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van Drunen L, Dobbelaar S, Crone EA, Wierenga LM. Genetic and environmental influences on structural brain development from childhood to adolescence: A longitudinal twin study on cortical thickness, surface area, and subcortical volume. Dev Cogn Neurosci 2024; 68:101407. [PMID: 38870602 PMCID: PMC11225697 DOI: 10.1016/j.dcn.2024.101407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 06/10/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
The human brain undergoes structural development from childhood to adolescence, with specific regions in the sensorimotor, social, and affective networks continuing to grow into adulthood. While genetic and environmental factors contribute to individual differences in these brain trajectories, the extent remains understudied. Our longitudinal study, utilizing up to three biennial MRI scans (n=485), aimed to assess the genetic and environmental effects on brain structure (age 7) and development (ages 7-14) in these regions. Heritability estimates varied across brain regions, with all regions showing genetic influence (ranging from 18 % to 59 %) with additional shared environmental factors affecting the primary motor cortex (30 %), somatosensory cortex (35 %), DLPFC (5 %), TPJ (17 %), STS (17 %), precuneus (10 %), hippocampus (22 %), amygdala (5 %), and nucleus accumbens (10 %). Surface area was more genetically driven (38 %) than cortical thickness (14 %). Longitudinal brain changes were primarily driven by genetics (ranging from 1 % to 29 %), though shared environment factors (additionally) influenced the somatosensory cortex (11 %), DLPFC (7 %), cerebellum (28 %), TPJ (16 %), STS (20 %), and hippocampus (17 %). These findings highlight the importance of further investigating brain-behavior associations and the influence of enriched and deprived environments from childhood to adolescence. Ultimately, our study can provide insights for interventions aimed at supporting children's development.
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Affiliation(s)
- L van Drunen
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands.
| | - S Dobbelaar
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands
| | - E A Crone
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands
| | - L M Wierenga
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands
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2
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Fjell AM. Aging Brain from a Lifespan Perspective. Curr Top Behav Neurosci 2024. [PMID: 38797799 DOI: 10.1007/7854_2024_476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.
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Affiliation(s)
- Anders Martin Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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3
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Rolan EP, Mikhail ME, Culbert KM, Burt SA, Klump KL. Estrogen moderation of genetic influences on eating disorder symptoms during gonadarche in girls: Specific effects on binge eating. Psychoneuroendocrinology 2023; 158:106384. [PMID: 37708824 PMCID: PMC10880121 DOI: 10.1016/j.psyneuen.2023.106384] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 07/13/2023] [Accepted: 09/05/2023] [Indexed: 09/16/2023]
Abstract
The heritability of eating disorder (ED) symptoms increases dramatically across gonadarche in girls. Past studies suggest these developmental differences could be due to pubertal activation of estrogen, but findings have been limited to only one ED symptom (i.e., binge eating). The current study examined whether estrogen contributes to gonadarcheal differences in genetic influences on overall levels of ED symptoms as well as key cognitive symptoms (i.e., weight/shape concerns) that are present across all EDs and are early risk factors for eating pathology. Given that binge eating frequently co-occurs with all of these symptoms, analyses also examined whether estrogen effects exist for overall levels of ED symptoms and body weight/shape concerns after accounting for the known effects of estrogen on genetic risk for binge eating. Participants included 964 female twins (ages 8-16) from the Michigan State University Twin Registry. Overall levels of ED symptoms were assessed with the Minnesota Eating Behavior Survey (MEBS) total score. Weight/shape concerns were assessed with a latent factor modeled using subscales from the MEBS and the Eating Disorder Examination Questionnaire. Estradiol levels were assessed with saliva samples. Twin moderation models were used to examine whether genetic influences on overall levels of ED symptoms and weight/shape concerns differed significantly across estradiol levels. Although initial models suggested modest differences in genetic influences on overall levels of ED symptoms across estradiol levels, these effects were eliminated when binge eating was accounted for in the models. In addition, weight/shape concerns did not show significant moderation of genetic influences by estradiol in models with or without binge eating. Taken together, results are significant in suggesting that individual differences in estradiol levels during gonadarche have a unique and specific impact on genetic risk for binge eating, while other etiologic factors must contribute to increased heritability of cognitive ED symptoms during this key developmental period in girls.
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Affiliation(s)
- Emily P Rolan
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Megan E Mikhail
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Kristen M Culbert
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - S Alexandra Burt
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Kelly L Klump
- Department of Psychology, Michigan State University, East Lansing, MI, USA.
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4
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Teeuw J, Klein M, Mota NR, Brouwer RM, van ‘t Ent D, Al-Hassaan Z, Franke B, Boomsma DI, Hulshoff Pol HE. Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample. Int J Mol Sci 2022; 23:ijms23063176. [PMID: 35328598 PMCID: PMC8949114 DOI: 10.3390/ijms23063176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/10/2022] [Accepted: 03/10/2022] [Indexed: 12/10/2022] Open
Abstract
Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to −0.20), with sizeable genetic correlations (FA ra up to +0.42; MD ra up to −0.33). The cortical gray matter (CGM; rph up to −0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.
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Affiliation(s)
- Jalmar Teeuw
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Correspondence: ; Tel.: +31-(088)-75-53-387
| | - Marieke Klein
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Nina Roth Mota
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Rachel M. Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Dennis van ‘t Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
| | - Zyneb Al-Hassaan
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Psychology, Utrecht University, 3584 CS Utrecht, The Netherlands
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5
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El Marroun H, Klapwijk ET, Koevoets M, Brouwer RM, Peters S, Van't Ent D, Boomsma DI, Muetzel RL, Crone EA, Hulshoff Pol HE, Franken IHA. Alcohol use and brain morphology in adolescence: A longitudinal study in three different cohorts. Eur J Neurosci 2021; 54:6012-6026. [PMID: 34390509 PMCID: PMC9291789 DOI: 10.1111/ejn.15411] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 07/28/2021] [Accepted: 07/28/2021] [Indexed: 11/30/2022]
Abstract
Alcohol consumption is commonly initiated during adolescence, but the effects on human brain development remain unknown. In this multisite study, we investigated the longitudinal associations of adolescent alcohol use and brain morphology. Three longitudinal cohorts in the Netherlands (BrainScale n = 200, BrainTime n = 239 and a subsample of the Generation R study n = 318) of typically developing participants aged between 8 and 29 years were included. Adolescent alcohol use was self‐reported. Longitudinal neuroimaging data were collected for at least two time points. Processing pipelines and statistical analyses were harmonized across cohorts. Main outcomes were global and regional brain volumes, which were a priori selected. Linear mixed effect models were used to test main effects of alcohol use and interaction effects of alcohol use with age in each cohort separately. Alcohol use was associated with adolescent's brain morphology showing accelerated decrease in grey matter volumes, in particular in the frontal and cingulate cortex volumes, and decelerated increase in white matter volumes. No dose–response association was observed. The findings were most prominent and consistent in the older cohorts (BrainScale and BrainTime). In summary, this longitudinal study demonstrated differences in neurodevelopmental trajectories of grey and white matter volume in adolescents who consume alcohol compared with non‐users. These findings highlight the importance to further understand underlying neurobiological mechanisms when adolescents initiate alcohol consumption. Therefore, further studies need to determine to what extent this reflects the causal nature of this association, as this longitudinal observational study does not allow for causal inference.
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Affiliation(s)
- Hanan El Marroun
- Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam, Erasmus MC, Rotterdam, The Netherlands.,Department of Pediatrics, University Medical Center Rotterdam, Erasmus MC, Rotterdam, The Netherlands.,Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Eduard T Klapwijk
- Department of Developmental and Educational Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Martijn Koevoets
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Sabine Peters
- Department of Developmental and Educational Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Dennis Van't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam, Erasmus MC, Rotterdam, The Netherlands
| | - Eveline A Crone
- Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ingmar H A Franken
- Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam, Erasmus MC, Rotterdam, The Netherlands.,Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
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6
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Brouwer RM, Schutte J, Janssen R, Boomsma DI, Hulshoff Pol HE, Schnack HG. The Speed of Development of Adolescent Brain Age Depends on Sex and Is Genetically Determined. Cereb Cortex 2021; 31:1296-1306. [PMID: 33073292 PMCID: PMC8204942 DOI: 10.1093/cercor/bhaa296] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/18/2020] [Accepted: 09/10/2020] [Indexed: 11/20/2022] Open
Abstract
Children and adolescents show high variability in brain development. Brain age-the estimated biological age of an individual brain-can be used to index developmental stage. In a longitudinal sample of adolescents (age 9-23 years), including monozygotic and dizygotic twins and their siblings, structural magnetic resonance imaging scans (N = 673) at 3 time points were acquired. Using brain morphology data of different types and at different spatial scales, brain age predictors were trained and validated. Differences in brain age between males and females were assessed and the heritability of individual variation in brain age gaps was calculated. On average, females were ahead of males by at most 1 year, but similar aging patterns were found for both sexes. The difference between brain age and chronological age was heritable, as was the change in brain age gap over time. In conclusion, females and males show similar developmental ("aging") patterns but, on average, females pass through this development earlier. Reliable brain age predictors may be used to detect (extreme) deviations in developmental state of the brain early, possibly indicating aberrant development as a sign of risk of neurodevelopmental disorders.
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Affiliation(s)
- Rachel M Brouwer
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Jelle Schutte
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Ronald Janssen
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology and Netherlands Twin
Register, VU University Amsterdam, 1081 HV
Amsterdam, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
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7
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Buimer EEL, Pas P, Brouwer RM, Froeling M, Hoogduin H, Leemans A, Luijten P, van Nierop BJ, Raemaekers M, Schnack HG, Teeuw J, Vink M, Visser F, Hulshoff Pol HE, Mandl RCW. The YOUth cohort study: MRI protocol and test-retest reliability in adults. Dev Cogn Neurosci 2020; 45:100816. [PMID: 33040972 PMCID: PMC7365929 DOI: 10.1016/j.dcn.2020.100816] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 06/09/2020] [Accepted: 07/02/2020] [Indexed: 11/30/2022] Open
Abstract
The YOUth cohort study is a unique longitudinal study on brain development in the general population. As part of the YOUth study, 2000 children will be included at 8, 9 or 10 years of age and planned to return every three years during adolescence. Magnetic resonance imaging (MRI) brain scans are collected, including structural T1-weighted imaging, diffusion-weighted imaging (DWI), resting-state functional MRI and task-based functional MRI. Here, we provide a comprehensive report of the MR acquisition in YOUth Child & Adolescent including the test-retest reliability of brain measures derived from each type of scan. To measure test-retest reliability, 17 adults were scanned twice with a week between sessions using the full YOUth MRI protocol. Intraclass correlation coefficients were calculated to quantify reliability. Global brain measures derived from structural T1-weighted and DWI scans were reliable. Resting-state functional connectivity was moderately reliable, as well as functional brain measures for both the inhibition task (stop versus go) and the emotion task (face versus house). Our results complement previous studies by presenting reliability results of regional brain measures collected with different MRI modalities. YOUth facilitates data sharing and aims for reliable and high-quality data. Here we show that using the state-of-the art YOUth MRI protocol brain measures can be estimated reliably.
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Affiliation(s)
- Elizabeth E L Buimer
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Pascal Pas
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Rachel M Brouwer
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Martijn Froeling
- Image Sciences Institute, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Hans Hoogduin
- Image Sciences Institute, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Peter Luijten
- Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Bastiaan J van Nierop
- Image Sciences Institute, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Mathijs Raemaekers
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Hugo G Schnack
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Jalmar Teeuw
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - Matthijs Vink
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands; Department of Psychology, Utrecht University, Utrecht, the Netherlands
| | | | - Hilleke E Hulshoff Pol
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - René C W Mandl
- UMCU Brain Center, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands.
