Skokauskas, Norbert, Soares, Jair C, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Asherson, Philip, Spaniel, Filip, Lawrie, Stephen M, Stern, Emily R, Stewart, S Evelyn, Takayanagi, Yoichiro, Temmingh, Henk S, Tolin, David F, Tomecek, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Assogna, Francesca, Uhlmann, Anne, van Amelsvoort, Therese, van der Wee, Nic J A, van der Werff, Steven J A, van Haren, Neeltje E M, van Wingen, Guido A, Vance, Alasdair, Vázquez-Bourgon, Javier, Vecchio, Daniela, Venkatasubramanian, Ganesan, Auzias, Guillaume, Vieta, Eduard, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Völzke, Henry, von Polier, Georg G, Walton, Esther, Weickert, Thomas W, Weickert, Cynthia Shannon, Weideman, Andrea S, Ayesa-Arriola, Rosa, Wittfeld, Katharina, Wolf, Daniel H, Wu, Mon-Ju, Yang, T. T., Yang, Sikun, Yoncheva, Yuliya, Yun, Je-Yeon, Cheng, Yuqi, Zanetti, Marcus V, Ziegler, Georg C, Bakker, Geor, Franke, Barbara, Hoogman, Martine, Buitelaar, Jan K, van Rooij, Daan, Andreassen, Ole A, Ching, Christopher R K, Veltman, Dick J, Schmaal, Lianne, Stein, Dan J, van den Heuvel, Odile A, Disorder, Major Depressive, Banaj, Nerisa, Turner, Jessica A, van Erp, Theo G M, Pausova, Zdenka, Thompson, Paul M, Paus, Tomáš, Attention-Deficit/Hyperactivity Disorder, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bargalló, Núria, Bau, Claiton H D, Baumeister, Sarah, Baune, Bernhard T, Bellgrove, Mark A, Benedetti, Francesco, Disorder, Obsessive-Compulsive, Bertolino, Alessandro, Boedhoe, Premika S W, Boks, Marco, Bollettini, Irene, Del Mar Bonnin, Caterina, Borgers, Tiana, Borgwardt, Stefan, Brandeis, Daniel, Brennan, Brian P, Bruggemann, Jason M, Groups, Schizophrenia ENIGMA Working, Bülow, Robin, Busatto, Geraldo F, Calderoni, Sara, Calhoun, Vince D, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carr, Vaughan J, Cascella, Nicola, Cercignani, Mara, Patel, Yash, Chaim-Avancini, Tiffany M, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Crespo-Facorro, Benedicto, Cubillo, Ana I, Cullen, Kathryn R, Cupertino, Renata B, Daly, Eileen, Dannlowski, Udo, Parker, Nadine, Davey, Christopher G, Denys, Damiaan, Deruelle, Christine, Di Giorgio, Annabella, Dickie, Erin W, Dima, Danai, Dohm, Katharina, Ehrlich, Stefan, Ely, Benjamin A, Erwin-Grabner, Tracy, Shin, Jean, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas, Faraone, Stephen V, Fatjó-Vilas, Mar, Fedor, Jennifer M, Fitzgerald, Kate D, Ford, Judith M, Frodl, Thomas, Fu, Cynthia H Y, Howard, Derek, Fullerton, Janice M, Gabel, Matt C, Glahn, David C, Roberts, Gloria, Gogberashvili, Tinatin, Goikolea, Jose M, Gotlib, Ian H, Goya-Maldonado, Roberto, Grabe, Hans, Green, Melissa J, Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S. I., Pozzi, E., Abe, Y., Abe, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S. H., Anagnostou, E., Mcintosh, A. A., Arango, C., Arnold, P. D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C. E., Baranov, A., Bargallo, N., Bau, C. H. D., Baumeister, S., Baune, B. T., Bellgrove, M. A., Benedetti, F., Bertolino, A., Boedhoe, P. S. W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B. P., Bruggemann, J. M., Bulow, R., Busatto, G. F., Calderoni, S., Calhoun, V. D., Calvo, R., Canales-Rodriguez, E. J., Cannon, D. M., Carr, V. J., Cascella, N., Cercignani, M., Chaim-Avancini, T. M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A. I., Cullen, K. R., Cupertino, R. B., Daly, E., Dannlowski, U., Davey, C. G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E. W., Dima, D., Dohm, K., Ehrlich, S., Ely, B. A., Erwin-Grabner, T., Ethofer, T., Fair, D. A., Fallgatter, A. J., Faraone, S. V., Fatjo-Vilas, M., Fedor, J. M., Fitzgerald, K. D., Ford, J. M., Frodl, T., Fu, C. H. Y., Fullerton, J. M., Gabel, M. C., Glahn, D. C., Roberts, G., Gogberashvili, T., Goikolea, J. M., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Green, M. J., Grevet, E. H., Groenewold, N. A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R. E., Gur, R. C., Haar, S., Haarman, B. C. M., Haavik, J., Hahn, T., Hajek, T., Harrison, B. J., Harrison, N. A., Hartman, C. A., Whalley, H. C., Heslenfeld, D. J., Hibar, D. P., Hilland, E., Hirano, Y., Ho, T. C., Hoekstra, P. J., Hoekstra, L., Hohmann, S., Hong, L. E., Hoschl, C., Hovik, M. F., Howells, F. M., Nenadic, I., Jalbrzikowski, M., James, A. C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J. A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Kramer, B., Krug, A., Kuntsi, J., Kwon, J. S., Landen, M., Landro, N. I., Lazaro, L., Lebedeva, I. S., Leehr, E. J., Lera-Miguel, S., Lesch, K. -P., Lochner, C., Louza, M. R., Luna, B., Lundervold, A. J., Macmaster, F. P., Maglanoc, L. A., Malpas, C. B., Portella, M. J., Marsh, R., Martyn, F. M., Mataix-Cols, D., Mathalon, D. H., Mccarthy, H., Mcdonald, C., Mcphilemy, G., Meinert, S., Menchon, J. M., Minuzzi, L., Mitchell, P. B., Moreno, C., Morgado, P., Muratori, F., Murphy, C. M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D. D., Nicolau, R., O'Gorman Tuura, R. L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R. A., Oranje, B., Garcia De La Foz, V. O., Overs, B. J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Pico-Perez, M., Picon, F. A., Piras, F., Plessen, K. J., Pomarol-Clotet, E., Preda, A., Puig, O., Quide, Y., Radua, J., Ramos-Quiroga, J. A., Rasser, P. E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P. G. P., Rubia, K. K., Hashimoto, R., Sacchet, M. D., Salvador, R., Santonja, J., Sarink, K., Sarro, S., Satterthwaite, T. D., Sawa, A., Schall, U., Schofield, P. R., Schrantee, A., Seitz, J., Serpa, M. H., Setien-Suero, E., Shaw, P., Shook, D., Silk, T. J., Sim, K., Simon, S., Simpson, H. B., Singh, A., Skoch, A., Skokauskas, N., Soares, J. C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S. M., Stern, E. R., Stewart, S. E., Takayanagi, Y., Temmingh, H. S., Tolin, D. F., Tomecek, D., Tordesillas-Gutierrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N. J. A., Van Der Werff, S. J. A., Van Haren, N. E. M., Van Wingen, G. A., Vance, A., Vazquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A. N., Volzke, H., Von Polier, G. G., Walton, E., Weickert, T. W., Weickert, C. S., Weideman, A. S., Wittfeld, K., Wolf, D. H., Wu, M. -J., Yang, T. T., Yang, K., Yoncheva, Y., Yun, J. -Y., Cheng, Y., Zanetti, M. V., Ziegler, G. C., Franke, B., Hoogman, M., Buitelaar, J. K., Van Rooij, D., Andreassen, O. A., Ching, C. R. K., Veltman, D. J., Schmaal, L., Stein, D. J., Van Den Heuvel, O. A., Turner, J. A., Van Erp, T. G. M., Pausova, Z., Thompson, P. M., Paus, T., Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Pediatric surgery, Radiology and nuclear medicine, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Neurodegeneration, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Adult Psychiatry, ANS - Compulsivity, Impulsivity & Attention, General Paediatrics, ARD - Amsterdam Reproduction and Development, Radiology and Nuclear Medicine, APH - Personalized Medicine, ANS - Brain Imaging, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, University of Zurich, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Clinical Neuropsychology, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Child and Adolescent Psychiatry / Psychology, IBBA, and Cognitive Psychology