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8
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van Keulen BJ, Dolan CV, van der Voorn B, Andrew R, Walker BR, Hulshoff Pol H, Boomsma DI, Rotteveel J, Finken MJJ. Sexual dimorphism in cortisol metabolism throughout pubertal development: a longitudinal study. Endocr Connect 2020; 9:542-551. [PMID: 32413849 PMCID: PMC7354723 DOI: 10.1530/ec-20-0123] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 05/15/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Sex differences in disease susceptibility might be explained by sexual dimorphism in hypothalamic-pituitary-adrenal axis activity, which has been postulated to emerge during puberty. However, studies conducted thus far lacked an assessment of Tanner pubertal stage. This study aimed to assess the contribution of pubertal development to sexual dimorphism in cortisol production and metabolism. METHODS Participants (n = 218) were enrolled from a population-based Netherlands Twin Register. At the ages of 9, 12 and 17 years, Tanner pubertal stage was assessed and early morning urine samples were collected. Cortisol metabolites were measured with GC-MS/MS and ratios were calculated, representing cortisol metabolism enzyme activities, such as A-ring reductases, 11β-HSDs and CYP3A4. Cortisol production and metabolism parameters were compared between sexes for pre-pubertal (Tanner stage 1), early pubertal (Tanner stage 2-3) and late-pubertal (Tanner stage 4-5) stages. RESULTS Cortisol metabolite excretion rate decreased with pubertal maturation in both sexes, but did not significantly differ between sexes at any pubertal stage, although in girls a considerable decrease was observed between early and late-pubertal stage (P < 0.001). A-ring reductase activity was similar between sexes at pre- and early pubertal stages and was lower in girls than in boys at late-pubertal stage. Activities of 11β-HSDs were similar between sexes at pre-pubertal stage and favored cortisone in girls at early and late-pubertal stages. Cytochrome P450 3A4 activity did not differ between sexes. CONCLUSIONS Prepubertally, sexes were similar in cortisol parameters. During puberty, as compared to boys, in girls the activities of A-ring reductases declined and the balance between 11β-HSDs progressively favored cortisone. In addition, girls showed a considerable decrease in cortisol metabolite excretion rate between early and late-pubertal stages. Our findings suggest that the sexual dimorphism in cortisol may either be explained by rising concentrations of sex steroids or by puberty-induced changes in body composition.
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Affiliation(s)
- Britt J van Keulen
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
- Correspondence should be addressed to B J van Keulen:
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bibian van der Voorn
- Department of Pediatric Endocrinology, Sophia Kinderziekenhuis, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ruth Andrew
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
| | - Brian R Walker
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Hilleke Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joost Rotteveel
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
| | - Martijn J J Finken
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
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9
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Van Keulen BJ, Dolan CV, Andrew R, Walker BR, Hulshoff Pol HE, Boomsma DI, Rotteveel J, Finken MJ. Exploring the Temporal Relation between Body Mass Index and Corticosteroid Metabolite Excretion in Childhood. Nutrients 2020; 12:nu12051525. [PMID: 32456232 PMCID: PMC7284460 DOI: 10.3390/nu12051525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/10/2020] [Accepted: 05/20/2020] [Indexed: 11/22/2022] Open
Abstract
Childhood obesity is associated with alterations in hypothalamus–pituitary–adrenal (HPA) axis activity. However, it is unknown whether these alterations are a cause or a consequence of obesity. This study aimed to explore the temporal relationship between cortisol production and metabolism, and body mass index (BMI). This prospective follow-up study included 218 children (of whom 50% were male), born between 1995 and 1996, who were assessed at the ages of 9, 12 and 17 years. Morning urine samples were collected for assessment of cortisol metabolites by gas chromatography-tandem mass spectrometry, enabling the calculation of cortisol metabolite excretion rate and cortisol metabolic pathways. A cross-lagged regression model was used to determine whether BMI at various ages during childhood predicted later cortisol production and metabolism parameters, or vice versa. The cross-lagged regression coefficients showed that BMI positively predicted cortisol metabolite excretion (p = 0.03), and not vice versa (p = 0.33). In addition, BMI predicted the later balance of 11β-hydroxysteroid dehydrogenase (HSD) activities (p = 0.07), and not vice versa (p = 0.55). Finally, cytochrome P450 3A4 activity positively predicted later BMI (p = 0.01). Our study suggests that changes in BMI across the normal range predict alterations in HPA axis activity. Therefore, the alterations in HPA axis activity as observed in earlier studies among children with obesity may be a consequence rather than a cause of increased BMI.
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Affiliation(s)
- Britt J. Van Keulen
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands; (J.R.); (M.J.J.F.)
- Correspondence: ; Tel.: +31-20-4444-444
| | - Conor V. Dolan
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands; (C.V.D.); (D.I.B.)
| | - Ruth Andrew
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, 47, Little France Crescent, Edinburgh EH16 4TJ, UK; (R.A.); (B.R.W.)
| | - Brian R. Walker
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, 47, Little France Crescent, Edinburgh EH16 4TJ, UK; (R.A.); (B.R.W.)
- Institute of Genetic Medicine, Newcastle University, Central Pkwy, Newcastle upon Tyne NE1 3BZ, UK
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht, Brain Center, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands;
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands; (C.V.D.); (D.I.B.)
| | - Joost Rotteveel
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands; (J.R.); (M.J.J.F.)
| | - Martijn J.J. Finken
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands; (J.R.); (M.J.J.F.)
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10
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Long-Term Stability of Cortisol Production and Metabolism Throughout Adolescence: Longitudinal Twin Study. Twin Res Hum Genet 2020; 23:33-38. [PMID: 32209144 DOI: 10.1017/thg.2020.6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Life-course experiences have been postulated to program hypothalamus-pituitary-adrenal (HPA) axis activity, suggesting that HPA axis activity is, at least partially, stable over time. Yet, there is paucity of data on the long-term stability of cortisol production and metabolism. We performed a prospective follow-up study in twins recruited from a nationwide register to estimate the stability of cortisol production and metabolism over time, and the contribution of genetic and environmental factors to this stability. In total, 218 healthy mono- and dizygotic twins were included. At the ages of 9, 12 and 17 years, morning urine samples were collected for assessment (by gas chromatography-tandem mass spectrometry) of cortisol metabolites, enabling the calculation of cortisol metabolite excretion rate and cortisol metabolism activity. Our results showed a low stability for both cortisol metabolite excretion rate (with correlations <.20) and cortisol metabolism activity indices (with correlations of .25 to .46 between 9 and 12 years, -.02 to .15 between 12 and 17 years and .09 to .28 between 9 and 17 years). Because of the low stability over time, genetic and environmental contributions to this stability were difficult to assess, although it seemed to be mostly determined by genetic factors. The low stability in both cortisol production and metabolism between ages 9 and 17 years reflects the dynamic nature of the HPA axis.
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11
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van Keulen BJ, Dolan CV, Andrew R, Walker BR, Hulshoff Pol HE, Boomsma DI, Rotteveel J, Finken MJJ. Heritability of Cortisol Production and Metabolism Throughout Adolescence. J Clin Endocrinol Metab 2020; 105:5586817. [PMID: 31608377 PMCID: PMC7046020 DOI: 10.1210/clinem/dgz016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 09/25/2019] [Indexed: 12/12/2022]
Abstract
CONTEXT Inter-individual differences in cortisol production and metabolism emerge with age and may be explained by genetic factors. OBJECTIVE To estimate the relative contributions of genetic and environmental factors to inter-individual differences in cortisol production and metabolism throughout adolescence. DESIGN Prospective follow-up study of twins. SETTING Nationwide register. PARTICIPANTS 218 mono- and dizygotic twins (N = 109 pairs) born between 1995 amd 1996, recruited from the Netherlands Twin Register. Cortisol metabolites were determined in 213, 169, and 160 urine samples at the ages of 9, 12, and 17, respectively. MAIN OUTCOME MEASURES The total contribution of genetic factors (broad-sense heritability) and shared and unshared environmental influences to inter-individual differences in cortisol production and activities of 5α-reductase, 5β-reductase, and 11β-hydroxysteroid dehydrogenases and cytochrome P450 3A4. RESULTS For cortisol production rate at the ages of 9, 12, and 17, broad-sense heritability was estimated as 42%, 30%, and 0%, respectively, and the remainder of the variance was explained by unshared environmental factors. For cortisol metabolism indices, the following heritability was observed: for the A-ring reductases (5α-and 5β-reductases), broad-sense heritability increased with age (to >50%), while for the other indices (renal 11β-HSD2, global 11β-HSD, and CYP3A4), the contribution of genetic factors was highest (68%, 18%, and 67%, respectively) at age 12. CONCLUSIONS The contribution of genetic factors to inter-individual differences in cortisol production decreased between 12 and 17y, indicative of a predominant role of individual circumstances. For cortisol metabolism, distinct patterns of genetic and environmental influences were observed, with heritability that either increased with age or peaked at age 12y.
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Affiliation(s)
- Britt J van Keulen
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
- Correspondence and Requests: Britt J van Keulen, MD, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric endocrinology, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. E-mail:
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, The Netherlands
| | - Ruth Andrew
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
| | - Brian R Walker
- Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brian Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, The Netherlands
| | - Joost Rotteveel
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
| | - Martijn J J Finken
- Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Endocrinology, Amsterdam, The Netherlands
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12
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Maggioni E, Squarcina L, Dusi N, Diwadkar VA, Brambilla P. Twin MRI studies on genetic and environmental determinants of brain morphology and function in the early lifespan. Neurosci Biobehav Rev 2020; 109:139-149. [PMID: 31911159 DOI: 10.1016/j.neubiorev.2020.01.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 12/19/2019] [Accepted: 01/02/2020] [Indexed: 02/04/2023]
Abstract
Neurodevelopment represents a period of increased opportunity and vulnerability, during which a complex confluence of genetic and environmental factors influences brain growth trajectories, cognitive and mental health outcomes. Recently, magnetic resonance imaging (MRI) studies on twins have increased our knowledge of the extent to which genes, the environment and their interactions shape inter-individual brain variability. The present review draws from highly salient MRI studies in young twin samples to provide a robust assessment of the heritability of structural and functional brain changes during development. The available studies suggest that (as with many other traits), global brain morphology and network organization are highly heritable from early childhood to young adulthood. Conversely, genetic correlations among brain regions exhibit heterogeneous trajectories, and this heterogeneity reflects the progressive, experience-related increase in brain network complexity. Studies also support the key role of environment in mediating brain network differentiation via changes of genetic expression and hormonal levels. Thus, rest- and task-related functional brain circuits seem to result from a contextual and dynamic expression of heritability.
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Affiliation(s)
- Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via F. Sforza 28, Milano, Italy
| | - Letizia Squarcina
- Child Psychopathology Unit, Scientific Institute, IRCCS Eugenio Medea, via Don Luigi Monza 20, Bosisio Parini, LC, Italy
| | - Nicola Dusi
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via F. Sforza 28, Milano, Italy
| | - Vaibhav A Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University, 42 W Warren Ave, Detroit, MI, United States
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via F. Sforza 28, Milano, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
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13
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The Netherlands Twin Register: Longitudinal Research Based on Twin and Twin-Family Designs. Twin Res Hum Genet 2019; 22:623-636. [PMID: 31666148 DOI: 10.1017/thg.2019.93] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The Netherlands Twin Register (NTR) is a national register in which twins, multiples and their parents, siblings, spouses and other family members participate. Here we describe the NTR resources that were created from more than 30 years of data collections; the development and maintenance of the newly developed database systems, and the possibilities these resources create for future research. Since the early 1980s, the NTR has enrolled around 120,000 twins and a roughly equal number of their relatives. The majority of twin families have participated in survey studies, and subsamples took part in biomaterial collection (e.g., DNA) and dedicated projects, for example, for neuropsychological, biomarker and behavioral traits. The recruitment into the NTR is all inclusive without any restrictions on enrollment. These resources - the longitudinal phenotyping, the extended pedigree structures and the multigeneration genotyping - allow for future twin-family research that will contribute to gene discovery, causality modeling, and studies of genetic and cultural inheritance.
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14
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Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. Neuroimage 2019; 202:116073. [PMID: 31386921 DOI: 10.1016/j.neuroimage.2019.116073] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 06/27/2019] [Accepted: 08/02/2019] [Indexed: 12/11/2022] Open
Abstract
The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.
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15
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Kochunov P, Patel B, Ganjgahi H, Donohue B, Ryan M, Hong EL, Chen X, Adhikari B, Jahanshad N, Thompson PM, Van't Ent D, den Braber A, de Geus EJC, Brouwer RM, Boomsma DI, Hulshoff Pol HE, de Zubicaray GI, McMahon KL, Martin NG, Wright MJ, Nichols TE. Homogenizing Estimates of Heritability Among SOLAR-Eclipse, OpenMx, APACE, and FPHI Software Packages in Neuroimaging Data. Front Neuroinform 2019; 13:16. [PMID: 30914942 PMCID: PMC6422938 DOI: 10.3389/fninf.2019.00016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 02/25/2019] [Indexed: 11/30/2022] Open
Abstract
Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Binish Patel
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Habib Ganjgahi
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Brian Donohue
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Meghann Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Elliot L Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Xu Chen
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Paul M Thompson
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Dennis Van't Ent
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Rachel M Brouwer
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Greig I de Zubicaray
- Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | | | - Margaret J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Thomas E Nichols
- Big Data Institute, University of Oxford, Oxford, United Kingdom
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16
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Koenis MM, Brouwer RM, Swagerman SC, van Soelen IL, Boomsma DI, Hulshoff Pol HE. Association between structural brain network efficiency and intelligence increases during adolescence. Hum Brain Mapp 2018; 39:822-836. [PMID: 29139172 PMCID: PMC6866576 DOI: 10.1002/hbm.23885] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 11/01/2017] [Accepted: 11/07/2017] [Indexed: 12/15/2022] Open
Abstract
Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the structural brain network. A more efficient structural brain network has been associated with higher intelligence. Whether development of structural network efficiency is related to intelligence, and if so to which extent genetic and environmental influences are implicated in their association, is not known. In a longitudinal study, we mapped FA-weighted efficiency of the structural brain network in 310 twins and their older siblings at an average age of 10, 13, and 18 years. Age-trajectories of global and local FA-weighted efficiency were related to intelligence. Contributions of genes and environment were estimated using structural equation modeling. Efficiency of brain networks changed in a non-linear fashion from childhood to early adulthood, increasing between 10 and 13 years, and leveling off between 13 and 18 years. Adolescents with higher intelligence had higher global and local network efficiency. The dependency of FA-weighted global efficiency on IQ increased during adolescence (rph =0.007 at age 10; 0.23 at age 18). Global efficiency was significantly heritable during adolescence (47% at age 18). The genetic correlation between intelligence and global and local efficiency increased with age; genes explained up to 87% of the observed correlation at age 18. In conclusion, the brain's structural network differentiates depending on IQ during adolescence, and is under increasing influence of genes that are also associated with intelligence as it develops from late childhood to adulthood.
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Affiliation(s)
- Marinka M.G. Koenis
- Brain Center Rudolf Magnus, Department of PsychiatryUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Rachel M. Brouwer
- Brain Center Rudolf Magnus, Department of PsychiatryUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Suzanne C. Swagerman
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Inge L.C. van Soelen
- Brain Center Rudolf Magnus, Department of PsychiatryUniversity Medical Center UtrechtUtrechtThe Netherlands
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Hilleke E. Hulshoff Pol
- Brain Center Rudolf Magnus, Department of PsychiatryUniversity Medical Center UtrechtUtrechtThe Netherlands
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17
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Teeuw J, Brouwer RM, Koenis MMG, Swagerman SC, Boomsma DI, Hulshoff Pol HE. Genetic Influences on the Development of Cerebral Cortical Thickness During Childhood and Adolescence in a Dutch Longitudinal Twin Sample: The Brainscale Study. Cereb Cortex 2018; 29:978-993. [DOI: 10.1093/cercor/bhy005] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Indexed: 01/05/2023] Open
Affiliation(s)
- Jalmar Teeuw
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100, 5384 CX Utrecht, the Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100, 5384 CX Utrecht, the Netherlands
| | - Marinka M G Koenis
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100, 5384 CX Utrecht, the Netherlands
| | - Suzanne C Swagerman
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100, 5384 CX Utrecht, the Netherlands
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18
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White T, Muetzel RL, El Marroun H, Blanken LME, Jansen P, Bolhuis K, Kocevska D, Mous SE, Mulder R, Jaddoe VWV, van der Lugt A, Verhulst FC, Tiemeier H. Paediatric population neuroimaging and the Generation R Study: the second wave. Eur J Epidemiol 2018; 33:99-125. [PMID: 29064008 PMCID: PMC5803295 DOI: 10.1007/s10654-017-0319-y] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 10/06/2017] [Indexed: 10/25/2022]
Abstract
Paediatric population neuroimaging is an emerging field that falls at the intersection between developmental neuroscience and epidemiology. A key feature of population neuroimaging studies involves large-scale recruitment that is representative of the general population. One successful approach for population neuroimaging is to embed neuroimaging studies within large epidemiological cohorts. The Generation R Study is a large, prospective population-based birth-cohort in which nearly 10,000 pregnant mothers were recruited between 2002 and 2006 with repeated measurements in the children and their parents over time. Magnetic resonance imaging was included in 2009 with the scanning of 1070 6-to-9-year-old children. The second neuroimaging wave was initiated in April 2013 with a total of 4245 visiting the MRI suite and 4087 9-to-11-year-old children being scanned. The sequences included high-resolution structural MRI, 35-direction diffusion weighted imaging, and a 6 min and 2 s resting-state functional MRI scan. The goal of this paper is to provide an overview of the imaging protocol and the overlap between the neuroimaging data and metadata. We conclude by providing a brief overview of results from our first wave of neuroimaging, which highlights a diverse array of questions that can be addressed by merging the fields of developmental neuroscience and epidemiology.
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Affiliation(s)
- Tonya White
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands.
- Department of Radiology, Erasmus University Medical Centre, Rotterdam, The Netherlands.
- Kinder Neuroimaging Centrum Rotterdam (KNICR), Rotterdam, The Netherlands.
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Hanan El Marroun
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Laura M E Blanken
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Philip Jansen
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Koen Bolhuis
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Desana Kocevska
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Sabine E Mous
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- ENCORE Expertise Centre for Neurodevelopmental Disorders, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Rosa Mulder
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Department of Paediatrics, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Department of Paediatrics, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Aad van der Lugt
- Department of Radiology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Frank C Verhulst
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Kp-2869, Postbus 2060, 3000 CB, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands
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19
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Swagerman SC, van Bergen E, Dolan C, de Geus EJC, Koenis MMG, Hulshoff Pol HE, Boomsma DI. Genetic transmission of reading ability. BRAIN AND LANGUAGE 2017; 172:3-8. [PMID: 26300341 DOI: 10.1016/j.bandl.2015.07.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2015] [Revised: 07/01/2015] [Accepted: 07/16/2015] [Indexed: 05/07/2023]
Abstract
Reading is the processing of written language. Family resemblance for reading (dis)ability might be due to transmission of a genetic liability or due to family environment, including cultural transmission from parents to offspring. Familial-risk studies exploring neurobehavioral precursors for dyslexia and twin studies can only speak to some of these issues, but a combined twin-family study can resolve the nature of the transmitted risk. Word-reading fluency scores of 1100 participants from 431 families (with twins, siblings and their parents) were analyzed to estimate genetic and environmental sources of variance, and to test the presence of assortative mating and cultural transmission. Results show that variation in reading ability is mainly caused by additive and non-additive genetic factors (64%). The substantial assortative mating (rfather-mother=0.38) has scientific and clinical implications. We conclude that parents and offspring tend to resemble each other for genetic reasons, and not due to cultural transmission.
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Affiliation(s)
- Suzanne C Swagerman
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands.
| | - Elsje van Bergen
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands; Department of Experimental Psychology, University of Oxford, 9 South Parks Road, Oxford OX1 3UD, United Kingdom
| | - Conor Dolan
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands; EMGO(+) Institute of Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
| | - Marinka M G Koenis
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
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20
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Van 't Ent D, den Braber A, Baselmans BML, Brouwer RM, Dolan CV, Hulshoff Pol HE, de Geus EJC, Bartels M. Associations between subjective well-being and subcortical brain volumes. Sci Rep 2017; 7:6957. [PMID: 28761095 PMCID: PMC5537231 DOI: 10.1038/s41598-017-07120-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 06/21/2017] [Indexed: 12/26/2022] Open
Abstract
To study the underpinnings of individual differences in subjective well-being (SWB), we tested for associations of SWB with subcortical brain volumes in a dataset of 724 twins and siblings. For significant SWB-brain associations we probed for causal pathways using Mendelian Randomization (MR) and estimated genetic and environmental contributions from twin modeling. Another independent measure of genetic correlation was obtained from linkage disequilibrium (LD) score regression on published genome-wide association summary statistics. Our results indicated associations of SWB with hippocampal volumes but not with volumes of the basal ganglia, thalamus, amygdala, or nucleus accumbens. The SWB-hippocampus relations were nonlinear and characterized by lower SWB in subjects with relatively smaller hippocampal volumes compared to subjects with medium and higher hippocampal volumes. MR provided no evidence for an SWB to hippocampal volume or hippocampal volume to SWB pathway. This was in line with twin modeling and LD-score regression results which indicated non-significant genetic correlations. We conclude that low SWB is associated with smaller hippocampal volume, but that genes are not very important in this relationship. Instead other etiological factors, such as exposure to stress and stress hormones, may exert detrimental effects on SWB and the hippocampus to bring about the observed association.