Subjects
Male, Obsessive-Compulsive Disorder, Bipolar Disorder, Autism Spectrum Disorder, Autism, [SDV]Life Sciences [q-bio], Gene Expression, cytology [Cerebral Cortex], Cohort Studies, Fetal Development, physiology [Gene Expression], 2738 Psychiatry and Mental Health, 0302 clinical medicine, diagnostic imaging [Cerebral Cortex], SCHIZOPHRENIA, BRAIN, Child, Obsessive-compulsive disorder (OCD), Original Investigation, Aged, 80 and over, Cerebral Cortex, 0303 health sciences, pathology [Depressive Disorder, Major], Principal Component Analysis, Adolescent psychiatry, 10058 Department of Child and Adolescent Psychiatry, Middle Aged, diagnostic imaging [Obsessive-Compulsive Disorder], REGIONS, Magnetic Resonance Imaging, 3. Good health, FALSE DISCOVERY RATE, Psychiatry and Mental health, Autism spectrum disorder, Schizophrenia, growth & development [Cerebral Cortex], Child, Preschool, Major depressive disorder, diagnostic imaging [Schizophrenia], Esquizofrènia, Female, Psiquiatria infantil, Psiquiatria de l'adolescència, diagnostic imaging [Autism Spectrum Disorder], Adult, medicine.medical_specialty, Adolescent, Human Development, 610 Medicine & health, diagnostic imaging [Bipolar Disorder], pathology [Autism Spectrum Disorder], diagnostic imaging [Depressive Disorder, Major], 03 medical and health sciences, Young Adult, All institutes and research themes of the Radboud University Medical Center, Neuroimaging, SDG 3 - Good Health and Well-being, CEREBRAL-CORTEX, Child psychiatry, medicine, Attention deficit hyperactivity disorder, Humans, Bipolar disorder, ddc:610, Psychiatry, pathology [Schizophrenia], 030304 developmental biology, Aged, Depressive Disorder, Major, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, DENDRITE, Computational Biology, Correction, pathology [Attention Deficit Disorder with Hyperactivity], physiology [Fetal Development], medicine.disease, PATHOLOGY, pathology [Bipolar Disorder], pathology [Obsessive-Compulsive Disorder], 10036 Medical Clinic, Attention Deficit Disorder with Hyperactivity, 10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics, Case-Control Studies, DENSITY, ORIGINS, HIPPOCAMPUS, diagnostic imaging [Attention Deficit Disorder with Hyperactivity], pathology [Cerebral Cortex], Autisme, business, Neuroscience, 030217 neurology & neurosurgery, physiology [Human Development]
Abstract

[Importance] Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., [Objective] To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., [Design, Setting, and Participants] Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., [Main Outcomes and Measures] Interregional profiles of group difference in cortical thickness between cases and controls., [Results] A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., [Conclusions and Relevance] In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Published
2021

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

Author

Sønderby, Ida E., Gústafsson, Ómar, Doan, Nhat Trung, Hibar, Derrek P., Martin-Brevet, Sandra, Abdellaoui, Abdel, Crespo Facorro, Benedicto, Prieto, Carlos, Universidad de Sevilla. Departamento de Psiquiatría, NCRR NIH HHS, NIBIB NIH HHS, NICHD NIH HHS, NIGMS NIH HHS, and NIMH NIH HHS

Subjects
Deletion, Dosage, Phenotype, Autism, Duplications, Microdeletion syndrome, Microduplication, Magnetic Resonance Imaging, Intracranial, Gene, Basal Ganglia
Abstract

Erratum: Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia (Molecular psychiatry (2020) 25 3 (584-602)) 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