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Affiliation(s)
- D Van 't Ent
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands. .,Amsterdam Neuroscience, Amsterdam, The Netherlands.
| | - A den Braber
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands
| | - B M L Baselmans
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - R M Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C V Dolan
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - H E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - E J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - M Bartels
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands
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21
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Brouwer RM, Panizzon MS, Glahn DC, Hibar DP, Hua X, Jahanshad N, Abramovic L, de Zubicaray GI, Franz CE, Hansell NK, Hickie IB, Koenis MMG, Martin NG, Mather KA, McMahon KL, Schnack HG, Strike LT, Swagerman SC, Thalamuthu A, Wen W, Gilmore JH, Gogtay N, Kahn RS, Sachdev PS, Wright MJ, Boomsma DI, Kremen WS, Thompson PM, Hulshoff Pol HE. Genetic influences on individual differences in longitudinal changes in global and subcortical brain volumes: Results of the ENIGMA plasticity working group. Hum Brain Mapp 2017; 38:4444-4458. [PMID: 28580697 DOI: 10.1002/hbm.23672] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 05/16/2017] [Accepted: 05/17/2017] [Indexed: 12/12/2022] Open
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 (h2 ) 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 38:4444-4458, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Rachel M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, San Diego, California
| | - David C Glahn
- Department of Psychiatry, Yale University of Medicine, New Haven, Connecticut
| | - Derrek P Hibar
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, California
| | - Xue Hua
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, California
| | - Neda Jahanshad
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, California
| | - Lucija Abramovic
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Greig I de Zubicaray
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Australia
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, California
| | - Narelle K Hansell
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD, Australia
| | - Ian B Hickie
- Clinical Research Unit, Brain & Mind Research Institute, University of Sydney, NSW, Australia
| | - Marinka M G Koenis
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Karen A Mather
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales, Sydney, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | - Hugo G Schnack
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lachlan T Strike
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD, Australia
| | - Suzanne C Swagerman
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales, Sydney, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales, Sydney, Australia
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Nitin Gogtay
- National Institute of Mental Health, Bethesda, Maryland
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales, Sydney, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, California
| | - Paul M Thompson
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, California
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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22
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Sethna V, Pote I, Wang S, Gudbrandsen M, Blasi A, McCusker C, Daly E, Perry E, Adams KPH, Kuklisova-Murgasova M, Busuulwa P, Lloyd-Fox S, Murray L, Johnson MH, Williams SCR, Murphy DGM, Craig MC, McAlonan GM. Mother-infant interactions and regional brain volumes in infancy: an MRI study. Brain Struct Funct 2016; 222:2379-2388. [PMID: 27915378 PMCID: PMC5504257 DOI: 10.1007/s00429-016-1347-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Accepted: 11/25/2016] [Indexed: 12/12/2022]
Abstract
It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme environments in childhood. Less is understood about how normative variations in parent–child interactions are associated with the development of the infant brain in typical settings. To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother–infant interactions and regional brain volumes in a community sample of 3- to 6-month-old infants (N = 39). In addition, we examined whether this relationship differed in male and female infants. We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. These preliminary findings suggest that variations in mother–infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes.
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Affiliation(s)
- Vaheshta Sethna
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK.
| | - Inês Pote
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Siying Wang
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Maria Gudbrandsen
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Anna Blasi
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Caroline McCusker
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Emily Perry
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Kerrie P H Adams
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Maria Kuklisova-Murgasova
- Division of Imaging Sciences and Biomedical Engineering, Centre for the Developing Brain, King's College London, London, UK
| | - Paula Busuulwa
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK.,GKT School of Medical Education, King's College London, London, UK
| | - Sarah Lloyd-Fox
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Lynne Murray
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.,Stellenbosch University, Stellenbosch, South Africa
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Steven C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Michael C Craig
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
| | - Grainne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, PO 50, 16 De Crespigny Park, London, SE5 8A, UK
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23
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Development of brain networks and relevance of environmental and genetic factors: A systematic review. Neurosci Biobehav Rev 2016; 71:215-239. [DOI: 10.1016/j.neubiorev.2016.08.024] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Revised: 07/10/2016] [Accepted: 08/23/2016] [Indexed: 01/25/2023]
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24
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No Evidence of Causal Effects of Blood Pressure on Cognition in the Population at Large. Twin Res Hum Genet 2016; 19:17-26. [PMID: 26810864 DOI: 10.1017/thg.2015.99] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The large body of literature on the association between blood pressure (BP) and cognitive functioning has yielded mixed results, possibly due to the presence of non-linear effects across age, or because BP affects specific brain areas differently, impacting more on some cognitive skills than on others. If a robust association was detected among BP and specific cognitive tasks, the causal nature of reported associations between BP and cognition could be investigated in twin data, which allow a test of alternative explanations, including genetic pleiotropy. The present study first examines the association between BP and cognition in a sample of 1,140 participants with an age range between 10 and 86 years. Linear and quadratic effects of systolic BP (SBP) and diastolic BP (DBP) on cognitive functioning were examined for 17 tests across five functions. Associations were corrected for effects of sex and linear and quadratic effects of age. Second, to test a causal model, data from 123 monozygotic (MZ) twin pairs were analyzed to test whether cognitive functioning of the twins with the higher BP was different from that of the co-twins with lower BP. Associations between BP and cognitive functioning were absent for the majority of the cognitive tests, with the exception of a lower speed of emotion identification and verbal reasoning in subjects with high diastolic BP. In the MZ twin pair analyses, no effects of BP on cognition were found. We conclude that in the population at large, BP level is not associated with cognitive functioning in a clinically meaningful way.
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25
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Budisavljevic S, Kawadler JM, Dell'Acqua F, Rijsdijk FV, Kane F, Picchioni M, McGuire P, Toulopoulou T, Georgiades A, Kalidindi S, Kravariti E, Murray RM, Murphy DG, Craig MC, Catani M. Heritability of the limbic networks. Soc Cogn Affect Neurosci 2015; 11:746-57. [PMID: 26714573 PMCID: PMC4847695 DOI: 10.1093/scan/nsv156] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 12/16/2015] [Indexed: 11/18/2022] Open
Abstract
Individual differences in cognitive ability and social behaviour are influenced by the variability in the structure and function of the limbic system. A strong heritability of the limbic cortex has been previously reported, but little is known about how genetic factors influence specific limbic networks. We used diffusion tensor imaging tractography to investigate heritability of different limbic tracts in 52 monozygotic and 34 dizygotic healthy adult twins. We explored the connections that contribute to the activity of three distinct functional limbic networks, namely the dorsal cingulum (‘medial default-mode network’), the ventral cingulum and the fornix (‘hippocampal-diencephalic-retrosplenial network’) and the uncinate fasciculus (‘temporo-amygdala-orbitofrontal network’). Genetic and environmental variances were mapped for multiple tract-specific measures that reflect different aspects of the underlying anatomy. We report the highest heritability for the uncinate fasciculus, a tract that underpins emotion processing, semantic cognition, and social behaviour. High to moderate genetic and shared environmental effects were found for pathways important for social behaviour and memory, for example, fornix, dorsal and ventral cingulum. These findings indicate that within the limbic system inheritance of specific traits may rely on the anatomy of distinct networks and is higher for fronto-temporal pathways dedicated to complex social behaviour and emotional processing.
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Affiliation(s)
- Sanja Budisavljevic
- Department of Forensic and Neurodevelopmental Sciences, and Natbrainlab, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK, NEMo Laboratory, Department of General Psychology, University of Padova, 35131 Padova, Italy,
| | - Jamie M Kawadler
- Department of Forensic and Neurodevelopmental Sciences, and Natbrainlab, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Flavio Dell'Acqua
- Department of Forensic and Neurodevelopmental Sciences, and Natbrainlab, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | | | | | | | | | - Timothea Toulopoulou
- Department of Psychological Medicine, and Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK, Department of Psychology, and State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong, and
| | - Anna Georgiades
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Sridevi Kalidindi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Eugenia Kravariti
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | | | - Michael C Craig
- Department of Forensic and Neurodevelopmental Sciences, and Natbrainlab, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK, National Autism Unit, South London and Maudsley NHS Foundation Trust, Beckenham, UK
| | - Marco Catani
- Department of Forensic and Neurodevelopmental Sciences, and Natbrainlab, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
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26
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Koenis MMG, Brouwer RM, van den Heuvel MP, Mandl RCW, van Soelen ILC, Kahn RS, Boomsma DI, Hulshoff Pol HE. Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study. Hum Brain Mapp 2015; 36:4938-53. [PMID: 26368846 PMCID: PMC6869380 DOI: 10.1002/hbm.22988] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 07/31/2015] [Accepted: 08/21/2015] [Indexed: 01/25/2023] Open
Abstract
The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual level and, if so, how this relates to intelligence, is unresolved in adolescence. In addition, the influence of genetic factors in the developing network is not known. Therefore, in a longitudinal study of 162 healthy adolescent twins and their siblings (mean age at baseline 9.9 [range 9.0-15.0] years), we mapped local and global structural network efficiency of cerebral fiber pathways (weighted with mean FA and streamline count) and assessed intelligence over a three-year interval. We find that the efficiency of the brain's structural network is highly heritable (locally up to 74%). FA-based local and global efficiency increases during early adolescence. Streamline count based local efficiency both increases and decreases, and global efficiency reorganizes to a net decrease. Local FA-based efficiency was correlated to IQ. Moreover, increases in FA-based network efficiency (global and local) and decreases in streamline count based local efficiency are related to increases in intellectual functioning. Individual changes in intelligence and local FA-based efficiency appear to go hand in hand in frontal and temporal areas. More widespread local decreases in streamline count based efficiency (frontal cingulate and occipital) are correlated with increases in intelligence. We conclude that the teenage brain is a network in progress in which individual differences in maturation relate to level of intellectual functioning.
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Affiliation(s)
- Marinka M G Koenis
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Martijn P van den Heuvel
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - René C W Mandl
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Inge L C van Soelen
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
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27
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Harden KP, Mann FD. Biological Risk for the Development of Problem Behavior in Adolescence: Integrating Insights from Behavioral Genetics and Neuroscience. CHILD DEVELOPMENT PERSPECTIVES 2015; 9:211-216. [PMID: 26664416 PMCID: PMC4671633 DOI: 10.1111/cdep.12135] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Adolescence is a time of increasing engagement in a variety of problem behaviors, including substance use and delinquency. Genetic risk for problem behavior increases over adolescence, is mediated partially by individual differences in sensation seeking, and is exacerbated by involvement with deviant peers. In this article, we describe how findings from behavioral genetic research on problem behavior intersect with research from developmental neuroscience. In particular, the incentive-processing system, including the ventral striatum, responds increasingly to rewards in adolescence, particularly in peer contexts. This developmental shift may be influenced by hormonal changes at puberty. Individual differences in the structure and function of reward-responsive brain regions may be intermediary phenotypes that mediate adolescents' genetic risk for problem behavior. The study of problem behavior can be enriched by interdisciplinary research that integrates measures of brain structure and function into genetically informed studies.
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28
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Mackey S, Kan KJ, Chaarani B, Alia-Klein N, Batalla A, Brooks S, Cousijn J, Dagher A, de Ruiter M, Desrivieres S, Feldstein Ewing SW, Goldstein RZ, Goudriaan AE, Heitzeg MM, Hutchison K, Li CSR, London ED, Lorenzetti V, Luijten M, Martin-Santos R, Morales AM, Paulus MP, Paus T, Pearlson G, Schluter R, Momenan R, Schmaal L, Schumann G, Sinha R, Sjoerds Z, Stein DJ, Stein EA, Solowij N, Tapert S, Uhlmann A, Veltman D, van Holst R, Walter H, Wright MJ, Yucel M, Yurgelun-Todd D, Hibar DP, Jahanshad N, Thompson PM, Glahn DC, Garavan H, Conrod P. Genetic imaging consortium for addiction medicine: From neuroimaging to genes. PROGRESS IN BRAIN RESEARCH 2015; 224:203-23. [PMID: 26822360 PMCID: PMC4820288 DOI: 10.1016/bs.pbr.2015.07.026] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Since the sample size of a typical neuroimaging study lacks sufficient statistical power to explore unknown genomic associations with brain phenotypes, several international genetic imaging consortia have been organized in recent years to pool data across sites. The challenges and achievements of these consortia are considered here with the goal of leveraging these resources to study addiction. The authors of this review have joined together to form an Addiction working group within the framework of the ENIGMA project, a meta-analytic approach to multisite genetic imaging data. Collectively, the Addiction working group possesses neuroimaging and genomic data obtained from over 10,000 subjects. The deadline for contributing data to the first round of analyses occurred at the beginning of May 2015. The studies performed on this data should significantly impact our understanding of the genetic and neurobiological basis of addiction.