Published
2020

36. Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

Author

Walton, E, Hibar, D, Yilmaz, Z, Jahanshad, N, Cheung, J, Batury, V-L, Seitz, J, Bulik, CM, Thompson, PM, Ehrlich, Stefan, Hibar, Derrek P, Stein, Jason L, Renteria, Miguel E, Arias-Vasquez, Alejandro, Desrivieres, Sylvane, Jahanshad, Neda, Toro, Roberto, Wittfeld, Katharina, Abramovic, Lucija, Andersson, Micael, Aribisala, Benjamin S, Armstrong, Nicola J, Bernard, Manon, Bohlken, Marc M, Boks, Marco P, Bralten, Janita, Brown, Andrew A, Chakravarty, M Mallar, Chen, Qiang, Ching, Christopher RK, Cuellar-Partida, Gabriel, Den Braber, Anouk, Giddaluru, Sudheer, Goldman, Aaron L, Grimm, Oliver, Guadalupe, Tulio, Hass, Johanna, Woldehawariat, Girma, Holmes, Avram J, Hoogman, Martine, Janowitz, Deborah, Jia, Tianye, Kim, Sungeun, Klein, Marieke, Kraemer, Bernd, Lee, Phil H, Loohuis, Loes M Olde, Luciano, Michelle, Macare, Christine, Mather, Karen A, Mattheisen, Manuel, Milaneschi, Yuri, Nho, Kwangsik, Papmeyer, Martina, Ramasamy, Adaikalavan, Risacher, Shannon L, Roiz-Santianez, Roberto, Rose, Emma J, Salami, Alireza, Samann, Philipp G, Schmaal, Lianne, Schork, Andrew J, Shin, Jean, Strike, Lachlan T, Teumer, Alexander, van Donkelaar, Marjolein MJ, van Eijk, Kristel R, Walters, Raymond K, Westlye, Lars T, Whelan, Christopher D, Winkler, Anderson M, Zwiers, Marcel P, Alhusaini, Saud, Athanasiu, Lavinia, Hakobjan, Marina MH, Hartberg, Cecilie B, Haukvik, Unn K, Heister, Angelien JGAM, Hohn, David, Kasperaviciute, Dalia, Liewald, David CM, Lopez, Lorna M, Makkinje, Remco RR, Matarin, Mar, Naber, Marlies AM, Mckay, David R, Needham, Margaret, Nugent, Allison C, Putz, Benno, Shen, Li, Sprooten, Emma, Trabzuni, Daniah, van der Marel, Saskia SL, van Hulzen, Kimm JE, Walton, Esther, Wolf, Christiane, Almasy, Laura, Ames, David, Arepalli, Sampath, Assareh, Amelia A, Bastin, Mark E, Brodaty, Henry, Bulayeva, Kazima B, Carless, Melanie A, Cichon, Sven, Corvin, Aiden, Curran, Joanne E, Czisch, Michael, de Zubicaray, Greig I, Dillman, Allissa, Duggirala, Ravi, Dyer, Thomas D, Erk, Susanne, Fedko, Iryna O, Ferrucci, Luigi, Foroud, Tatiana M, Fox, Peter T, Fukunaga, Masaki, Gibbs, J Raphael, Goring, Harald HH, Green, Robert C, Guelfi, Sebastian, Hansell, Narelle K, Hartman, Catharina A, Hegenscheid, Katrin, Heinz, Andreas, Hernandez, Dena G, Heslenfeld, Dirk J, Hoekstra, Pieter J, Holsboer, Florian, Homuth, Georg, Hottenga, Jouke-Jan, Ikeda, Masashi, Jr, Jack Clifford R, Jenkinson, Mark, Johnson, Robert, Kanai, Ryota, Keil, Maria, Jr, Kent Jack W, Kochunov, Peter, Kwok, John B, Lawrie, Stephen M, Liu, Xinmin, Longo, Dan L, McMahon, Katie L, Meisenzahl, Eva, Melle, Ingrid, Mohnke, Sebastian, Montgomery, Grant W, Mostert, Jeanette C, Muhleisen, Thomas W, Nalls, Michael A, Nichols, Thomas E, Nilsson, Lars G, Nothen, Markus M, Ohi, Kazutaka, Olvera, Rene L, Perez-Iglesias, Rocio, Pike, G Bruce, Potkin, Steven G, Reinvang, Ivar, Reppermund, Simone, Rietschel, Marcella, Romanczuk-Seiferth, Nina, Rosen, Glenn D, Rujescu, Dan, Schnell, Knut, Schofield, Peter R, Smith, Colin, Steen, Vidar M, Sussmann, Jessika E, Thalamuthu, Anbupalam, Toga, Arthur W, Traynor, Bryan J, Troncoso, Juan, Turner, Jessica A, Hernandez, Maria C Valdes, van't Ent, Dennis, van der Brug, Marcel, van der Wee, Nic JA, van Tol, Marie-Jose, Veltman, Dick J, Wassink, Thomas H, Westman, Eric, Zielke, Ronald H, Zonderman, Alan B, Ashbrook, David G, Hager, Reinmar, Lu, Lu, McMahon, Francis J, Morris, Derek W, Williams, Robert W, Brunner, Han G, Buckner, Randy L, Buitelaar, Jan K, Cahn, Wiepke, Calhoun, Vince D, Cavalleri, Gianpiero L, Crespo-Facorro, Benedicto, Dale, Anders M, Davies, Gareth E, Delanty, Norman, Depondt, Chantal, Djurovic, Srdjan, Drevets, Wayne C, Espeseth, Thomas, Gollub, Randy L, Ho, Beng-Choon, Hoffmann, Wolfgang, Hosten, Norbert, Kahn, Rene S, Le Hellard, Stephanie, Meyer-Lindenberg, Andreas, Mueller-Myhsok, Bertram, Nauck, Matthias, Nyberg, Lars, Pandolfo, Massimo, Penninx, Brenda WJH, Roffman, Joshua L, Sisodiya, Sanjay M, Smoller, Jordan W, van Bokhoven, Hans, van Haren, Neeltje EM, Volzke, Henry, Walter, Henrik, Weiner, Michael W, Wen, Wei, White, Tonya, Agartz, Ingrid, Andreassen, Ole A, Blangero, John, Boomsma, Dorret I, Brouwer, Rachel M, Cannon, Dara M, Cookson, Mark R, de Geus, Eco JC, Deary, Ian J, Donohoe, Gary, Fernandez, Guillen, Fisher, Simon E, Francks, Clyde, Glahn, David C, Grabe, Hans J, Gruber, Oliver, Hardy, John, Hashimoto, Ryota, Pol, Hilleke E Hulshoff, Jonsson, Erik G, Kloszewska, Iwona, Lovestone, Simon, Mattay, Venkata S, Mecocci, Patrizia, McDonald, Colm, McIntosh, Andrew M, Ophoff, Roel A, Paus, Tomas, Pausova, Zdenka, Ryten, Mina, Sachdev, Perminder S, Saykin, Andrew J, Simmons, Andrew, Singleton, Andrew, Soininen, Hilkka, Wardlaw, Joanna M, Weale, Michael E, Weinberger, Daniel R, Adams, Hieab HH, Launer, Lenore J, Seiler, Stephan, Schmidt, Reinhold, Chauhan, Ganesh, Satizabal, Claudia L, Becker, James T, Yanek, Lisa R, van der Lee, Sven J, Ebling, Maritza, Fischl, Bruce, Longstreth, WT, Greve, Douglas, Schmidt, Helena, Nyquist, Paul, Vinke, Louis N, van Duijn, Cornelia M, Luting, Xue, Mazoyer, Bernard, Bis, Joshua C, Gudnason, Vilmundur, Seshadri, Sudha, Ikram, M Arfan, Martin, Nicholas G, Wright, Margaret J, Schumann, Gunter, Franke, Barbara, Thompson, Paul M, Medland, Sarah E, Duncan, Laramie, Yilmaz, Zeynep, Walters, Raymond, Goldstein, Jackie, Anttila, Verneri, Bulik-Sullivan, Brendan, Ripke, Stephan, Adan, Roger, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole, Aschauer, Harald, Baker, Jessica, Barrett, Jeffrey, Bencko, Vladimir, Bergen, Andrew, Berrettini, Wade, Birgegard, Andreas, Boni, Claudette, Perica, Vesna Boraska, Brandt, Harry, Burghardt, Roland, Carlberg, Laura, Cassina, Matteo, Cichon, Carolyn Cesta Sven, Clementi, Maurizio, Cohen-Woods, Sarah, Coleman, Joni, Cone, Roger, Courtet, Philippe, Crawford, Steven, Crow, Scott, Crowley, Jim, Danner, Unna, Davis, Oliver, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece, Dick, Danielle, Dikeos, Dimitris, Dina, Christian, Ding, Bo, Dmitrzak-Weglarz, Monika, Docampo, Elisa, Egberts, Karin, Escaramis, Georgia, Esko, Tonu, Estivill, Xavier, Favaro, Angela, Fernandez-Aranda, Fernando, Fichter, Manfred, Finan, Chris, Fischer, Krista, Floyd, James, Focker, Manuel, Foretova, Lenka, Forzan, Monica, Fox, Caroline, Franklin, Christopher, Gallinger, Valerie Gaborieau Steven, Gambaro, Giovanni, Gaspar, Helena, Giegling, Ina, Gonidakis, Fragiskos, Gorwood, Philip, Gratacos, Monica, Guillaume, Sebastien, Guo, Yiran, Hakonarson, Hakon, Halmi, Katherine, Harrison, Rebecca, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske, Hendriks, Judith, Herms, Stefan, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hilliard, Christopher, Huckins, Laura, Hudson, James, Huemer, Julia, Imgart, Hartmut, Inoko, Hidetoshi, Jamain, Sigrid Jall Stephane, Janout, Vladimir, Jimenez-Murcia, Susana, Johnson, Craig, Jordan, Jenny, Julia, Antonio, Jureus, Anders, Kalsi, Gursharan, Kaplan, Allan, Kaprio, Jaakko, Karhunen, Leila, Karwautz, Andreas, Kas, Martien, Kaye, Walter, Kennedy, Martin, Kennedy, James, Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl-Ri, Klareskog, Lars, Klump, Kelly, Knudsen, Gun Peggy, Koeleman, Bobby, Koubek, Doris, La Via, Maria, Landen, Mikael, Leboyer, Marion, Levitan, Robert, Li, Dong, Lichtenstein, Paul, Lilenfeld, Lisa, Lissowska, Jolanta, Lundervold, Astri, Magistretti, Pierre, Maj, Mario, Mannik, Katrin, Marsal, Sara, Kaminska, Debora, Martin, Nicholas, Mattingsdal, Morten, McDevitt, Sara, McGuffin, Peter, Merl, Elisabeth, Metspalu, Andres, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, James, Mitchell, Karen, Monteleone, Palmiero, Monteleone, Alessio Maria, Montgomery, Grant, Mortensen, Preben, Munn-Chernoff, Melissa, Mueller, Timo, Nacmias, Benedetta, Navratilova, Marie, Nilsson, Ida, Norring, Claes, Ntalla, Ioanna, Ophoff, Roel, O'Toole, Julie, Palotie, Aarno, Pantel, Jacques, Papezova, Hana, Pinto, Richard Parker Dalila, Rabionet, Raquel, Raevuori, Anu, Rajewski, Andrzej, Ramoz, Nicolas, Rayner, N William, Reichborn-Kjennerud, Ted, Ricca, Valdo, Ripatti, Samuli, Ritschel, Franziska, Roberts, Marion, Rotondo, Alessandro, Rybakowski, Filip, Santonastaso, Paolo, Scherag, Andre, Scherer, Stephen, Schmidt, Ulrike, Schork, Nicholas, Schosser, Alexandra, Scott, Laura, Seitz, Jochen, Slachtova, Lenka, Sladek, Robert, Slagboom, P Eline, Slof-Op't Landt, Margarita, Slopien, Agnieszka, Smith, Tosha, Soranzo, Nicole, Sorbi, Sandro, Southam, Lorraine, Steen, Vidar, Strengman, Eric, Strober, Michael, Szatkiewicz, Jin, Szeszenia-Dabrowska, Neonila, Tachmazidou, Ioanna, Tenconi, Elena, Tortorella, Alfonso, Tozzi, Federica, Treasure, Janet, Tschop, Matthias, Tsitsika, Artemis, Tziouvas, Konstantinos, van Elburg, Annemarie, van Furth, Eric, Wade, Tracey, Wagner, Gudrun, Watson, Hunna, Wichmann, H-Erich, Widen, Elisabeth, Woodside, D Blake, Yanovski, Jack, Yao, Shuyang, Zerwas, Stephanie, Zipfel, Stephan, Thornton, Laura, Hinney, Anke, Breen, Gerome, Bulik, Cynthia M, PGC-ED, Grp, ENIGMA Genetics Working, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Kas lab, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, and APH - Mental Health

Subjects
0301 basic medicine, Anorexia Nervosa, Eating Disorders, REWARD CIRCUITRY, Genome-wide association study, ADOLESCENT, PGC-ED, Bioinformatics, Linkage Disequilibrium, 0302 clinical medicine, Anorexia nervosa, Brain structure, Genetic correlation, SCHIZOPHRENIA, ENIGMA Genetics Working Group, 2.1 Biological and endogenous factors, Psychology, Aetiology, Cervell, RISK, ABNORMALITIES, Anorèxia nerviosa, Brain, FUNCTIONAL CONNECTIVITY, Organ Size, Single Nucleotide, Serious Mental Illness, Magnetic Resonance Imaging, 3. Good health, Anorexia, Mental Health, Neurology, Anorexia nervosa (differential diagnoses), Brain size, MENDELIAN RANDOMIZATION, Biomedical Imaging, Cognitive Sciences, RESPONSE-INHIBITION, Neuroscience (miscellaneous), Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Mendelian randomization, Journal Article, Genetics, Humans, Genetic Testing, GENOME-WIDE ASSOCIATION, Polymorphism, POLYMORPHISMS, Genetic association, Neurology & Neurosurgery, Prevention, Human Genome, Neurosciences, Mendelian Randomization Analysis, Genetic architecture, Brain Disorders, 030104 developmental biology, Genetic marker, Case-Control Studies, 030217 neurology & neurosurgery, Genètica, Genome-Wide Association Study
Abstract