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Affiliation(s)
- Scott Mackey
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA.
| | - Kees-Jan Kan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Bader Chaarani
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Nelly Alia-Klein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Albert Batalla
- Department of Psychiatry and Psychology, Hospital Clínic, IDIBAPS, CIBERSAM, University of Barcelona, Barcelona, Spain; Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Samantha Brooks
- Department of Psychiatry and MRC Unit on Anxiety & Stress Disorders, University of Cape Town, Cape Town, South Africa
| | - Janna Cousijn
- Department of Psychiatry and MRC Unit on Anxiety & Stress Disorders, University of Cape Town, Cape Town, South Africa
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Michiel de Ruiter
- Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | | | - Rita Z Goldstein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anna E Goudriaan
- Department of Psychiatry and MRC Unit on Anxiety & Stress Disorders, University of Cape Town, Cape Town, South Africa; Department of Psychiatry, University of Amsterdam, Amsterdam, The Netherlands
| | - Mary M Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Kent Hutchison
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Edythe D London
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Valentina Lorenzetti
- School of Psychological Sciences, Monash Institute of Cognitive and Clinical Neurosciences and Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Maartje Luijten
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Rocio Martin-Santos
- Department of Psychiatry and Psychology, Hospital Clínic, IDIBAPS, CIBERSAM, University of Barcelona, Barcelona, Spain
| | - Angelica M Morales
- David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Martin P Paulus
- VA San Diego Healthcare System and Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Tomas Paus
- Rotman Research Institute, University of Toronto, Toronto, ON, Canada
| | - Godfrey Pearlson
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Renée Schluter
- Department of Psychiatry, University of Amsterdam, Amsterdam, The Netherlands
| | - Reza Momenan
- Section on Brain Electrophysiology and Imaging, Institute on Alcohol Abuse and Alcoholism, Bethesda, USA
| | - Lianne Schmaal
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Rajita Sinha
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Zsuzsika Sjoerds
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dan J Stein
- Department of Psychiatry and MRC Unit on Anxiety & Stress Disorders, University of Cape Town, Cape Town, South Africa
| | - Elliot A Stein
- Intramural Research Program-Neuroimaging Research Branch, National Institute on Drug Abuse, Baltimore, MD, USA
| | - Nadia Solowij
- School of Psychology, University of Wollongong, Wollongong, NSW, Australia
| | - Susan Tapert
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Anne Uhlmann
- Department of Psychiatry and MRC Unit on Anxiety & Stress Disorders, University of Cape Town, Cape Town, South Africa
| | - Dick Veltman
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Ruth van Holst
- Department of Psychiatry, University of Amsterdam, Amsterdam, The Netherlands
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité Universitatsmedizin, Berlin, Germany
| | | | - Murat Yucel
- School of Psychological Sciences, Monash Institute of Cognitive and Clinical Neurosciences and Monash Biomedical Imaging, Monash University, Melbourne, Australia
| | - Deborah Yurgelun-Todd
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Derrek P Hibar
- Department of Neurology, Imaging Genetics Center, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Department of Neurology, Imaging Genetics Center, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Department of Neurology, Imaging Genetics Center, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, QC, Canada
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Regional Cortical Surface Area in Adolescents: A Preliminary MRI Twin Study of Genetic and Environmental Contributions. Behav Genet 2015; 46:205-16. [PMID: 26519369 DOI: 10.1007/s10519-015-9755-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2014] [Accepted: 09/28/2015] [Indexed: 02/05/2023]
Abstract
Cortical surface area (CSA) has particular relevance for understanding development, behavior, and the connection between brain structure and function. Little is known about genetic and environmental determinants of CSA during development. We utilized bivariate twin methods to identify global and regionally specific genetic factors which influence CSA in a preliminary sample of typically-developing adolescents, with hypotheses based on findings in middle-aged adults. Similar to previous findings, we observed high heritability for total CSA. There was also significant evidence for genetic influences on regional CSA, particularly when these were not adjusted for total CSA, with highest heritability in frontal cortex and relatively fewer genetic contributions to medial temporal cortical structures. Adjustment for total CSA reduced regional CSA heritability dramatically, but a moderate influence of genetic factors remained in some regions. Both global and regionally-specific genetic factors influence regional CSA during adolescence.
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Douet V, Chang L, Cloak C, Ernst T. Genetic influences on brain developmental trajectories on neuroimaging studies: from infancy to young adulthood. Brain Imaging Behav 2015; 8:234-50. [PMID: 24077983 DOI: 10.1007/s11682-013-9260-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Human brain development has been studied intensively with neuroimaging. However, little is known about how genes influence developmental brain trajectories, even though a significant number of genes (about 10,000, or approximately one-third) in the human genome are expressed primarily in the brain and during brain development. Interestingly, in addition to showing differential expression among tissues, many genes are differentially expressed across the ages (e.g., antagonistic pleiotropy). Age-specific gene expression plays an important role in several critical events in brain development, including neuronal cell migration, synaptogenesis and neurotransmitter receptor specificity, as well as in aging and neurodegenerative disorders (e.g., Alzheimer disease or amyotrophic lateral sclerosis). In addition, the majority of psychiatric and mental disorders are polygenic, and many have onsets during childhood and adolescence. In this review, we summarize the major findings from neuroimaging studies that link genetics with brain development, from infancy to young adulthood. Specifically, we focus on the heritability of brain structures across the ages, age-related genetic influences on brain development and sex-specific developmental trajectories.
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Affiliation(s)
- Vanessa Douet
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, 96813, USA,
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31
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Longitudinal development of hormone levels and grey matter density in 9 and 12-year-old twins. Behav Genet 2015; 45:313-23. [PMID: 25656383 PMCID: PMC4422848 DOI: 10.1007/s10519-015-9708-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Accepted: 01/16/2015] [Indexed: 12/28/2022]
Abstract
Puberty is characterized by major changes in hormone levels and structural changes in the brain. To what extent these changes are associated and to what extent genes or environmental influences drive such an association is not clear. We acquired circulating levels of luteinizing hormone, follicle stimulating hormone (FSH), estradiol and testosterone and magnetic resonance images of the brain from 190 twins at age 9 [9.2 (0.11) years; 99 females/91 males]. This protocol was repeated at age 12 [12.1 (0.26) years] in 125 of these children (59 females/66 males). Using voxel-based morphometry, we tested whether circulating hormone levels are associated with grey matter density in boys and girls in a longitudinal, genetically informative design. In girls, changes in FSH level between the age of 9 and 12 positively associated with changes in grey matter density in areas covering the left hippocampus, left (pre)frontal areas, right cerebellum, and left anterior cingulate and precuneus. This association was mainly driven by environmental factors unique to the individual (i.e. the non-shared environment). In 12-year-old girls, a higher level of circulating estradiol levels was associated with lower grey matter density in frontal and parietal areas. This association was driven by environmental factors shared among the members of a twin pair. These findings show a pattern of physical and brain development going hand in hand.
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32
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Swagerman SC, Brouwer RM, de Geus EJC, Hulshoff Pol HE, Boomsma DI. Development and heritability of subcortical brain volumes at ages 9 and 12. GENES BRAIN AND BEHAVIOR 2014; 13:733-42. [DOI: 10.1111/gbb.12182] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Revised: 10/09/2014] [Accepted: 10/11/2014] [Indexed: 02/05/2023]
Affiliation(s)
- S. C. Swagerman
- Department of Biological Psychology; VU University Amsterdam; Amsterdam The Netherlands
| | - R. M. Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry; University Medical Center Utrecht; Utrecht The Netherlands
| | - E. J. C. de Geus
- Department of Biological Psychology; VU University Amsterdam; Amsterdam The Netherlands
- Emgo Institute for Health and Care Research; VU University Medical Center; Amsterdam The Netherlands
| | - H. E. Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry; University Medical Center Utrecht; Utrecht The Netherlands
| | - D. I. Boomsma
- Department of Biological Psychology; VU University Amsterdam; Amsterdam The Netherlands
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33
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de Zeeuw EL, van Beijsterveldt CEM, Glasner TJ, Bartels M, Ehli EA, Davies GE, Hudziak JJ, Rietveld CA, Groen-Blokhuis MM, Hottenga JJ, de Geus EJC, Boomsma DI. Polygenic scores associated with educational attainment in adults predict educational achievement and ADHD symptoms in children. Am J Med Genet B Neuropsychiatr Genet 2014; 165B:510-20. [PMID: 25044548 DOI: 10.1002/ajmg.b.32254] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2014] [Accepted: 06/02/2014] [Indexed: 12/31/2022]
Abstract
The American Psychiatric Association estimates that 3 to 7 per cent of all school aged children are diagnosed with attention deficit hyperactivity disorder (ADHD). Even after correcting for general cognitive ability, numerous studies report a negative association between ADHD and educational achievement. With polygenic scores we examined whether genetic variants that have a positive influence on educational attainment have a protective effect against ADHD. The effect sizes from a large GWA meta-analysis of educational attainment in adults were used to calculate polygenic scores in an independent sample of 12-year-old children from the Netherlands Twin Register. Linear mixed models showed that the polygenic scores significantly predicted educational achievement, school performance, ADHD symptoms and attention problems in children. These results confirm the genetic overlap between ADHD and educational achievement, indicating that one way to gain insight into genetic variants responsible for variation in ADHD is to include data on educational achievement, which are available at a larger scale.
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Affiliation(s)
- Eveline L de Zeeuw
- Department of Biological Psychology, VU University, Amsterdam, the Netherlands; EMGO+ Institute for Health and Care Research, VU University Medical Centre, Amsterdam, the Netherlands
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34
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Kochunov P, Jahanshad N, Sprooten E, Nichols TE, Mandl RC, Almasy L, Booth T, Brouwer RM, Curran JE, de Zubicaray GI, Dimitrova R, Duggirala R, Fox PT, Hong LE, Landman BA, Lemaitre H, Lopez LM, Martin NG, McMahon KL, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Wright SN, Bastin ME, McIntosh AM, Boomsma DI, Kahn RS, den Braber A, de Geus EJC, Deary IJ, Hulshoff Pol HE, Williamson DE, Blangero J, van 't Ent D, Thompson PM, Glahn DC. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling. Neuroimage 2014; 95:136-50. [PMID: 24657781 PMCID: PMC4043878 DOI: 10.1016/j.neuroimage.2014.03.033] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2013] [Revised: 02/21/2014] [Accepted: 03/04/2014] [Indexed: 01/25/2023] Open
Abstract
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Emma Sprooten
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
| | - Thomas E Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK; Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford University, UK
| | - René C Mandl
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Rachel M Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Rali Dimitrova
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bennett A Landman
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Hervé Lemaitre
- U1000 Research Unit Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris-Sud, Orsay, France
| | - Lorna M Lopez
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | | | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Charles P Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Jessika E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Arthur W Toga
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Susan N Wright
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Douglas E Williamson
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dennis van 't Ent
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA; Department of Neurology, Pediatrics, Engineering, Psychiatry, Radiology, & Ophthalmology, University of Southern California, Los Angeles, CA, USA
| | - David C Glahn
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
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35
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Thompson PM, Stein JL, Medland SE, Hibar DP, Vasquez AA, Renteria ME, Toro R, Jahanshad N, Schumann G, Franke B, Wright MJ, Martin NG, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Andreasen NC, Andreassen OA, Apostolova LG, Appel K, Armstrong NJ, Aribisala B, Bastin ME, Bauer M, Bearden CE, Bergmann Ø, Binder EB, Blangero J, Bockholt HJ, Bøen E, Bois C, Boomsma DI, Booth T, Bowman IJ, Bralten J, Brouwer RM, Brunner HG, Brohawn DG, Buckner RL, Buitelaar J, Bulayeva K, Bustillo JR, Calhoun VD, Cannon DM, Cantor RM, Carless MA, Caseras X, Cavalleri GL, Chakravarty MM, Chang KD, Ching CRK, Christoforou A, Cichon S, Clark VP, Conrod P, Coppola G, Crespo-Facorro B, Curran JE, Czisch M, Deary IJ, de Geus EJC, den Braber A, Delvecchio G, Depondt C, de Haan L, de Zubicaray GI, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Dyer TD, Ehrlich S, Ekman CJ, Elvsåshagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernández G, Fisher SE, Foroud T, Fox PT, Francks C, Frangou S, Frey EM, Frodl T, Frouin V, Garavan H, Giddaluru S, Glahn DC, Godlewska B, Goldstein RZ, Gollub RL, Grabe HJ, Grimm O, Gruber O, Guadalupe T, Gur RE, Gur RC, Göring HHH, Hagenaars S, Hajek T, Hall GB, Hall J, Hardy J, Hartman CA, Hass J, Hatton SN, Haukvik UK, Hegenscheid K, Heinz A, Hickie IB, Ho BC, Hoehn D, Hoekstra PJ, Hollinshead M, Holmes AJ, Homuth G, Hoogman M, Hong LE, Hosten N, Hottenga JJ, Hulshoff Pol HE, Hwang KS, Jack CR, Jenkinson M, Johnston C, Jönsson EG, Kahn RS, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Krämer B, Kwok JBJ, Lagopoulos J, Laje G, Landen M, Landman BA, Lauriello J, Lawrie SM, Lee PH, Le Hellard S, Lemaître H, Leonardo CD, Li CS, Liberg B, Liewald DC, Liu X, Lopez LM, Loth E, Lourdusamy A, Luciano M, Macciardi F, Machielsen MWJ, MacQueen GM, Malt UF, Mandl R, Manoach DS, Martinot JL, Matarin M, Mather KA, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, McIntosh AM, McMahon FJ, McMahon KL, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Montgomery GW, Morris DW, Moses EK, Mueller BA, Muñoz Maniega S, Mühleisen TW, Müller-Myhsok B, Mwangi B, Nauck M, Nho K, Nichols TE, Nilsson LG, Nugent AC, Nyberg L, Olvera RL, Oosterlaan J, Ophoff RA, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Pearlson GD, Penninx BW, Peterson CP, Pfennig A, Phillips M, Pike GB, Poline JB, Potkin SG, Pütz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Risacher SL, Roffman JL, Roiz-Santiañez R, Romanczuk-Seiferth N, Rose EJ, Royle NA, Rujescu D, Ryten M, Sachdev PS, Salami A, Satterthwaite TD, Savitz J, Saykin AJ, Scanlon C, Schmaal L, Schnack HG, Schork AJ, Schulz SC, Schür R, Seidman L, Shen L, Shoemaker JM, Simmons A, Sisodiya SM, Smith C, Smoller JW, Soares JC, Sponheim SR, Sprooten E, Starr JM, Steen VM, Strakowski S, Strike L, Sussmann J, Sämann PG, Teumer A, Toga AW, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, van der Wee NJ, van Eijk K, van Erp TGM, van Haren NEM, van ‘t Ent D, van Tol MJ, Valdés Hernández MC, Veltman DJ, Versace A, Völzke H, Walker R, Walter H, Wang L, Wardlaw JM, Weale ME, Weiner MW, Wen W, Westlye LT, Whalley HC, Whelan CD, White T, Winkler AM, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Zwiers MP, Thalamuthu A, Schofield PR, Freimer NB, Lawrence NS, Drevets W. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav 2014; 8:153-82. [PMID: 24399358 PMCID: PMC4008818 DOI: 10.1007/s11682-013-9269-5] [Citation(s) in RCA: 499] [Impact Index Per Article: 49.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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Affiliation(s)
- Paul M. Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Jason L. Stein
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095 Netherlands
| | - Sarah E. Medland
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
| | - Derrek P. Hibar
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Alejandro Arias Vasquez
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Miguel E. Renteria
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- CNRS URA 2182 ‘Genes, synapses and cognition’, Institut Pasteur, Paris, France
- Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Université Paris Diderot, Paris, France
| | - Neda Jahanshad
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Gunter Schumann
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Margaret J. Wright
- QIMR Berghofer Medical Research Institute, Neuroimaging Genetics, Brisbane, Australia
| | - Nicholas G. Martin
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology, Brisbane, Australia
| | - Ingrid Agartz
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
- Department of Neurology and NeuroSurgery, McGill University, Montreal, Quebec Canada
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Jorge Almeida
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Kathryn Alpert
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
| | | | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Liana G. Apostolova
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
| | - Katja Appel
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
| | - Nicola J. Armstrong
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
| | - Benjamin Aribisala
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
| | - Carrie E. Bearden
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
- Department of Psychology, UCLA, Los Angeles, CA USA
| | - Ørjan Bergmann
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | | | - Erlend Bøen
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Catherine Bois
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Ian J. Bowman
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Rachel M. Brouwer
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Han G. Brunner
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - David G. Brohawn
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Randy L. Buckner
- Massachusetts General Hospital, Boston, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Jan Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Kazima Bulayeva
- N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin str. 3, Moscow, 119991 Russia
| | - Juan R. Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, NM USA
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM USA
| | - Dara M. Cannon
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Rita M. Cantor
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
| | - Melanie A. Carless
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Gianpiero L. Cavalleri
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - M. Mallar Chakravarty
- The Kimel Family Translational Imaging Genetics Laboratory, The Centre for Addiction and Mental Health, Toronto, ON Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON Canada
| | - Kiki D. Chang
- Department of Psychiatry, Stanford University School of Medicine, Stanford, CA USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Andrea Christoforou
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Sven Cichon
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Vincent P. Clark
- Department of Psychology, University of New Mexico, Albuquerque, NM USA
| | - Patricia Conrod
- CHU Sainte Justine University Hospital Research Center, Montreal, QC Canada
- Addictions Department, King’s Health Partners, King’s College London, London, UK
| | - Giovanni Coppola
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Joanne E. Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | | | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Eco J. C. de Geus
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | | | - Chantal Depondt
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
| | - Lieuwe de Haan
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Danai Dima
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | - Rali Dimitrova
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Srdjan Djurovic
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Hongwei Dong
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Gary Donohoe
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | | | - Thomas D. Dyer
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Stefan Ehrlich
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
| | - Carl Johan Ekman
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - Torbjørn Elvsåshagen
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Louise Emsell
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Susanne Erk
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Thomas Espeseth
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Jesen Fagerness
- Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Scott Fears
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
| | - Iryna Fedko
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | - Guillén Fernández
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Simon E. Fisher
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Peter T. Fox
- Research Imaging Institute, UT Health Science Center at San Antonio, San Antonio, TX USA
- South Texas Veterans Health Care Center, San Antonio, TX USA
- South Texas Veterans Health Care System, San Antonio, TX USA
| | - Clyde Francks
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Sophia Frangou
- Psychosis Research Unit, Mount Sinai School of Medicine, New York, NY USA
| | - Eva Maria Frey
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
- Department of Psychiatry and Psychotherapy, Trinity College, University Dublin, Dublin, Germany
| | - Vincent Frouin
- Neurospin, Commissariat à l’Energie Atomique, Paris, France
| | - Hugh Garavan
- Department of Psychiatry, UHC University of Vermont, Bergen, VT USA
| | - Sudheer Giddaluru
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | | | - Rita Z. Goldstein
- Department of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Randy L. Gollub
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, Stralsund, Germany
| | - Oliver Grimm
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Oliver Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Tulio Guadalupe
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
- Philadelphia Veterans Administration Medical Center, Philadelphia, PA USA
| | - Harald H. H. Göring
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Saskia Hagenaars
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Geoffrey B. Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON Canada
| | - Jeremy Hall
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
| | - John Hardy
- Department of Molecular Neuroscience, UCL Institute, London, UK
| | - Catharina A. Hartman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Johanna Hass
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
| | - Sean N. Hatton
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Unn K. Haukvik
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Katrin Hegenscheid
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Ian B. Hickie
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Beng-Choon Ho
- Department of Psychiatry, University of Iowa, Iowa City, IA USA
| | - David Hoehn
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Pieter J. Hoekstra
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marisa Hollinshead
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Avram J. Holmes
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
| | - Norbert Hosten
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | | | - Kristy S. Hwang
- Oakland University William Beaumont School of Medicine, Rochester Hills, MI USA
| | | | - Mark Jenkinson
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Caroline Johnston
- National Institute of Health Research Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service Foundation Trust, London, UK
- King’s College London, Institute of Psychiatry, London, UK
| | - Erik G. Jönsson
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - René S. Kahn
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dalia Kasperaviciute
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Sinead Kelly
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | - Sungeun Kim
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
| | - Laura Koenders
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Bernd Krämer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - John B. J. Kwok
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Kensington, NSW Australia
| | - Jim Lagopoulos
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Gonzalo Laje
- Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, MD USA
| | - Mikael Landen
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - John Lauriello
- Department of Psychiatry, University of Missouri, Columbia, MO USA
| | - Stephen M. Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Phil H. Lee
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Stephanie Le Hellard
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Herve Lemaître
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
| | - Cassandra D. Leonardo
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Chiang-shan Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | - Benny Liberg
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - David C. Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Xinmin Liu
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
- Taub Institute for Research on Alzheimer Disease and the Aging Brain, Columbia University Medical Center, New York, NY USA
| | - Lorna M. Lopez
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Eva Loth
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | | | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | | | - Glenda M. MacQueen
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta Canada
| | - Ulrik F. Malt
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - René Mandl
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dara S. Manoach
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Jean-Luc Martinot
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
| | - Mar Matarin
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Karen A. Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
| | - Manuel Mattheisen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Genomic Mathematics, University of Bonn, Bonn, Germany
| | - Morten Mattingsdal
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research Unit, Sorlandet Hospital HF, Kristiansand, Norway
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Andrew M. McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Francis J. McMahon
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
| | - Katie L. McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | | | - Ingrid Melle
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yuri Milaneschi
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD USA
| | - Sebastian Mohnke
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Grant W. Montgomery
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
| | - Derek W. Morris