Molecular neurobiology 56(7), 5146-5156 (2019). doi:10.1007/s12035-018-1439-4, Published by Humana Press, Totowa, NJ

Published
2019

37. Cortical Abnormalities Associated With Pediatric and Adult Obsessive-Compulsive Disorder: Findings From the ENIGMA Obsessive-Compulsive Disorder Working Group

Author

Boedhoe, Premika SW, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Hanna, Gregory L, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nishida, Seiji, Nurmi, Erika, O'Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Reess, Tim J, Sakai, Yuki, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, van Wingen, Guido A, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, ENIGMA-OCD Working Group, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, and ENIGMA OCD Working Group

Subjects
Adult, Obsessive-Compulsive Disorder, ENIGMA OCD Working Group, Adolescent, FreeSurfer, Medical and Health Sciences, Young Adult, Reference Values, Parietal Lobe, Humans, Age of Onset, Child, Cerebral Cortex, Pediatric, Psychiatry, Cortical Thickness, Psychology and Cognitive Sciences, Neurosciences, Surface Area, Serious Mental Illness, Magnetic Resonance Imaging, Temporal Lobe, Frontal Lobe, Brain Disorders, Mental Health, Neurological, ENIGMA-OCD Working Group, MRI
Abstract

ObjectiveBrain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken.MethodT1-weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using FreeSurfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume.ResultsIn adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortex and a thinner inferior parietal cortex. Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showed significant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from -0.10 to -0.33.ConclusionsThe parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were found in medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication.

Published
2018

38. Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Author

Whelan, Christopher D, Altmann, Andre, Botía, Juan A, Jahanshad, Neda, Hibar, Derrek P, Absil, Julie, Alhusaini, Saud, Alvim, Marina K M, Auvinen, Pia, Bartolini, Emanuele, Bergo, Felipe P G, Bernardes, Tauana, Blackmon, Karen, Braga, Barbara, Caligiuri, Maria Eugenia, Calvo, Anna, Carr, Sarah J, Chen, Jian, Chen, Shuai, Cherubini, Andrea, David, Philippe, Domin, Martin, Foley, Sonya, França, Wendy, Haaker, Gerrit, Isaev, Dmitry, Keller, Simon S, Kotikalapudi, Raviteja, Kowalczyk, Magdalena A, Kuzniecky, Ruben, Langner, Soenke, Lenge, Matteo, Leyden, Kelly M, Liu, Min, Loi, Richard Q, Martin, Pascal, Mascalchi, Mario, Morita, Marcia E, Pariente, Jose C, Rodríguez-Cruces, Raul, Rummel, Christian, Saavalainen, Taavi, Semmelroch, Mira K, Severino, Mariasavina, Thomas, Rhys H, Tondelli, Manuela, Tortora, Domenico, Vaudano, Anna Elisabetta, Vivash, Lucy, von Podewils, Felix, Wagner, Jan, Weber, Bernd, Yao, Yi, Yasuda, Clarissa L, Zhang, Guohao, Bargalló, Nuria, Bender, Benjamin, Bernasconi, Neda, Bernasconi, Andrea, Bernhardt, Boris C, Blümcke, Ingmar, Carlson, Chad, Cavalleri, Gianpiero L, Cendes, Fernando, Concha, Luis, Delanty, Norman, Depondt, Chantal, Devinsky, Orrin, Doherty, Colin P, Focke, Niels K, Gambardella, Antonio, Guerrini, Renzo, Hamandi, Khalid, Jackson, Graeme D, Kälviäinen, Reetta, Kochunov, Peter, Kwan, Patrick, Labate, Angelo, McDonald, Carrie R, Meletti, Stefano, O'Brien, Terence J, Ourselin, Sebastien, Richardson, Mark P, Striano, Pasquale, Thesen, Thomas, Wiest, Roland, Zhang, Junsong, Vezzani, Annamaria, Ryten, Mina, Thompson, Paul M, and Sisodiya, Sanjay M

Subjects
Adult, Male, Brain Mapping, International Cooperation, Current Literature In Clinical Sciences, Brain, 610 Medicine & health, Original Articles, Magnetic Resonance Imaging, epilepsy, MRI, precentral gyrus, thalamus, Cross-Sectional Studies, Meta-Analysis as Topic, Image Processing, Computer-Assisted, Humans, Female, Correlation of Data, Neurology (clinical)
Abstract

Structural MRI abnormalities are inconsistently reported in epilepsy. In the largest neuroimaging study to date, Whelan et al. report robust structural alterations across and within epilepsy syndromes, including shared volume loss in the thalamus, and widespread cortical thickness differences. The resulting neuroanatomical map will guide prospective studies of disease progression., Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10−4), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10−6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10−19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10−4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10−4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10−4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10−4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Published
2018

39. Genetic influences on individual differences in longitudinal changes in global and subcortical brain volumes: results of the ENIGMA Plasticity Working Group

Author

Brouwer, Rachel M, Panizzon, Matthew S, Glahn, David C, Hibar, Derrek P, Hua, Xue, Jahanshad, Neda, Abramovic, Lucija, De Zubicaray, Greig I, Franz, Carol E, Hansell, Narelle K, Hickie, Ian B, Koenis, Marinka M G, Martin, Nicholas G, Mather, Karen A, McMahon, Katie L, Schnack, Hugo G, Strike, Lachlan T, Swagerman, Suzanne C, Thalamuthu, Anbupalam, Wen, Wei, Gilmore, John H, Gogtay, Nitin, Kahn, René S, Sachdev, Perminder S, Wright, Margaret J, Boomsma, Dorret I, Kremen, William S, Thompson, Paul M, Hulshoff Pol, Hilleke E, Biological Psychology, APH - Mental Health, APH - Methodology, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
Netherlands Twin Register (NTR), Biological Variation, Individual, Models, Genetic, Models, Neurological, Brain, Organ Size, Magnetic Resonance Imaging, Article, Quantitative Trait, Heritable, Journal Article, Humans, Twin Studies as Topic, Gene-Environment Interaction, sense organs, Longitudinal Studies, skin and connective tissue diseases
Abstract

Structural brain changes that occur during development and ageing are related to mental health and general cognitive functioning. Individuals differ in the extent to which their brain volumes change over time, but whether these differences can be attributed to differences in their genotypes has not been widely studied. Here we estimate heritability (h(2) ) of changes in global and subcortical brain volumes in five longitudinal twin cohorts from across the world and in different stages of the lifespan (N = 861). Heritability estimates of brain changes were significant and ranged from 16% (caudate) to 42% (cerebellar gray matter) for all global and most subcortical volumes (with the exception of thalamus and pallidum). Heritability estimates of change rates were generally higher in adults than in children suggesting an increasing influence of genetic factors explaining individual differences in brain structural changes with age. In children, environmental influences in part explained individual differences in developmental changes in brain structure. Multivariate genetic modeling showed that genetic influences of change rates and baseline volume significantly overlapped for many structures. The genetic influences explaining individual differences in the change rate for cerebellum, cerebellar gray matter and lateral ventricles were independent of the genetic influences explaining differences in their baseline volumes. These results imply the existence of genetic variants that are specific for brain plasticity, rather than brain volume itself. Identifying these genes may increase our understanding of brain development and ageing and possibly have implications for diseases that are characterized by deviant developmental trajectories of brain structure. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

Published
2017

40. Heritability and reliability of automatically segmented human hippocampal formation subregions

Author

Whelan, Christopher D., Hibar, Derrek P., van Velzen, Laura S., Zannas, Anthony S., Carrillo-Roa, Tania, McMahon, Katie, Prasad, Gautam, Kelly, Sinéad, Faskowitz, Joshua, deZubiracay, Greig, Iglesias, Juan E., van Erp, Theo G.M., Frodl, Thomas, Martin, Nicholas G., Wright, Margaret J., Jahanshad, Neda, Schmaal, Lianne, Sämann, Philipp G., Thompson, Paul M., for the Alzheimer's Disease Neuroimaging Initiative, Psychiatry, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
Adult, Male, 0301 basic medicine, Intraclass correlation, Imaging genetics, IN-VIVO MRI, Cognitive Neuroscience, Neuroimaging, Hippocampal formation, SURFACE-BASED ANALYSIS, Hippocampus, Article, 03 medical and health sciences, AUTOMATED SEGMENTATION, 0302 clinical medicine, Alzheimer Disease, TEMPORAL-LOBE EPILEPSY, Image Processing, Computer-Assisted, medicine, Humans, COMPUTATIONAL ATLAS, Aged, Aged, 80 and over, Depressive Disorder, Subiculum, HIGH-RESOLUTION MRI, COMMON VARIANTS, MAJOR DEPRESSION, Middle Aged, medicine.disease, Anxiety Disorders, Magnetic Resonance Imaging, ALZHEIMERS-DISEASE, Phenotype, 030104 developmental biology, Neurology, Schizophrenia, Endophenotype, SUBCORTICAL BRAIN VOLUMES, Female, Psychology, Neuroscience, Algorithms, Software, 030217 neurology & neurosurgery, Alzheimer's Disease Neuroimaging Initiative
Abstract