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | - Eric K. Moses
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
- Centre for Genetic Origins of Health and Disease, The University of Western Australia, Perth, Australia
| | - Bryon A. Mueller
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Thomas W. Mühleisen
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
| | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Benson Mwangi
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
- University of Texas Center of Excellence on Mood Disorders, Department of Psychiatry, UT Medical School, Houston, TX USA
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | - Thomas E. Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK
| | - Lars-Göran Nilsson
- Department of Psychology, Stockholm University, Stockholm, Sweden
- Stockholm Brain Institute, Stockholm, Sweden
| | - Allison C. Nugent
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD USA
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Rene L. Olvera
- Department of Psychiatry, UT Health Science Center at San Antonio, San Antonio, TX USA
| | - Jaap Oosterlaan
- Department of Clinical Neuropsychology, VU University, Amsterdam, The Netherlands
| | - Roel A. Ophoff
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
| | - Massimo Pandolfo
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
| | | | - Martina Papmeyer
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Tomas Paus
- Rotman Research Institute, University of Toronto, Toronto, ON Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
| | - Godfrey D. Pearlson
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT USA
| | - Brenda W. Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Charles P. Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
| | - Mary Phillips
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - G. Bruce Pike
- Department of Radiology, University of Calgary, Calgary, Alberta Canada
| | - Jean-Baptiste Poline
- Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, Berkeley, CA USA
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | - Benno Pütz
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Adaikalavan Ramasamy
- Department of Medical and Molecular Genetics, King’s College London, London, UK
- Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Jerod Rasmussen
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | - Marcella Rietschel
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Mark Rijpkema
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
| | - Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Roberto Roiz-Santiañez
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Nina Romanczuk-Seiferth
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Emma J. Rose
- Transdisciplinary and Translational Prevention Program, RTI International, Baltimore, MD USA
| | - Natalie A. Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Dan Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Mina Ryten
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Medical and Molecular Genetics, King’s College London, London, UK
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales Australia
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | | | - Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK USA
- Faculty of Community Medicine, University of Tulsa, Tulsa, OK USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Cathy Scanlon
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Lianne Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo G. Schnack
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - S. Charles Schulz
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
| | - Remmelt Schür
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Larry Seidman
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA USA
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA USA
| | - Li Shen
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | | | - Andrew Simmons
- Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Trust and Institute of Psychiatry, King’s College London, London, UK
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Colin Smith
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Jordan W. Smoller
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Jair C. Soares
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
| | - Scott R. Sponheim
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
- Minneapolis VA Health Care System, Minneapolis, MN USA
| | - Emma Sprooten
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Vidar M. Steen
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Stephen Strakowski
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Lachlan Strike
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
| | - Jessika Sussmann
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | | | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Arthur W. Toga
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Diana Tordesillas-Gutierrez
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Daniah Trabzuni
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Sarah Trost
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Jessica Turner
- The Mind Research Network, Albuquerque, NM USA
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA USA
| | | | - Nic J. van der Wee
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
| | - Kristel van Eijk
- Department of Psychiatry, Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Theo G. M. van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | | | - Dennis van ‘t Ent
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | - Marie-Jose van Tol
- Behavioural and Cognitive Neuroscience Neuroimaging Center, University Medical Center Groningen, Groningen, The Netherlands
| | - Maria C. Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Dick J. Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Henry Völzke
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
| | - Robert Walker
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt University Berlin, Berlin, Germany
| | - Lei Wang
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
| | - Joanna M. Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Michael E. Weale
- Department of Medical and Molecular Genetics, King’s College London, London, UK
| | - Michael W. Weiner
- Departments of Radiology, Medicine, Psychiatry, University of California, San Francisco, CA USA
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
| | - Lars T. Westlye
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Heather C. Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Christopher D. Whelan
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - Tonya White
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Anderson M. Winkler
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
| | - Girma Woldehawariat
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
| | | | - David Zilles
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Marcel P. Zwiers
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud University NijmegenDonders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Nelson B. Freimer
- Department of Psychiatry and Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA USA
| | | | - Wayne Drevets
- Janssen Research & Development, of Johnson & Johnson, Inc., 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| | - the Alzheimer’s Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- CNRS URA 2182 ‘Genes, synapses and cognition’, Institut Pasteur, Paris, France
- Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Université Paris Diderot, Paris, France
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
- Department of Psychiatry, University of Iowa, Iowa City, IA USA
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
- Max Planck Institute of Psychiatry, Munich, Germany
- The Mind Research Network, Albuquerque, NM USA
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Massachusetts General Hospital, Boston, MA USA
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
- N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin str. 3, Moscow, 119991 Russia
- Department of Psychiatry, University of New Mexico, Albuquerque, NM USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM USA
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
- The Kimel Family Translational Imaging Genetics Laboratory, The Centre for Addiction and Mental Health, Toronto, ON Canada
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
- School of Psychology, University of Queensland, Brisbane, QLD 4072 Australia
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
- Research Imaging Institute, UT Health Science Center at San Antonio, San Antonio, TX USA
- South Texas Veterans Health Care Center, San Antonio, TX USA
- Neurospin, Commissariat à l’Energie Atomique, Paris, France
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
- National Institute of Health Research Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service Foundation Trust, London, UK
- King’s College London, Institute of Psychiatry, London, UK
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
- Taub Institute for Research on Alzheimer Disease and the Aging Brain, Columbia University Medical Center, New York, NY USA
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Genomic Mathematics, University of Bonn, Bonn, Germany
- Research Unit, Sorlandet Hospital HF, Kristiansand, Norway
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
- Ludwig-Maximilians-University (LMU), Munich, Germany
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Centre for Genetic Origins of Health and Disease, The University of Western Australia, Perth, Australia
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
- Department of Psychology, Stockholm University, Stockholm, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Department of Psychiatry, UT Health Science Center at San Antonio, San Antonio, TX USA
- Rotman Research Institute, University of Toronto, Toronto, ON Canada
- The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
- Department of Medical and Molecular Genetics, King’s College London, London, UK
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales Australia
- Laureate Institute for Brain Research, Tulsa, OK USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA USA
- Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Trust and Institute of Psychiatry, King’s College London, London, UK
- Minneapolis VA Health Care System, Minneapolis, MN USA
- Behavioural and Cognitive Neuroscience Neuroimaging Center, University Medical Center Groningen, Groningen, The Netherlands
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
- Departments of Radiology, Medicine, Psychiatry, University of California, San Francisco, CA USA
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Radboud University NijmegenDonders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
- Center for Brain Science, Harvard University, Cambridge, MA USA
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Department Early Psychosis, Academic Psychiatric Centre, AMC, UvA, Amsterdam, Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
- Cognitive Science Department, UC San Diego, La Jolla, CA USA
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuropsychology, VU University, Amsterdam, The Netherlands
- Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Department of Neurology and NeuroSurgery, McGill University, Montreal, Quebec Canada
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
- University of Texas Center of Excellence on Mood Disorders, Department of Psychiatry, UT Medical School, Houston, TX USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD USA
- Berlin School of Mind and Brain, Humboldt University Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
- Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, Stralsund, Germany
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA USA
- Department of Psychiatry, Brown University, Providence, RI USA
- Psychosis Research Unit, Mount Sinai School of Medicine, New York, NY USA
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
- Philadelphia Veterans Administration Medical Center, Philadelphia, PA USA
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
- Department of Psychiatry and Psychotherapy, Trinity College, University Dublin, Dublin, Germany
- Stockholm Brain Institute, Stockholm, Sweden
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA USA
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON Canada
- Department of Psychology, University of New Mexico, Albuquerque, NM USA
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology, University of Calgary, Calgary, Alberta Canada
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
- Electrical Engineering, Vanderbilt University, Nashville, TN USA
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD USA
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON Canada
- Faculty of Community Medicine, University of Tulsa, Tulsa, OK USA
- Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, MD USA
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta Canada
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- School of Medical Sciences, University of New South Wales, Kensington, NSW Australia
- Oakland University William Beaumont School of Medicine, Rochester Hills, MI USA
- CHU Sainte Justine University Hospital Research Center, Montreal, QC Canada
- Addictions Department, King’s Health Partners, King’s College London, London, UK
- South Texas Veterans Health Care System, San Antonio, TX USA
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- Department of Psychiatry, Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
- School of Medicine, University of Nottingham, Nottingham, UK
- Department of Psychiatry, Stanford University School of Medicine, Stanford, CA USA
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, Berkeley, CA USA
- Department of Psychiatry, University of Missouri, Columbia, MO USA
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT USA
- Mayo Clinic, Rochester, MN USA
- Transdisciplinary and Translational Prevention Program, RTI International, Baltimore, MD USA
- Department of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Psychiatry, University of Halle, Halle, Germany
- Advanced Biomedical Informatics Group, llc., Iowa City, IA USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095 Netherlands
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology, Brisbane, Australia
- QIMR Berghofer Medical Research Institute, Neuroimaging Genetics, Brisbane, Australia
- Department of Psychology, UCLA, Los Angeles, CA USA
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
- Dr. E. Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
- Department of Psychiatry, UHC University of Vermont, Bergen, VT USA
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales (UNSW), Sydney, Australia
- Department of Psychiatry and Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA USA
- School of Psychology, University of Exeter, Exeter, UK
- Janssen Research & Development, of Johnson & Johnson, Inc., 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
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Bohlken MM, Brouwer RM, Mandl RC, van Haren NE, Brans RG, van Baal GCM, de Geus EJ, Boomsma DI, Kahn RS, Hulshoff Pol HE. Genes contributing to subcortical volumes and intellectual ability implicate the thalamus. Hum Brain Mapp 2014; 35:2632-42. [PMID: 24038793 PMCID: PMC6869799 DOI: 10.1002/hbm.22356] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Revised: 06/03/2013] [Accepted: 06/10/2013] [Indexed: 12/31/2022] Open
Abstract
It has been shown that brain volume and general intellectual ability are to a significant extent influenced by the same genetic factors. Several cortical regions of the brain also show a genetic correlation with intellectual ability, demonstrating that intellectual functioning is probably represented in a heritable distributed network of cortical regions throughout the brain. This study is the first to investigate a genetic association between subcortical volumes and intellectual ability, taking into account the thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens using an extended twin design. Genetic modeling was performed on a healthy adult twin sample consisting of 106 twin pairs and 30 of their siblings, IQ data was obtained from 132 subjects. Our results demonstrate that of all subcortical volumes measured, only thalamus volume is significantly correlated with intellectual functioning. Importantly, the association found between thalamus volume and intellectual ability is significantly influenced by a common genetic factor. This genetic factor is also implicated in cerebral brain volume. The thalamus, with its widespread cortical connections, may thus play a key role in human intelligence.
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Affiliation(s)
| | | | | | | | | | | | | | | | - René S. Kahn
- Department of PsychiatryUMC UtrechtThe Netherlands
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Da Mota B, Tudoran R, Costan A, Varoquaux G, Brasche G, Conrod P, Lemaitre H, Paus T, Rietschel M, Frouin V, Poline JB, Antoniu G, Thirion B. Machine learning patterns for neuroimaging-genetic studies in the cloud. Front Neuroinform 2014; 8:31. [PMID: 24782753 PMCID: PMC3986524 DOI: 10.3389/fninf.2014.00031] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2013] [Accepted: 03/17/2014] [Indexed: 02/03/2023] Open
Abstract
Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.