Available online 30 December 2015 The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregionmeasuresmay provide additional insight. Here, we evaluated the test–retest reliability and transplatform reliability (1.5 T versus 3 T) of the subregion segmentationmodule in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N= 39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N =163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP,N=598).We also investigated agreement between themost recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h2) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test–retest reliability was high for all twelve subregions in the 3 T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70–0.97) andmoderate-to-high in the 4 TQTIM sample (ICC=0.5–0.89). Transplatform reliabilitywas strong for eleven of the twelve subregions (ICC=0.66–0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5 T and 3 T field strengths (ICC = 0.47–0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC = 0.78–0.84; Dice Similarity Coefficient (DSC)=0.55–0.70), and poor for all other subregions (ICC=0.34–0.81; DSC=0.28–0.51). All hippocampal subregion volumes were highly heritable (h2=0.67–0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium. This work was supported in part by a Consortium grant (U54 EB020403) from the NIH contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB. The study also received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska- Curie grant agreement No 654911 (project “THALAMODEL”). Juan Eugenio Iglesias also acknowledges financial support from the Gipuzkoako Foru Aldundia (Fellows Gipuzkoa Program) and the Spanish Ministry of Economy and Competitiveness grant TEC2014-51882-P. Data collection and sharing for this projectwas funded in part by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, theNational Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