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Affiliation(s)
- Benoit Da Mota
- Parietal Team, INRIA Saclay, Île-de-France Saclay, France ; CEA, DSV, I2BM, Neurospin Gif-sur-Yvette, France
| | - Radu Tudoran
- KerData Team, INRIA Rennes - Bretagne Atlantique Rennes, France
| | | | - Gaël Varoquaux
- Parietal Team, INRIA Saclay, Île-de-France Saclay, France ; CEA, DSV, I2BM, Neurospin Gif-sur-Yvette, France
| | - Goetz Brasche
- Microsoft, Advance Technology Lab Europe Munich, Germany
| | - Patricia Conrod
- Institute of Psychiatry, King's College London London, UK ; Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital Montreal, QC, Canada
| | - Herve Lemaitre
- Institut National de la Santé et de la Recherche Médicale, INSERM CEA Unit 1000 "Imaging & Psychiatry," University Paris Sud, Orsay, and AP-HP Department of Adolescent Psychopathology and Medicine, Maison de Solenn, University Paris Descartes Paris, France
| | - Tomas Paus
- Rotman Research Institute, University of Toronto Toronto, ON, Canada ; School of Psychology, University of Nottingham Nottingham, UK ; Montreal Neurological Institute, McGill University Montréal, QC, Canada
| | - Marcella Rietschel
- Central Institute of Mental Health Mannheim, Germany ; Medical Faculty Mannheim, University of Heidelberg Heidelberg, Germany
| | | | - Jean-Baptiste Poline
- CEA, DSV, I2BM, Neurospin Gif-sur-Yvette, France ; Henry H. Wheeler Jr. Brain Imaging Center, University of California at Berkeley Berkeley, CA, USA
| | - Gabriel Antoniu
- KerData Team, INRIA Rennes - Bretagne Atlantique Rennes, France
| | - Bertrand Thirion
- Parietal Team, INRIA Saclay, Île-de-France Saclay, France ; CEA, DSV, I2BM, Neurospin Gif-sur-Yvette, France
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Vijayakumar N, Whittle S, Yücel M, Dennison M, Simmons J, Allen NB. Prefrontal structural correlates of cognitive control during adolescent development: a 4-year longitudinal study. J Cogn Neurosci 2013; 26:1118-30. [PMID: 24345180 DOI: 10.1162/jocn_a_00549] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Maturation of cognitive control abilities has been attributed to the protracted structural maturation of underlying neural correlates during adolescence. This study examined the relationship between development of two forms of cognitive control (proactive and reactive control) and structural maturation of the ACC, dorsolateral pFC, and ventrolateral pFC (vlPFC) between early and mid adolescence using a longitudinal design. Adolescents (n = 92) underwent baseline assessments when they were 12 years old and follow-up assessments approximately 4 years later. At each assessment, structural MRI scans were acquired, and a modified Stroop task was performed. Results showed longitudinal improvements in reactive control between early and mid adolescence. Furthermore, magnitude of the improvement in proactive control was associated with reduced thinning of the right vlPFC across the sample, whereas the magnitude of the improvements in reactive control was associated with reduced thinning of the left ACC in men alone. These findings suggest that individual differences in the maturation of ACC and vlPFC underlie the development of two distinct forms of cognitive control between early and mid adolescence as well as highlight sex differences in this relationship.
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Winham SJ, Biernacka JM. Gene-environment interactions in genome-wide association studies: current approaches and new directions. J Child Psychol Psychiatry 2013; 54:1120-34. [PMID: 23808649 PMCID: PMC3829379 DOI: 10.1111/jcpp.12114] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/03/2013] [Indexed: 01/20/2023]
Abstract
BACKGROUND Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized gene-environment interactions are now fairly common in human genetic research, and with the shift toward genome-wide association studies, genome-wide gene-environment interaction studies are beginning to emerge. METHODS We summarize the basic ideas behind gene-environment interaction, and provide an overview of possible study designs and traditional analysis methods in the context of genome-wide analysis. We then discuss novel approaches beyond the traditional strategy of analyzing the interaction between the environmental factor and each polymorphism individually. RESULTS Two-step filtering approaches that reduce the number of polymorphisms tested for interactions can substantially increase the power of genome-wide gene-environment studies. New analytical methods including data-mining approaches, and gene-level and pathway-level analyses, also have the capacity to improve our understanding of how complex genetic and environmental factors interact to influence psychologic and psychiatric traits. Such methods, however, have not yet been utilized much in behavioral and mental health research. CONCLUSIONS Although methods to investigate gene-environment interactions are available, there is a need for further development and extension of these methods to identify gene-environment interactions in the context of genome-wide association studies. These novel approaches need to be applied in studies of psychology and psychiatry.
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Affiliation(s)
- Stacey J Winham
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester MN 55905
| | - Joanna M. Biernacka
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester MN 55905,Department of Psychiatry and Psychology, Mayo Clinic, Rochester MN 55905
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Kremen WS, Fennema-Notestine C, Eyler LT, Panizzon MS, Chen CH, Franz CE, Lyons MJ, Thompson WK, Dale AM. Genetics of brain structure: contributions from the Vietnam Era Twin Study of Aging. Am J Med Genet B Neuropsychiatr Genet 2013; 162B:751-61. [PMID: 24132907 PMCID: PMC4754776 DOI: 10.1002/ajmg.b.32162] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2012] [Accepted: 03/15/2013] [Indexed: 11/09/2022]
Abstract
Understanding the genetics of neuropsychiatric disorders requires an understanding of the genetics of brain structure and function. The Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study focused on cognitive and brain aging. Here, we describe basic science work carried out within the VETSA MRI study that provides meaningful contributions toward the study of neuropsychiatric disorders. VETSA produced the first comprehensive assessment of the heritability of cortical and subcortical brain structure sizes, all within the same individuals. We showed that neocortical thickness and surface area are largely genetically distinct. With continuous neocortical thickness maps, we demonstrated regional specificity of genetic influences, and that genetic factors did not conform to traditional regions of interest (ROIs). However, there was some evidence for different genetic factors accounting for different types of cortex, and for genetic relationships across cortical regions corresponding to anatomical and functional connectivity and brain maturation patterns. With continuous neocortical surface area maps, we confirmed the anterior-posterior gradient of genetic influences on cortical area patterning demonstrated in animal models. Finally, we used twin methods to create the first map of cortical ROIs based entirely on genetically informative data. We conclude that these genetically based cortical phenotypes may be more appropriate for genetic studies than traditional ROIs based on structure or function. Our results also suggest that cortical volume-the product of thickness and surface area-is a problematic phenotype for genetic studies because two independent sets of genes may be obscured. Examples supporting the validity of these conclusions are provided.
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Affiliation(s)
- William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Twin Research Laboratory, Center for Behavioral Genomics, University of California, San Diego, La Jolla, California,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, California,Correspondence to: William S. Kremen, Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093.,
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Department of Radiology, University of California, San Diego, La Jolla, California
| | - Lisa T. Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, La Jolla, California
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Twin Research Laboratory, Center for Behavioral Genomics, University of California, San Diego, La Jolla, California
| | - Chi-Hua Chen
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Twin Research Laboratory, Center for Behavioral Genomics, University of California, San Diego, La Jolla, California
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Twin Research Laboratory, Center for Behavioral Genomics, University of California, San Diego, La Jolla, California
| | - Michael J. Lyons
- Department of Psychology, Boston University, Boston, Massachusetts
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Twin Research Laboratory, Center for Behavioral Genomics, University of California, San Diego, La Jolla, California
| | - Anders M. Dale
- Department of Psychiatry, University of California, San Diego, La Jolla, California,Department of Radiology, University of California, San Diego, La Jolla, California,Department of Neurosciences, University of California, San Diego, La Jolla, California
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Networks of anatomical covariance. Neuroimage 2013; 80:489-504. [PMID: 23711536 DOI: 10.1016/j.neuroimage.2013.05.054] [Citation(s) in RCA: 306] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2013] [Revised: 05/08/2013] [Accepted: 05/09/2013] [Indexed: 01/18/2023] Open
Abstract
Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.
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Koenis MMG, Brouwer RM, van Baal GCM, van Soelen ILC, Peper JS, van Leeuwen M, Delemarre-van de Waal HA, Boomsma DI, Hulshoff Pol HE. Longitudinal study of hormonal and physical development in young twins. J Clin Endocrinol Metab 2013; 98:E518-27. [PMID: 23430788 DOI: 10.1210/jc.2012-3361] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
CONTEXT AND OBJECTIVE Information on the correlation of normative reproductive hormone levels with physical development (Tanner stages) during puberty and on the influences of genes and environment on variation in these hormones and Tanner stages is limited. DESIGN, SETTING, AND PARTICIPANTS One hundred twelve healthy 9-year-old twin pairs (n = 224) took part in a longitudinal study, of which 89 pairs participated again at age 12 years (n = 178). MAIN OUTCOME MEASURES Morning urinary LH, FSH, estradiol, and salivary testosterone levels, determined by competitive immunoassays, were measured. Tanner stages were determined through physical examination. RESULTS Over the 3-year interval, all hormone levels showed a 2- to 9-fold increase. LH and FSH at age 9 years predicted sex-specific Tanner stages at age 12 years in both boys and girls. Most of the associations between hormone levels at age 9 years and physical development at 12 years were explained by genetic influences. FSH in 9-year-old boys correlated with all hormone levels and Tanner stages at age 12 years. Moderate to high heritability estimates were found for hormone levels at both ages and in both sexes. In girls a shift from environmental (age 9 years) to genetic influences (age 12 years) was found for estradiol and pubic hair development, and for breast development a shift in the opposite direction was seen. CONCLUSIONS During development LH and FSH (and testosterone in boys) levels predict secondary sexual characteristics in boys and girls 3 years later. These correlations are largely due to genes that are involved in both early pubertal hormone levels and subsequent physical development.
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Affiliation(s)
- M M G Koenis
- Department of Psychiatry, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
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Vink JM, Bartels M, van Beijsterveldt TCEM, van Dongen J, van Beek JHDA, Distel MA, de Moor MHM, Smit DJA, Minica CC, Ligthart L, Geels LM, Abdellaoui A, Middeldorp CM, Hottenga JJ, Willemsen G, de Geus EJC, Boomsma DI. Sex differences in genetic architecture of complex phenotypes? PLoS One 2012; 7:e47371. [PMID: 23272036 PMCID: PMC3525575 DOI: 10.1371/journal.pone.0047371] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2012] [Accepted: 09/11/2012] [Indexed: 12/02/2022] Open
Abstract
We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA) studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ) same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women.
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Affiliation(s)
- Jacqueline M Vink
- Netherlands Twin Register, Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
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The Young Netherlands Twin Register (YNTR): longitudinal twin and family studies in over 70,000 children. Twin Res Hum Genet 2012. [PMID: 23186620 DOI: 10.1017/thg.2012.118] [Citation(s) in RCA: 134] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The Netherlands Twin Register (NTR) began in 1987 with data collection in twins and their families, including families with newborn twins and triplets. Twenty-five years later, the NTR has collected at least one survey for 70,784 children, born after 1985. For the majority of twins, longitudinal data collection has been done by age-specific surveys. Shortly after giving birth, mothers receive a first survey with items on pregnancy and birth. At age 2, a survey on growth and achievement of milestones is sent. At ages 3, 7, 9/10, and 12 parents and teachers receive a series of surveys that are targeted at the development of emotional and behavior problems. From age 14 years onward, adolescent twins and their siblings report on their behavior problems, health, and lifestyle. When the twins are 18 years and older, parents are also invited to take part in survey studies. In sub-groups of different ages, in-depth phenotyping was done for IQ, electroencephalography , MRI, growth, hormones, neuropsychological assessments, and cardiovascular measures. DNA and biological samples have also been collected and large numbers of twin pairs and parents have been genotyped for zygosity by either micro-satellites or sets of short nucleotide polymorphisms and repeat polymorphisms in candidate genes. Subject recruitment and data collection is still ongoing and the longitudinal database is growing. Data collection by record linkage in the Netherlands is beginning and we expect these combined longitudinal data to provide increased insights into the genetic etiology of development of mental and physical health in children and adolescents.
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Abstract
This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.
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