Published
2016

41. Identification of common variants associated with human hippocampal and intracranial volumes

Author

Stein, Jason L, Medland, Sarah E, Bernard, Manon, Nauck, Matthias, Nöthen, Markus M., Olvera, Rene L, Pandolfo, Massimo, Pike, G Bruce, Puls, Ralf, Reinvang, Ivar, Rentería, Miguel E, Rietschel, Marcella, Roffman, Joshua L, Brown, Andrew A, Royle, Natalie A, Rujescu, Dan, Savitz, Jonathan, Schnack, Hugo G, Schnell, Knut, Seiferth, Nina, Smith, Colin, Steen, Vidar M, Valdés Hernández, Maria C, Van den Heuvel, Martijn, Cannon, Dara M, van der Wee, Nic J, Van Haren, Neeltje E M, Veltman, Joris A, Völzke, Henry, Walker, Robert, Westlye, Lars T, Whelan, Christopher D, Agartz, Ingrid, Boomsma, Dorret I, Cavalleri, Gianpiero L, Chakravarty, M Mallar, Dale, Anders M, Djurovic, Srdjan, Drevets, Wayne C, Hagoort, Peter, Hall, Jeremy, Heinz, Andreas, Jack, Clifford R, Foroud, Tatiana M, Le Hellard, Stephanie, Macciardi, Fabio, Christoforou, Andrea, Montgomery, Grant W, Poline, Jean Baptiste, Porteous, David J, Sisodiya, Sanjay M, Starr, John M, Sussmann, Jessika, Toga, Arthur W, Veltman, Dick J, Walter, Henrik, Weiner, Michael W, Domin, Martin, Initiative, Alzheimer's Disease Neuroimaging, Consortium, EPIGEN, Consortium, IMAGEN, Group, Saguenay Youth Study, Bis, Joshua C, Ikram, M Arfan, Smith, Albert V, Gudnason, Vilmundur, Tzourio, Christophe, Vernooij, Meike W, Grimm, Oliver, Launer, Lenore J, DeCarli, Charles, Seshadri, Sudha, Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology, Andreassen, Ole A, Apostolova, Liana G, Bastin, Mark E, Blangero, John, Brunner, Han G, Buckner, Randy L, Hollinshead, Marisa, Cichon, Sven, Coppola, Giovanni, de Zubicaray, Greig I, Deary, Ian J, Donohoe, Gary, de Geus, Eco J C, Espeseth, Thomas, Fernández, Guillén, Glahn, David C, Grabe, Hans J, Holmes, Avram J, Hardy, John, Hulshoff Pol, Hilleke E, Jenkinson, Mark, Kahn, René S, McDonald, Colm, McIntosh, Andrew M, McMahon, Francis J, McMahon, Katie L, Meyer-Lindenberg, Andreas, Morris, Derek W, Homuth, Georg, Müller-Myhsok, Bertram, Nichols, Thomas E, Ophoff, Roel A, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda W, Potkin, Steven G, Sämann, Philipp G, Saykin, Andrew J, Schumann, Gunter, Vasquez, Alejandro Arias, Hottenga, Jouke-Jan, Smoller, Jordan W, Wardlaw, Joanna M, Weale, Michael E, Martin, Nicholas G, Franke, Barbara, Wright, Margaret J, Thompson, Paul M, Consortium, Enhancing Neuro Imaging Genetics through Meta-Analysis, Weiner, Michael, Aisen, Paul, Langan, Camilla, Petersen, Ronald, Jagust, William, Trojanowki, John Q, Beckett, Laurel, Green, Robert C, Morris, John, Liu, Enchi, Lopez, Lorna M, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Hansell, Narelle K, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Hwang, Kristy S, Thompson, Paul, Schuff, Norbert, Alexander, Gene, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Kim, Sungeun, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, J. Q., Shaw, Les, Lee, Virginia M Y, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Laje, Gonzalo, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lee, Phil H, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Liu, Xinmin, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Loth, Eva, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, Mitsis, Effie, Romirowsky, Aliza, deToledo-Morrell, Leyla, Hibar, Derrek P, Lourdusamy, Anbarasu, Shah, Raj C, Duara, Ranjan, Varon, Daniel, Roberts, Peggy, Albert, Marilyn, Onyike, Chiadi, Kielb, Stephanie, Rusinek, Henry, de Leon, Mony J, Glodzik, Lidia, Mattingsdal, Morten, De Santi, Susan, Doraiswamy, P Murali, Petrella, Jeffrey R, Coleman, R Edward, Arnold, Steven E, Karlawish, Jason H, Wolk, David, Smith, Charles D, Jicha, Greg, Hardy, Peter, Mohnke, Sebastian, Lopez, Oscar L, Oakley, MaryAnn, Simpson, Donna M, Porsteinsson, Anton P, Goldstein, Bonnie S, Martin, Kim, Makino, Kelly M, Ismail, M Saleem, Mulnard, Ruth A, Thai, Gaby, Maniega, Susana Muñoz, Mc-Adams-Ortiz, Catherine, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Diaz-Arrastia, Ramon, King, Richard, Weiner, Myron, Martin-Cook, Kristen, DeVous, Michael, Levey, Allan I, Nho, Kwangsik, Lah, James J, Cellar, Janet S, Burns, Jeffrey M, Anderson, Heather S, Swerdlow, Russell H, Apostolova, Liana, Lu, Po H, Bartzokis, George, Silverman, Daniel H S, Graff-Radford, Neill R, Nugent, Allison C, Parfitt, Francine, Johnson, Heather, Farlow, Martin R, Hake, Ann Marie, Matthews, Brandy R, Herring, Scott, van Dyck, Christopher H, Carson, Richard E, MacAvoy, Martha G, Chertkow, Howard, O'Brien, Carol, Bergman, Howard, Hosei, Chris, Black, Sandra, Stefanovic, Bojana, Caldwell, Curtis, Hsiung, Ging-Yuek Robin, Feldman, Howard, Mudge, Benita, Assaly, Michele, Kertesz, Andrew, Papmeyer, Martina, Rogers, John, Trost, Dick, Bernick, Charles, Munic, Donna, Kerwin, Diana, Mesulam, Marek-Marsel, Lipowski, Kristina, Wu, Chuang-Kuo, Johnson, Nancy, Sadowsky, Carl, Pütz, Benno, Martinez, Walter, Villena, Teresa, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, Sperling, Reisa A, Johnson, Keith A, Marshall, Gad, Frey, Meghan, Yesavage, Jerome, Ramasamy, Adaikalavan, Taylor, Joy L, Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Sabbagh, Marwan, Belden, Christine, Jacobson, Sandra, Kowall, Neil, Killiany, Ronald, Budson, Andrew E, Senstad, Rudy E, Rasmussen, Jerod, Norbash, Alexander, Johnson, Patricia Lynn, Obisesan, Thomas O, Wolday, Saba, Bwayo, Salome K, Lerner, Alan, Hudson, Leon, Ogrocki, Paula, Fletcher, Evan, Carmichael, Owen, Rijpkema, Mark, Olichney, John, Kittur, Smita, Borrie, Michael, Lee, T-Y, Bartha, Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M, Risacher, Shannon L, Preda, Adrian, Nguyen, Dana, Tariot, Pierre, Fleisher, Adam, Reeder, Stephanie, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Scharre, Douglas W, Kataki, Maria, Roddey, J Cooper, Zimmerman, Earl A, Celmins, Dzintra, Brown, Alice D, Pearlson, Godfrey D, Blank, Karen, Anderson, Karen, Santulli, Robert B, Schwartz, Eben S, Sink, Kaycee M, Rose, Emma J, Williamson, Jeff D, Garg, Pradeep, Watkins, Franklin, Ott, Brian R, Querfurth, Henry, Tremont, Geoffrey, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Rosen, Howard J, Ryten, Mina, Miller, Bruce L, Mintzer, Jacobo, Longmire, Crystal Flynn, Spicer, Kenneth, Finger, Elizabeth, Rachinsky, Irina, Drost, Dick, Cavalleri, Gianpiero, Alhusaini, Saud, Delanty, Norman, Whelan, Christopher, Sisodiya, Sanjay, Kasperaviciute, Dalia, Matarin, Mar, Depondt, Chantal, Goldstein, David B, Heinzen, Erin L, Shianna, Kevin, Sprooten, Emma, Radtke, Rodney, Ottmann, Ruth, Sergievsky, G. H., Schumann, G., Conrod, P., Reed, L., Barker, G., Williams, S., Loth, E., Struve, M., Strengman, Eric, Lourdusamy, A., Cattrell, A., Nymberg, C., Topper, L., Smith, L., Havatzias, S., Stueber, K., Mallik, C., Stacey, D., Wong, C Peng, Teumer, Alexander, Werts, H., Andrew, C., Desrivieres, S., Heinz, A., Gallinat, J., Häke, I., Ivanov, N., Klär, A., Reuter, J., Winkler, Anderson M, Trabzuni, Daniah, Palafox, C., Hohmann, C., Schilling, C., Lüdemann, K., Romanowski, A., Ströhle, A., Wolff, E., Rapp, M., Ittermann, B., Brühl, R., Turner, Jessica, Ihlenfeld, A., Walaszek, B., Schubert, F., Garavan, H., Connolly, C., Jones, J., Lalor, E., McCabe, E., Ní Shiothcháin, A., Whelan, R., van Eijk, Kristel, Spanagel, R., Leonardi-Essmann, F., Sommer, W., Flor, H., Vollstaedt-Klein, S., Nees, F., Banaschewski, T., Poustka, L., Steiner, S., Mann, K., van Erp, Theo G M, Buehler, M., Rietschel, M., Stolzenburg, E., Schmal, C., Schirmbeck, F., Paus, T., Gowland, P., Heym, N., Lawrence, C., Newman, C., van Tol, Marie-Jose, Pausova, Z., Smolka, M., Huebner, T., Ripke, S., Mennigen, E., Muller, K., Ziesch, V., Büchel, C., Bromberg, U., Fadai, T., Wittfeld, Katharina, Lueken, L., Yacubian, J., Finsterbusch, J., Martinot, J. L., Artiges, E., Bordas, N., de Bournonville, S., Bricaud, Z., Gollier Briand, F., Lemaitre, H., Wolf, Christiane, Massicotte, J., Miranda, R., Paillère Martinot, M. L., Penttilä, J., Poline, J. B., Barbot, A., Schwartz, Y., Lalanne, C., Frouin, V., Thyreau, B., Woudstra, Saskia, Dalley, J., Mar, A., Robbins, T., Subramaniam, N., Theobald, D., Richmond, N., de Rover, M., Molander, A., Jordan, E., Robinson, E., Aleman, Andre, Hipolata, L., Moreno, M., Arroyo, M., Stephens, D., Ripley, T., Crombag, H., Pena, Y., Lathrop, M., Zelenika, D., Heath, S., Lanzerath, D., Heinrichs, B., Spranger, T., Fuchs, B., Speiser, C., Resch, F., Haffner, J., Parzer, P., Brunner, R., Klaassen, A., Toro, Roberto, Almasy, Laura, Klaassen, I., Constant, P., Mignon, X., Thomsen, T., Zysset, S., Vestboe, A., Ireland, J., Rogers, J., Binder, Elisabeth B, Chakravarty, Mallar, Smith, Albert Vernon, van der Lijn, Fedde, Crivello, Fabrice, Fornage, Myriam, Shulman, Joshua M, Brohawn, David G, Schmidt, Helena, Srikanth, Velandai, Schuur, Maaike, Yu, Lei, Choi, Seung-Hoan, Sigurdsson, Sigurdur, Verhaaren, Benjamin F J, DeStefano, Anita L, Lambert, Jean-Charles, Cantor, Rita M, Struchalin, Maksim, Stankovich, Jim, Ibrahim-Verbaas, Carla A, Fleischman, Debra, Zijdenbos, Alex, den Heijer, Tom, Mazoyer, Bernard, Coker, Laura H, Enzinger, Christian, Danoy, Patrick, Carless, Melanie A, Amin, Najaf, Arfanakis, Konstantinos, van Buchem, Mark A, de Bruijn, Renée F A G, Beiser, Alexa, Dufouil, Carole, Huang, Juebin, Cavalieri, Margherita, Thomson, Russell, Niessen, Wiro J, Corvin, Aiden, Chibnik, Lori B, Gislason, Gauti K, Hofman, Albert, Pikula, Aleksandra, Amouyel, Philippe, Freeman, Kevin B, Phan, Thanh G, Oostra, Ben A, Nalls, Michael A, Uitterlinden, Andre G, Czisch, Michael, Au, Rhoda, Elbaz, Alexis, Beare, Richard J, van Swieten, John C, Lopez, Oscar, Harris, Tamara B, Chouraki, Vincent, Breteler, Monique M B, De Jager, Philip L, Becker, James T, Curran, Joanne E, Knopman, David, Fazekas, Franz, Wolf, Philip A, van der Lugt, Aad, Longstreth, W. T., Brown, Mathew A, Bennett, David A, van Duijn, Cornelia M, Davies, Gail, Mosley, Thomas H, Schmidt, Reinhold, de Almeida, Marcio A A, Appel, Katja, Duggirala, Ravi, Dyer, Thomas D, Erk, Susanne, Fagerness, Jesen, Fox, Peter T, Freimer, Nelson B, Gill, Michael, Göring, Harald H H, Bartecek, Richard, Hagler, Donald J, Hoehn, David, Holsboer, Florian, Hoogman, Martine, Hosten, Norbert, Jahanshad, Neda, Johnson, Matthew P, Kent, Jack W, Kochunov, Peter, Bergmann, Ørjan, Lancaster, Jack L, Lawrie, Stephen M, Liewald, David C, Mandl, René, Mattheisen, Manuel, Meisenzahl, Eva, Melle, Ingrid, Moses, Eric K, Mühleisen, Thomas W, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, Queensland Institute of Medical Research, Radboud University Medical Center [Nijmegen], Yale University School of Medicine, Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Universität Greifswald - University of Greifswald, Universität Heidelberg [Heidelberg], University Medical Center [Utrecht], University of Oslo (UiO), University of Toronto, National University of Ireland [Galway] (NUI Galway), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], University of Bergen (UiB), Harvard University [Cambridge], VU University Amsterdam, University of Edinburgh, Structure et Réactivité des Systèmes Moléculaires Complexes (SRSMC), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], National Institutes of Health [Bethesda] (NIH), Department of Forensic and Neurodevelopmental Sciences, King‘s College London, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Georgia State University, University System of Georgia (USG), Department of Psychiatry and Human Behavior [Irvine], University of California [Irvine] (UCI), Leiden University Medical Center (LUMC), Dundee Technopole, CXR Biosciences Ltd, University of Groningen [Groningen], Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland (RCSI), Department of Genetics, Southwest Foundation for Biomedical Research, Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Neurology Division, Beaumont Hospital, Dublin 9, Ireland, Beaumont Hospital, The University of Texas Health Science Center at Houston (UTHealth), Center for Neurobehavioral Genetics, Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Department of Computer Science, Durham University, Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], University of California, Institute of Neurology [London], University College of London [London] (UCL), University of California [San Francisco] (UCSF), Department of Medicine, University of Washington [Seattle], Erasmus University Medical Center [Rotterdam] (Erasmus MC), Centre Émile Durkheim (CED), Sciences Po Bordeaux - Institut d'études politiques de Bordeaux (IEP Bordeaux)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Salermo, Università degli Studi di Salerno (UNISA), School of Psychology, University of Queensland, University of Queensland [Brisbane], Hartford Hospital, Lancaster University, Centre for Advanced Imaging, McConnell Brain Imaging Centre (MNI), McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Stanley Center for Psychiatric Research, Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Faculteit Medische Wetenschappen/UMCG, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), Biological Psychology, Neuroscience Campus Amsterdam - Brain Imaging, EMGO+ - Mental Health, EPIGEN Consortium, IMAGENConsortium, Saguenay Youth Study Group, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium, Psychiatry, NCA - Brain Imaging, EMGO - Mental health, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Virology, Epidemiology, Clinical Chemistry, Erasmus MC other, Radiology & Nuclear Medicine, University of California (UC)-University of California (UC), Yale School of Medicine [New Haven, Connecticut] (YSM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Universität Heidelberg [Heidelberg] = Heidelberg University, Harvard University, Vrije Universiteit Amsterdam [Amsterdam] (VU), University of California [Irvine] (UC Irvine), Universiteit Leiden, University of California (UC), University of California [San Francisco] (UC San Francisco), Università degli Studi di Salerno = University of Salerno (UNISA), University of Iceland [Reykjavik], McGill University, University of Bergen (UIB), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Bijvoet Center of Biomolecular Research, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, UMR5116, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and McGill University-McGill University

Subjects
Netherlands Twin Register (NTR), Pathology, 110 012 Social cognition of verbal communication, [SDV]Life Sciences [q-bio], Hippocampus, Genome-wide association study, DCN PAC - Perception action and control, Hippocampal formation, physiopathology [Brain], Bioinformatics, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, TEMPORAL-LOBE EPILEPSY, 110 014 Public activities, Renal disorder [IGMD 9], 0303 health sciences, medicine.diagnostic_test, Translational research Immune Regulation [ONCOL 3], Brain, Human brain, Genomic disorders and inherited multi-system disorders [DCN PAC - Perception action and control IGMD 3], ALZHEIMERS-DISEASE, medicine.anatomical_structure, Brain size, genetics [Chromosomes, Human, Pair 12], genetics [Polymorphism, Single Nucleotide], Biomarker (medicine), NA+/H+ EXCHANGER, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Genetic Markers, medicine.medical_specialty, 110 000 Neurocognition of Language, DCN MP - Plasticity and memory, A neurocomputational model for the Processing of Linguistic Utterances based on the Unification-Space architecture [110 007 PLUS], BRAIN VOLUME, UNIFIED APPROACH, 110 013 Binding and the MUC-model, Neuroimaging, Biology, GENOTYPE IMPUTATION, Polymorphism, Single Nucleotide, Article, Genomic disorders and inherited multi-system disorders DCN MP - Plasticity and memory [IGMD 3], 03 medical and health sciences, AUTOMATED SEGMENTATION, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, ddc:570, FUNCTIONAL IMPLICATIONS, Genetics, medicine, Humans, GENOME-WIDE ASSOCIATION, 030304 developmental biology, Chromosomes, Human, Pair 12, Magnetic resonance imaging, Genetic Loci, physiopathology [Hippocampus], 110 009 The human brain and Chinese prosody, Genetics and epigenetic pathways of disease Genomic disorders and inherited multi-system disorders [NCMLS 6], HUMAN HEIGHT, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 108202.pdf (Publisher’s version ) (Closed access) Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 x 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 x 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 x 10(-7)). 01 mei 2012

Published
2012

42. Multi-Site Meta-Analysis of Morphometry.

Author

Jahanshad, Neda, Faskowitz, Joshua, Roshchupkin, Gennady, Hibar, Derrek P., Gutman, Boris A., Tustison, Nicholas J., Adams, Hieab H. H., Niessen, Wiro J., Vernooij, Meike W., Ikram, M. Arfan, Zwiers, Marcel P., Vasquez, Alejandro Arias, Franke, Barbara, Kroll, Jennifer L., Mwangi, Benson, Soares, Jair C., Ing, Alex, Desrivieres, Sylvane, Schumann, Gunter, and Hansell, Narelle K.

Abstract

Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses (e.g., tensor-based morphometry; TBM) may help better localize statistical effects. This can lead to $10^{13}$1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

43. Altered regional brain volumes in elderly carriers of a risk variant for drug abuse in the dopamine D2 receptor gene (DRD2).

Author

Roussotte, Florence, Jahanshad, Neda, Hibar, Derrek, Thompson, Paul, Roussotte, Florence F, Hibar, Derrek P, Thompson, Paul M, and Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Subjects
ALZHEIMER'S disease, ANTHROPOMETRY, BRAIN, CELL receptors, COGNITION disorders, DATABASES, DISEASE susceptibility, GENETIC polymorphisms, GENETIC techniques, LONGITUDINAL method, MAGNETIC resonance imaging, RESEARCH funding, SUBSTANCE abuse, THREE-dimensional imaging, DISEASE progression, GENETIC carriers
Abstract

Dopamine D2 receptors mediate the rewarding effects of many drugs of abuse. In humans, several polymorphisms in DRD2, the gene encoding these receptors, increase our genetic risk for developing addictive disorders. Here, we examined one of the most frequently studied candidate variant for addiction in DRD2 for association with brain structure. We tested whether this variant showed associations with regional brain volumes across two independent elderly cohorts, totaling 1,032 subjects. We first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI1). We hypothesized that this addiction-related polymorphism would be associated with structural brain differences in regions previously implicated in familial vulnerability for drug dependence. Then, we assessed the generalizability of our findings by testing this polymorphism in a non-overlapping replication sample of 294 elderly subjects from a continuation of the first ADNI project (ADNI2) to minimize the risk of reporting false positive results. In both cohorts, the minor allele-previously linked with increased risk for addiction-was associated with larger volumes in various brain regions implicated in reward processing. These findings suggest that neuroanatomical phenotypes associated with familial vulnerability for drug dependence may be partially mediated by DRD2 genotype. [ABSTRACT FROM AUTHOR]

Published
2015
Full Text
View/download PDF

44. Brain structure in healthy adults is related to serum transferrin and the H63D polymorphism in the HFE gene.

Author

Jahanshad, Neda, Kohannim, Omid, Hibar, Derrek P., Stein, Jason L., McMahon, Katie L., de Zubicaray, Greig I., Medland, Sarah E., Montgomery, Grant W., Whitfield, John B., Martin, Nicholas G., Wright, Margaret J., Toga, Arthur W., and Thompson, Paul M.

Subjects
TRANSFERRIN, MAGNETIC resonance imaging, HEALTH of adults, BRAIN degeneration, IRON deficiency
Abstract

The article presents a study which investigates the association of brain structure in healthy adults with H63D polymorphism in the HFE gene and serum transferrin. It states that 615 young adult twins and their siblings were scanned using brain magnetic resonance imaging (MRI) to investigate the dependence of their brain structure on the level of transferrin. Results show the connections between the levels of transferrin, brain integrity, and genes related to iron.

Published
2012
Full Text
View/download PDF

45. Boosting power for clinical trials using classifiers based on multiple biomarkers

Author

Kohannim, Omid, Hua, Xue, Hibar, Derrek P., Lee, Suh, Chou, Yi-Yu, Toga, Arthur W., Jack, Clifford R., Weiner, Michael W., and Thompson, Paul M.

Subjects
*ALZHEIMER'S disease, *CLINICAL trials, *BIOMARKERS, *BRAIN imaging, *SUPPORT vector machines, *HIPPOCAMPUS (Brain), *CEREBROSPINAL fluid
Abstract

Abstract: Machine learning methods pool diverse information to perform computer-assisted diagnosis and predict future clinical decline. We introduce a machine learning method to boost power in clinical trials. We created a Support Vector Machine algorithm that combines brain imaging and other biomarkers to classify 737 Alzheimer''s disease Neuroimaging initiative (ADNI) subjects as having Alzheimer''s disease (AD), mild cognitive impairment (MCI), or normal controls. We trained our classifiers based on example data including: MRI measures of hippocampal, ventricular, and temporal lobe volumes, a PET-FDG numerical summary, CSF biomarkers (t-tau, p-tau, and Aβ42), ApoE genotype, age, sex, and body mass index. MRI measures contributed most to Alzheimer''s disease (AD) classification; PET-FDG and CSF biomarkers, particularly Aβ42, contributed more to MCI classification. Using all biomarkers jointly, we used our classifier to select the one-third of the subjects most likely to decline. In this subsample, fewer than 40 AD and MCI subjects would be needed to detect a 25% slowing in temporal lobe atrophy rates with 80% power—a substantial boosting of power relative to standard imaging measures. [Copyright &y& Elsevier]

Published
2010
Full Text
View/download PDF

46. Distinct Subcortical Volume Alterations in Pediatric and Adult OCD

Author

Federica Piras, Christine Lochner, Jan C. Beucke, José M. Menchón, Philip R. Szeszko, Hao Hu, Janardhanan C. Narayanaswamy, Damiaan Denys, Guido van Wingen, Yanni Liu, Luisa Lazaro, Jean Paul Fouche, Marcelo Queiroz Hoexter, Y. C.Janardhan Reddy, Silvia Brem, Paul D. Arnold, Sara Dallaspezia, Keisuke Ikari, Neda Jahanshad, Qing Zhao, Kang Ik Cho, Norbert Kathmann, Gianfranco Spalletta, Yuqi Cheng, Susanne Walitza, Derrek P. Hibar, Dan J. Stein, Christopher Pittenger, Odile A. van den Heuvel, Yoshinari Abe, Anushree Bose, David Mataix-Cols, Ganesan Venkatasubramanian, Je Yeon Yun, Ignacio Martínez-Zalacaín, Xiufeng Xu, João Ricardo Sato, Noam Soreni, Premika S.W. Boedhoe, Luciano Minuzzi, Carles Soriano-Mas, David F. Tolin, Kate D. Fitzgerald, Christian Kaufmann, Rachel Marsh, H. Blair Simpson, Fabrizio Piras, Zhen Wang, Michael C. Stevens, Lianne Schmaal, Marcelo C. Batistuzzo, Takashi Nakamae, Paul M. Thompson, Stephanie H. Ameis, Gregory L. Hanna, Irene Bollettini, Chaim Huyser, Kathrin Koch, Jun Soo Kwon, Mónica Giménez, Anna Calvo, Francesco Benedetti, Patricia Gruner, Jian Xu, Tomohiro Nakao, Universitat de Barcelona, Other departments, ANS - Amsterdam Neuroscience, Adult Psychiatry, Boedhoe, Premika S. W., Schmaal, Lianne, Abe, Yoshinari, Ameis, Stephanie H., Arnold, Paul D., Batistuzzo, Marcelo C., Benedetti, Francesco, Beucke, Jan C., Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Cheng, Yuqi, Cho, Kang Ik, Dallaspezia, Sara, Denys, Damiaan, Fitzgerald, Kate D., Fouche, Jean-Paul, Giménez, Mònica, Gruner, Patricia, Hanna, Gregory L., Hibar, Derrek P., Hoexter, Marcelo Q., Hu, Hao, Huyser, Chaim, Ikari, Keisuke, Jahanshad, Neda, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Liu, Yanni, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M., Minuzzi, Luciano, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C., Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Y. C. Janardhan, Sato, Joao R., Simpson, H. Blair, Soreni, Noam, Soriano-Mas, Carle, Spalletta, Gianfranco, Stevens, Michael C., Szeszko, Philip R., Tolin, David F., Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Van Wingen, Guido A., Xu, Jian, Xu, Xiufeng, Yun, Je-Yeon, Zhao, Qing, Thompson, Paul M., Stein, Dan J., Van Den Heuvel, Odile A., Psychiatry, Anatomy and neurosciences, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, and Netherlands Institute for Neuroscience (NIN)

Subjects
Obsessive-Compulsive Disorder, FreeSurfer, Audiology, Pediatrics, Hippocampus, 0302 clinical medicine, Neurodevelopmental disorder, Thalamus, Obsessive-compulsive disorder, Young adult, Child, Psychiatry, Pediatria, medicine.diagnostic_test, Healthy subjects, Organ Size, Middle Aged, Control subjects, Magnetic Resonance Imaging, Psychiatry and Mental health, Psychiatry and Mental Health, Mega analysis, Psychology, Human, Adult, medicine.medical_specialty, Adolescent, Neuroimaging, Globus Pallidus, behavioral disciplines and activities, Article, Malalts, 03 medical and health sciences, Young Adult, Hippocampu, mental disorders, medicine, Humans, Thalamu, Sick, Neurosi obsessiva, Globus Pallidu, Magnetic resonance imaging, Voxel-based morphometry, medicine.disease, 030227 psychiatry, Structural MRI, 030217 neurology & neurosurgery
Abstract

Objective: structural brain imaging studies in obsessive compulsive disorder (OCD) have produced inconsistent findings. This may be partially due to limited statistical power from relatively small samples and clinical heterogeneity related to variation in illness profile and developmental stage. To address these limitations, the authors conducted meta and mega-analyses of data from OCD sites worldwide. Method: T-1 images from 1,830 OCD patients and 1,759 control subjects were analyzed, using coordinated and standardized processing, to identify subcortical brain volumes that differ between OCD patients and healthy subjects. The authors performed a meta analysis on the mean of the left and right hemisphere measures of each subcortical structure, and they performed a mega-analysis by pooling these volumetric measurements from each site. The authors additionally examined potential modulating effects of clinical characteristics on morphological differences in OCD patients. Results: the meta-analysis indicated that adult patients had significantly smaller hippocampal volumes (Cohen's d=-0.13; % difference=-2.80) and larger pallidum volumes (d=0.16; % difference=3.16) compared with adult controls. Both effects were stronger in medicated patients compared with controls (d=-0.29, % difference=-4.18, and d=0.29, % difference=4.38, respectively). Unmedicated pediatric patients had significantly larger thalamic volumes (d=0.38, % difference=3.08) compared with pediatric controls. None of these findings were mediated by sample characteristics, such as mean age or scanning field strength. The mega-analysis yielded similar results. Conclusions: the results indicate different patterns of sub cortical abnormalities in pediatric and adult OCD patients. The patlidum and hippocampus seem to be of importance in adult OCD, whereas the thalamus seems to be key in pediatric OCD. These findings highlight the potential importance of neurodevelopmental alterations in OCD and suggest that further research on neuroplasticity in OCD may be useful.

Published
2017

47. Cortical Abnormalities Associated With Pediatric and Adult Obsessive-Compulsive Disorder: Findings From the ENIGMA Obsessive-Compulsive Disorder Working Group

Author

Alan Anticevic, Valentina Ciullo, Janardhanan C. Narayanaswamy, Paul D. Arnold, Pino Alonso, Seiji Nishida, Luisa Lázaro, Christine Lochner, Zhen Wang, Joseph O'Neill, Silvia Brem, Guido A. Van Wingen, Jean Paul Fouche, Marcelo Queiroz Hoexter, Y. C.Janardhan Reddy, Michael C. Stevens, Stephanie H. Ameis, Fabrizio Piras, Jun Soo Kwon, Rosa Calvo, Marcelo C. Batistuzzo, Gregory L. Hanna, Yoshinari Abe, Yuki Sakai, David F. Tolin, Irene Bollettini, Kathrin Koch, H. Blair Simpson, Noam Soreni, Erika L. Nurmi, Kang Ik Kevin Cho, Luciano Minuzzi, Jan C. Beucke, Susanne Walitza, Jamie D. Feusner, Derrek P. Hibar, Chaim Huyser, Anna Calvo, Tomohiro Nakao, Ignacio Martínez-Zalacaín, Patricia Gruner, Francesco Benedetti, Je Yeon Yun, David Mataix-Cols, Paul M. Thompson, Odile A. van den Heuvel, Anthony A. James, Premika S.W. Boedhoe, Yuqi Cheng, Hao Hu, Tim Jonas Reess, John Piacentini, Carles Soriano-Mas, Neda Jahanshad, Kate D. Fitzgerald, Astrid Morer, Sara Dallaspezia, Gianfranco Spalletta, Dan J. Stein, Takashi Nakamae, João Ricardo Sato, Egill A. Fridgeirsson, Christian Kaufmann, Ganesan Venkatasubramanian, Philip R. Szeszko, Lianne Schmaal, Rachel Marsh, Norbert Kathmann, Anushree Bose, Federica Piras, José M. Menchón, D. Denys, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Boedhoe, Premika S W, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Hanna, Gregory L, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nishida, Seiji, Nurmi, Erika, O'Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, Y C Janardhan, Reess, Tim J, Sakai, Yuki, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carle, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, van Wingen, Guido A, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, ANS - Compulsivity, Impulsivity & Attention, Adult Psychiatry, Graduate School, Child Psychiatry, and Netherlands Institute for Neuroscience (NIN)

Subjects
Adult, Obsessive-Compulsive Disorder, medicine.medical_specialty, Adolescent, FreeSurfer, behavioral disciplines and activities, Article, Temporal lobe, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Reference Values, Cortical abnormalities, Parietal Lobe, mental disorders, Journal Article, medicine, Obsessive-compulsive disorder, Humans, Cortical Thickne, Age of Onset, Young adult, Child, Psychiatry, Cerebral Cortex, Neurosi obsessiva, Parietal lobe, Surface Area, Voxel-based morphometry, Magnetic Resonance Imaging, Temporal Lobe, humanities, Frontal Lobe, 030227 psychiatry, Psychiatry and Mental health, Diagnòstic per la imatge, Frontal lobe, Diagnostic imaging, Age of onset, Psychology, 030217 neurology & neurosurgery, MRI
Abstract

Objective: Brain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken. Method: T1-weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using FreeSurfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume. Results: In adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortexand a thinner inferiorparietalcortex.Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showedsignificant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from 20.10 to 20.33. Conclusions: The parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were found in medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication.

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results